Package acmpca provides the API client, operations, and parameter types for AWS Certificate Manager Private Certificate Authority. This is the Amazon Web Services Private Certificate Authority API Reference. It provides descriptions, syntax, and usage examples for each of the actions and data types involved in creating and managing a private certificate authority (CA) for your organization. The documentation for each action shows the API request parameters and the JSON response. Alternatively, you can use one of the Amazon Web Services SDKs to access an API that is tailored to the programming language or platform that you prefer. For more information, see Amazon Web Services SDKs. Each Amazon Web Services Private CA API operation has a quota that determines the number of times the operation can be called per second. Amazon Web Services Private CA throttles API requests at different rates depending on the operation. Throttling means that Amazon Web Services Private CA rejects an otherwise valid request because the request exceeds the operation's quota for the number of requests per second. When a request is throttled, Amazon Web Services Private CA returns a ThrottlingExceptionerror. Amazon Web Services Private CA does not guarantee a minimum request rate for APIs. To see an up-to-date list of your Amazon Web Services Private CA quotas, or to request a quota increase, log into your Amazon Web Services account and visit the Service Quotasconsole.
Package date provides functionality for working with dates. This package introduces a light-weight Date type that is storage-efficient and covenient for calendrical calculations and date parsing and formatting (including years outside the [0,9999] interval). This package follows very closely the design of package time (http://golang.org/pkg/time/) in the standard library, many of the Date methods are implemented using the corresponding methods of the time.Time type, and much of the documentation is copied directly from that package. https://golang.org/src/time/time.go https://en.wikipedia.org/wiki/Gregorian_calendar https://en.wikipedia.org/wiki/Proleptic_Gregorian_calendar https://en.wikipedia.org/wiki/Astronomical_year_numbering https://en.wikipedia.org/wiki/ISO_8601 https://tools.ietf.org/html/rfc822 https://tools.ietf.org/html/rfc850 https://tools.ietf.org/html/rfc1123 https://tools.ietf.org/html/rfc3339
Package vcs exposes functions for resolving import paths and using version control systems, which can be used to implement behavior similar to the standard "go get" command. Deprecated: Use the go list command with -json flag instead, which implements up-to-date import path resolution behavior, module support, and includes the latest security fixes. This package was a copy of internal code in package cmd/go/internal/get before module support, modified to make the identifiers exported. It was provided here for developers who wanted to write tools with similar semantics. It needed to be manually kept in sync with upstream when changes were made to cmd/go/internal/get, as tracked in go.dev/issue/11490. By now, it has diverged significantly from upstream cmd/go/internal/get behavior and will not receive any further updates.
Package autorest implements an HTTP request pipeline suitable for use across multiple go-routines and provides the shared routines relied on by AutoRest (see https://github.com/Azure/autorest/) generated Go code. The package breaks sending and responding to HTTP requests into three phases: Preparing, Sending, and Responding. A typical pattern is: Each phase relies on decorators to modify and / or manage processing. Decorators may first modify and then pass the data along, pass the data first and then modify the result, or wrap themselves around passing the data (such as a logger might do). Decorators run in the order provided. For example, the following: will set the URL to: Preparers and Responders may be shared and re-used (assuming the underlying decorators support sharing and re-use). Performant use is obtained by creating one or more Preparers and Responders shared among multiple go-routines, and a single Sender shared among multiple sending go-routines, all bound together by means of input / output channels. Decorators hold their passed state within a closure (such as the path components in the example above). Be careful to share Preparers and Responders only in a context where such held state applies. For example, it may not make sense to share a Preparer that applies a query string from a fixed set of values. Similarly, sharing a Responder that reads the response body into a passed struct (e.g., ByUnmarshallingJson) is likely incorrect. Lastly, the Swagger specification (https://swagger.io) that drives AutoRest (https://github.com/Azure/autorest/) precisely defines two date forms: date and date-time. The github.com/Azure/go-autorest/autorest/date package provides time.Time derivations to ensure correct parsing and formatting. Errors raised by autorest objects and methods will conform to the autorest.Error interface. See the included examples for more detail. For details on the suggested use of this package by generated clients, see the Client described below.
Package validator implements value validations for structs and individual fields based on tags. It can also handle Cross-Field and Cross-Struct validation for nested structs and has the ability to dive into arrays and maps of any type. see more examples https://github.com/go-playground/validator/tree/v9/_examples Doing things this way is actually the way the standard library does, see the file.Open method here: The authors return type "error" to avoid the issue discussed in the following, where err is always != nil: Validator only InvalidValidationError for bad validation input, nil or ValidationErrors as type error; so, in your code all you need to do is check if the error returned is not nil, and if it's not check if error is InvalidValidationError ( if necessary, most of the time it isn't ) type cast it to type ValidationErrors like so err.(validator.ValidationErrors). Custom Validation functions can be added. Example: Cross-Field Validation can be done via the following tags: If, however, some custom cross-field validation is required, it can be done using a custom validation. Why not just have cross-fields validation tags (i.e. only eqcsfield and not eqfield)? The reason is efficiency. If you want to check a field within the same struct "eqfield" only has to find the field on the same struct (1 level). But, if we used "eqcsfield" it could be multiple levels down. Example: Multiple validators on a field will process in the order defined. Example: Bad Validator definitions are not handled by the library. Example: Baked In Cross-Field validation only compares fields on the same struct. If Cross-Field + Cross-Struct validation is needed you should implement your own custom validator. Comma (",") is the default separator of validation tags. If you wish to have a comma included within the parameter (i.e. excludesall=,) you will need to use the UTF-8 hex representation 0x2C, which is replaced in the code as a comma, so the above will become excludesall=0x2C. Pipe ("|") is the 'or' validation tags deparator. If you wish to have a pipe included within the parameter i.e. excludesall=| you will need to use the UTF-8 hex representation 0x7C, which is replaced in the code as a pipe, so the above will become excludesall=0x7C Here is a list of the current built in validators: Tells the validation to skip this struct field; this is particularly handy in ignoring embedded structs from being validated. (Usage: -) This is the 'or' operator allowing multiple validators to be used and accepted. (Usage: rbg|rgba) <-- this would allow either rgb or rgba colors to be accepted. This can also be combined with 'and' for example ( Usage: omitempty,rgb|rgba) When a field that is a nested struct is encountered, and contains this flag any validation on the nested struct will be run, but none of the nested struct fields will be validated. This is useful if inside of your program you know the struct will be valid, but need to verify it has been assigned. NOTE: only "required" and "omitempty" can be used on a struct itself. Same as structonly tag except that any struct level validations will not run. Allows conditional validation, for example if a field is not set with a value (Determined by the "required" validator) then other validation such as min or max won't run, but if a value is set validation will run. This tells the validator to dive into a slice, array or map and validate that level of the slice, array or map with the validation tags that follow. Multidimensional nesting is also supported, each level you wish to dive will require another dive tag. dive has some sub-tags, 'keys' & 'endkeys', please see the Keys & EndKeys section just below. Example #1 Example #2 Keys & EndKeys These are to be used together directly after the dive tag and tells the validator that anything between 'keys' and 'endkeys' applies to the keys of a map and not the values; think of it like the 'dive' tag, but for map keys instead of values. Multidimensional nesting is also supported, each level you wish to validate will require another 'keys' and 'endkeys' tag. These tags are only valid for maps. Example #1 Example #2 This validates that the value is not the data types default zero value. For numbers ensures value is not zero. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. The field under validation must be present and not empty only if any of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only if all of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: The field under validation must be present and not empty only when any of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only when all of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: This validates that the value is the default value and is almost the opposite of required. For numbers, length will ensure that the value is equal to the parameter given. For strings, it checks that the string length is exactly that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, max will ensure that the value is less than or equal to the parameter given. For strings, it checks that the string length is at most that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, min will ensure that the value is greater or equal to the parameter given. For strings, it checks that the string length is at least that number of characters. For slices, arrays, and maps, validates the number of items. For strings & numbers, eq will ensure that the value is equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings & numbers, ne will ensure that the value is not equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings, ints, and uints, oneof will ensure that the value is one of the values in the parameter. The parameter should be a list of values separated by whitespace. Values may be strings or numbers. For numbers, this will ensure that the value is greater than the parameter given. For strings, it checks that the string length is greater than that number of characters. For slices, arrays and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than time.Now.UTC(). Same as 'min' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than or equal to time.Now.UTC(). For numbers, this will ensure that the value is less than the parameter given. For strings, it checks that the string length is less than that number of characters. For slices, arrays, and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than time.Now.UTC(). Same as 'max' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than or equal to time.Now.UTC(). This will validate the field value against another fields value either within a struct or passed in field. Example #1: Example #2: Field Equals Another Field (relative) This does the same as eqfield except that it validates the field provided relative to the top level struct. This will validate the field value against another fields value either within a struct or passed in field. Examples: Field Does Not Equal Another Field (relative) This does the same as nefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltefield except that it validates the field provided relative to the top level struct. This does the same as contains except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. This does the same as excludes except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. For arrays & slices, unique will ensure that there are no duplicates. For maps, unique will ensure that there are no duplicate values. For slices of struct, unique will ensure that there are no duplicate values in a field of the struct specified via a parameter. This validates that a string value contains ASCII alpha characters only This validates that a string value contains ASCII alphanumeric characters only This validates that a string value contains unicode alpha characters only This validates that a string value contains unicode alphanumeric characters only This validates that a string value contains a basic numeric value. basic excludes exponents etc... for integers or float it returns true. This validates that a string value contains a valid hexadecimal. This validates that a string value contains a valid hex color including hashtag (#) This validates that a string value contains a valid rgb color This validates that a string value contains a valid rgba color This validates that a string value contains a valid hsl color This validates that a string value contains a valid hsla color This validates that a string value contains a valid email This may not conform to all possibilities of any rfc standard, but neither does any email provider accept all possibilities. This validates that a string value contains a valid file path and that the file exists on the machine. This is done using os.Stat, which is a platform independent function. This validates that a string value contains a valid url This will accept any url the golang request uri accepts but must contain a schema for example http:// or rtmp:// This validates that a string value contains a valid uri This will accept any uri the golang request uri accepts This validataes that a string value contains a valid URN according to the RFC 2141 spec. This validates that a string value contains a valid base64 value. Although an empty string is valid base64 this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid base64 URL safe value according the the RFC4648 spec. Although an empty string is a valid base64 URL safe value, this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid bitcoin address. The format of the string is checked to ensure it matches one of the three formats P2PKH, P2SH and performs checksum validation. Bitcoin Bech32 Address (segwit) This validates that a string value contains a valid bitcoin Bech32 address as defined by bip-0173 (https://github.com/bitcoin/bips/blob/master/bip-0173.mediawiki) Special thanks to Pieter Wuille for providng reference implementations. This validates that a string value contains a valid ethereum address. The format of the string is checked to ensure it matches the standard Ethereum address format Full validation is blocked by https://github.com/golang/crypto/pull/28 This validates that a string value contains the substring value. This validates that a string value contains any Unicode code points in the substring value. This validates that a string value contains the supplied rune value. This validates that a string value does not contain the substring value. This validates that a string value does not contain any Unicode code points in the substring value. This validates that a string value does not contain the supplied rune value. This validates that a string value starts with the supplied string value This validates that a string value ends with the supplied string value This validates that a string value contains a valid isbn10 or isbn13 value. This validates that a string value contains a valid isbn10 value. This validates that a string value contains a valid isbn13 value. This validates that a string value contains a valid UUID. Uppercase UUID values will not pass - use `uuid_rfc4122` instead. This validates that a string value contains a valid version 3 UUID. Uppercase UUID values will not pass - use `uuid3_rfc4122` instead. This validates that a string value contains a valid version 4 UUID. Uppercase UUID values will not pass - use `uuid4_rfc4122` instead. This validates that a string value contains a valid version 5 UUID. Uppercase UUID values will not pass - use `uuid5_rfc4122` instead. This validates that a string value contains only ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains only printable ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains one or more multibyte characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains a valid DataURI. NOTE: this will also validate that the data portion is valid base64 This validates that a string value contains a valid latitude. This validates that a string value contains a valid longitude. This validates that a string value contains a valid U.S. Social Security Number. This validates that a string value contains a valid IP Address. This validates that a string value contains a valid v4 IP Address. This validates that a string value contains a valid v6 IP Address. This validates that a string value contains a valid CIDR Address. This validates that a string value contains a valid v4 CIDR Address. This validates that a string value contains a valid v6 CIDR Address. This validates that a string value contains a valid resolvable TCP Address. This validates that a string value contains a valid resolvable v4 TCP Address. This validates that a string value contains a valid resolvable v6 TCP Address. This validates that a string value contains a valid resolvable UDP Address. This validates that a string value contains a valid resolvable v4 UDP Address. This validates that a string value contains a valid resolvable v6 UDP Address. This validates that a string value contains a valid resolvable IP Address. This validates that a string value contains a valid resolvable v4 IP Address. This validates that a string value contains a valid resolvable v6 IP Address. This validates that a string value contains a valid Unix Address. This validates that a string value contains a valid MAC Address. Note: See Go's ParseMAC for accepted formats and types: This validates that a string value is a valid Hostname according to RFC 952 https://tools.ietf.org/html/rfc952 This validates that a string value is a valid Hostname according to RFC 1123 https://tools.ietf.org/html/rfc1123 Full Qualified Domain Name (FQDN) This validates that a string value contains a valid FQDN. This validates that a string value appears to be an HTML element tag including those described at https://developer.mozilla.org/en-US/docs/Web/HTML/Element This validates that a string value is a proper character reference in decimal or hexadecimal format This validates that a string value is percent-encoded (URL encoded) according to https://tools.ietf.org/html/rfc3986#section-2.1 This validates that a string value contains a valid directory and that it exists on the machine. This is done using os.Stat, which is a platform independent function. NOTE: When returning an error, the tag returned in "FieldError" will be the alias tag unless the dive tag is part of the alias. Everything after the dive tag is not reported as the alias tag. Also, the "ActualTag" in the before case will be the actual tag within the alias that failed. Here is a list of the current built in alias tags: Validator notes: A collection of validation rules that are frequently needed but are more complex than the ones found in the baked in validators. A non standard validator must be registered manually like you would with your own custom validation functions. Example of registration and use: Here is a list of the current non standard validators: This package panics when bad input is provided, this is by design, bad code like that should not make it to production.
Package goka is a stateful stream processing library for Apache Kafka (version 0.9+) that eases the development of microservices. Goka extends the concept of consumer group with a group table, which represents the state of the group. A microservice modifies and serves the content of a table employing two complementary object types: processors and views. A processor is a set of callback functions that modify the group table when messages arrive and may also emit messages into other topics. Messages as well as rows in the group table are key-value pairs. Callbacks receive the arriving message and the row addressed by the message's key. In Kafka, keys are used to partition topics. A goka processor consumes from a set of co-partitioned topics (topics with the same number of partitions and the same key range). A group topic keeps track of the group table updates, allowing for recovery and rebalancing of processors: When multiple processor instances start in the same consumer group, the instances split the co-partitioned input topics and load the respective group table partitions from the group topic. A local disk storage minimizes recovery time by caching partitions of group table. A view is a materialized (ie, persistent) cache of a group table. A view subscribes for the updates of all partitions of a group table and keeps local disk storage in sync with the group topic. With a view, one can easily serve up-to-date content of the group table via, for example, gRPC. Package goka is a generated GoMock package. Package goka is a generated GoMock package. Package goka is a generated GoMock package.
Package ql implements a pure Go embedded SQL database engine. QL is a member of the SQL family of languages. It is less complex and less powerful than SQL (whichever specification SQL is considered to be). 2018-08-02: Release v1.2.0 adds initial support for Go modules. 2017-01-10: Release v1.1.0 fixes some bugs and adds a configurable WAL headroom. 2016-07-29: Release v1.0.6 enables alternatively using = instead of == for equality operation. 2016-07-11: Release v1.0.5 undoes vendoring of lldb. QL now uses stable lldb (github.com/cznic/lldb). 2016-07-06: Release v1.0.4 fixes a panic when closing the WAL file. 2016-04-03: Release v1.0.3 fixes a data race. 2016-03-23: Release v1.0.2 vendors github.com/cznic/exp/lldb and github.com/camlistore/go4/lock. 2016-03-17: Release v1.0.1 adjusts for latest goyacc. Parser error messages are improved and changed, but their exact form is not considered a API change. 2016-03-05: The current version has been tagged v1.0.0. 2015-06-15: To improve compatibility with other SQL implementations, the count built-in aggregate function now accepts * as its argument. 2015-05-29: The execution planner was rewritten from scratch. It should use indices in all places where they were used before plus in some additional situations. It is possible to investigate the plan using the newly added EXPLAIN statement. The QL tool is handy for such analysis. If the planner would have used an index, but no such exists, the plan includes hints in form of copy/paste ready CREATE INDEX statements. The planner is still quite simple and a lot of work on it is yet ahead. You can help this process by filling an issue with a schema and query which fails to use an index or indices when it should, in your opinion. Bonus points for including output of `ql 'explain <query>'`. 2015-05-09: The grammar of the CREATE INDEX statement now accepts an expression list instead of a single expression, which was further limited to just a column name or the built-in id(). As a side effect, composite indices are now functional. However, the values in the expression-list style index are not yet used by other statements or the statement/query planner. The composite index is useful while having UNIQUE clause to check for semantically duplicate rows before they get added to the table or when such a row is mutated using the UPDATE statement and the expression-list style index tuple of the row is thus recomputed. 2015-05-02: The Schema field of table __Table now correctly reflects any column constraints and/or defaults. Also, the (*DB).Info method now has that information provided in new ColumInfo fields NotNull, Constraint and Default. 2015-04-20: Added support for {LEFT,RIGHT,FULL} [OUTER] JOIN. 2015-04-18: Column definitions can now have constraints and defaults. Details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. 2015-03-06: New built-in functions formatFloat and formatInt. Thanks urandom! (https://github.com/urandom) 2015-02-16: IN predicate now accepts a SELECT statement. See the updated "Predicates" section. 2015-01-17: Logical operators || and && have now alternative spellings: OR and AND (case insensitive). AND was a keyword before, but OR is a new one. This can possibly break existing queries. For the record, it's a good idea to not use any name appearing in, for example, [7] in your queries as the list of QL's keywords may expand for gaining better compatibility with existing SQL "standards". 2015-01-12: ACID guarantees were tightened at the cost of performance in some cases. The write collecting window mechanism, a formerly used implementation detail, was removed. Inserting rows one by one in a transaction is now slow. I mean very slow. Try to avoid inserting single rows in a transaction. Instead, whenever possible, perform batch updates of tens to, say thousands of rows in a single transaction. See also: http://www.sqlite.org/faq.html#q19, the discussed synchronization principles involved are the same as for QL, modulo minor details. Note: A side effect is that closing a DB before exiting an application, both for the Go API and through database/sql driver, is no more required, strictly speaking. Beware that exiting an application while there is an open (uncommitted) transaction in progress means losing the transaction data. However, the DB will not become corrupted because of not closing it. Nor that was the case before, but formerly failing to close a DB could have resulted in losing the data of the last transaction. 2014-09-21: id() now optionally accepts a single argument - a table name. 2014-09-01: Added the DB.Flush() method and the LIKE pattern matching predicate. 2014-08-08: The built in functions max and min now accept also time values. Thanks opennota! (https://github.com/opennota) 2014-06-05: RecordSet interface extended by new methods FirstRow and Rows. 2014-06-02: Indices on id() are now used by SELECT statements. 2014-05-07: Introduction of Marshal, Schema, Unmarshal. 2014-04-15: Added optional IF NOT EXISTS clause to CREATE INDEX and optional IF EXISTS clause to DROP INDEX. 2014-04-12: The column Unique in the virtual table __Index was renamed to IsUnique because the old name is a keyword. Unfortunately, this is a breaking change, sorry. 2014-04-11: Introduction of LIMIT, OFFSET. 2014-04-10: Introduction of query rewriting. 2014-04-07: Introduction of indices. QL imports zappy[8], a block-based compressor, which speeds up its performance by using a C version of the compression/decompression algorithms. If a CGO-free (pure Go) version of QL, or an app using QL, is required, please include 'purego' in the -tags option of go {build,get,install}. For example: If zappy was installed before installing QL, it might be necessary to rebuild zappy first (or rebuild QL with all its dependencies using the -a option): The syntax is specified using Extended Backus-Naur Form (EBNF) Lower-case production names are used to identify lexical tokens. Non-terminals are in CamelCase. Lexical tokens are enclosed in double quotes "" or back quotes “. The form a … b represents the set of characters from a through b as alternatives. The horizontal ellipsis … is also used elsewhere in the spec to informally denote various enumerations or code snippets that are not further specified. QL source code is Unicode text encoded in UTF-8. The text is not canonicalized, so a single accented code point is distinct from the same character constructed from combining an accent and a letter; those are treated as two code points. For simplicity, this document will use the unqualified term character to refer to a Unicode code point in the source text. Each code point is distinct; for instance, upper and lower case letters are different characters. Implementation restriction: For compatibility with other tools, the parser may disallow the NUL character (U+0000) in the statement. Implementation restriction: A byte order mark is disallowed anywhere in QL statements. The following terms are used to denote specific character classes The underscore character _ (U+005F) is considered a letter. Lexical elements are comments, tokens, identifiers, keywords, operators and delimiters, integer, floating-point, imaginary, rune and string literals and QL parameters. Line comments start with the character sequence // or -- and stop at the end of the line. A line comment acts like a space. General comments start with the character sequence /* and continue through the character sequence */. A general comment acts like a space. Comments do not nest. Tokens form the vocabulary of QL. There are four classes: identifiers, keywords, operators and delimiters, and literals. White space, formed from spaces (U+0020), horizontal tabs (U+0009), carriage returns (U+000D), and newlines (U+000A), is ignored except as it separates tokens that would otherwise combine into a single token. The formal grammar uses semicolons ";" as separators of QL statements. A single QL statement or the last QL statement in a list of statements can have an optional semicolon terminator. (Actually a separator from the following empty statement.) Identifiers name entities such as tables or record set columns. An identifier is a sequence of one or more letters and digits. The first character in an identifier must be a letter. For example No identifiers are predeclared, however note that no keyword can be used as an identifier. Identifiers starting with two underscores are used for meta data virtual tables names. For forward compatibility, users should generally avoid using any identifiers starting with two underscores. For example The following keywords are reserved and may not be used as identifiers. Keywords are not case sensitive. The following character sequences represent operators, delimiters, and other special tokens Operators consisting of more than one character are referred to by names in the rest of the documentation An integer literal is a sequence of digits representing an integer constant. An optional prefix sets a non-decimal base: 0 for octal, 0x or 0X for hexadecimal. In hexadecimal literals, letters a-f and A-F represent values 10 through 15. For example A floating-point literal is a decimal representation of a floating-point constant. It has an integer part, a decimal point, a fractional part, and an exponent part. The integer and fractional part comprise decimal digits; the exponent part is an e or E followed by an optionally signed decimal exponent. One of the integer part or the fractional part may be elided; one of the decimal point or the exponent may be elided. For example An imaginary literal is a decimal representation of the imaginary part of a complex constant. It consists of a floating-point literal or decimal integer followed by the lower-case letter i. For example A rune literal represents a rune constant, an integer value identifying a Unicode code point. A rune literal is expressed as one or more characters enclosed in single quotes. Within the quotes, any character may appear except single quote and newline. A single quoted character represents the Unicode value of the character itself, while multi-character sequences beginning with a backslash encode values in various formats. The simplest form represents the single character within the quotes; since QL statements are Unicode characters encoded in UTF-8, multiple UTF-8-encoded bytes may represent a single integer value. For instance, the literal 'a' holds a single byte representing a literal a, Unicode U+0061, value 0x61, while 'ä' holds two bytes (0xc3 0xa4) representing a literal a-dieresis, U+00E4, value 0xe4. Several backslash escapes allow arbitrary values to be encoded as ASCII text. There are four ways to represent the integer value as a numeric constant: \x followed by exactly two hexadecimal digits; \u followed by exactly four hexadecimal digits; \U followed by exactly eight hexadecimal digits, and a plain backslash \ followed by exactly three octal digits. In each case the value of the literal is the value represented by the digits in the corresponding base. Although these representations all result in an integer, they have different valid ranges. Octal escapes must represent a value between 0 and 255 inclusive. Hexadecimal escapes satisfy this condition by construction. The escapes \u and \U represent Unicode code points so within them some values are illegal, in particular those above 0x10FFFF and surrogate halves. After a backslash, certain single-character escapes represent special values All other sequences starting with a backslash are illegal inside rune literals. For example A string literal represents a string constant obtained from concatenating a sequence of characters. There are two forms: raw string literals and interpreted string literals. Raw string literals are character sequences between back quotes “. Within the quotes, any character is legal except back quote. The value of a raw string literal is the string composed of the uninterpreted (implicitly UTF-8-encoded) characters between the quotes; in particular, backslashes have no special meaning and the string may contain newlines. Carriage returns inside raw string literals are discarded from the raw string value. Interpreted string literals are character sequences between double quotes "". The text between the quotes, which may not contain newlines, forms the value of the literal, with backslash escapes interpreted as they are in rune literals (except that \' is illegal and \" is legal), with the same restrictions. The three-digit octal (\nnn) and two-digit hexadecimal (\xnn) escapes represent individual bytes of the resulting string; all other escapes represent the (possibly multi-byte) UTF-8 encoding of individual characters. Thus inside a string literal \377 and \xFF represent a single byte of value 0xFF=255, while ÿ, \u00FF, \U000000FF and \xc3\xbf represent the two bytes 0xc3 0xbf of the UTF-8 encoding of character U+00FF. For example These examples all represent the same string If the statement source represents a character as two code points, such as a combining form involving an accent and a letter, the result will be an error if placed in a rune literal (it is not a single code point), and will appear as two code points if placed in a string literal. Literals are assigned their values from the respective text representation at "compile" (parse) time. QL parameters provide the same functionality as literals, but their value is assigned at execution time from an expression list passed to DB.Run or DB.Execute. Using '?' or '$' is completely equivalent. For example Keywords 'false' and 'true' (not case sensitive) represent the two possible constant values of type bool (also not case sensitive). Keyword 'NULL' (not case sensitive) represents an untyped constant which is assignable to any type. NULL is distinct from any other value of any type. A type determines the set of values and operations specific to values of that type. A type is specified by a type name. Named instances of the boolean, numeric, and string types are keywords. The names are not case sensitive. Note: The blob type is exchanged between the back end and the API as []byte. On 32 bit platforms this limits the size which the implementation can handle to 2G. A boolean type represents the set of Boolean truth values denoted by the predeclared constants true and false. The predeclared boolean type is bool. A duration type represents the elapsed time between two instants as an int64 nanosecond count. The representation limits the largest representable duration to approximately 290 years. A numeric type represents sets of integer or floating-point values. The predeclared architecture-independent numeric types are The value of an n-bit integer is n bits wide and represented using two's complement arithmetic. Conversions are required when different numeric types are mixed in an expression or assignment. A string type represents the set of string values. A string value is a (possibly empty) sequence of bytes. The case insensitive keyword for the string type is 'string'. The length of a string (its size in bytes) can be discovered using the built-in function len. A time type represents an instant in time with nanosecond precision. Each time has associated with it a location, consulted when computing the presentation form of the time. The following functions are implicitly declared An expression specifies the computation of a value by applying operators and functions to operands. Operands denote the elementary values in an expression. An operand may be a literal, a (possibly qualified) identifier denoting a constant or a function or a table/record set column, or a parenthesized expression. A qualified identifier is an identifier qualified with a table/record set name prefix. For example Primary expression are the operands for unary and binary expressions. For example A primary expression of the form denotes the element of a string indexed by x. Its type is byte. The value x is called the index. The following rules apply - The index x must be of integer type except bigint or duration; it is in range if 0 <= x < len(s), otherwise it is out of range. - A constant index must be non-negative and representable by a value of type int. - A constant index must be in range if the string a is a literal. - If x is out of range at run time, a run-time error occurs. - s[x] is the byte at index x and the type of s[x] is byte. If s is NULL or x is NULL then the result is NULL. Otherwise s[x] is illegal. For a string, the primary expression constructs a substring. The indices low and high select which elements appear in the result. The result has indices starting at 0 and length equal to high - low. For convenience, any of the indices may be omitted. A missing low index defaults to zero; a missing high index defaults to the length of the sliced operand The indices low and high are in range if 0 <= low <= high <= len(a), otherwise they are out of range. A constant index must be non-negative and representable by a value of type int. If both indices are constant, they must satisfy low <= high. If the indices are out of range at run time, a run-time error occurs. Integer values of type bigint or duration cannot be used as indices. If s is NULL the result is NULL. If low or high is not omitted and is NULL then the result is NULL. Given an identifier f denoting a predeclared function, calls f with arguments a1, a2, … an. Arguments are evaluated before the function is called. The type of the expression is the result type of f. In a function call, the function value and arguments are evaluated in the usual order. After they are evaluated, the parameters of the call are passed by value to the function and the called function begins execution. The return value of the function is passed by value when the function returns. Calling an undefined function causes a compile-time error. Operators combine operands into expressions. Comparisons are discussed elsewhere. For other binary operators, the operand types must be identical unless the operation involves shifts or untyped constants. For operations involving constants only, see the section on constant expressions. Except for shift operations, if one operand is an untyped constant and the other operand is not, the constant is converted to the type of the other operand. The right operand in a shift expression must have unsigned integer type or be an untyped constant that can be converted to unsigned integer type. If the left operand of a non-constant shift expression is an untyped constant, the type of the constant is what it would be if the shift expression were replaced by its left operand alone. Expressions of the form yield a boolean value true if expr2, a regular expression, matches expr1 (see also [6]). Both expression must be of type string. If any one of the expressions is NULL the result is NULL. Predicates are special form expressions having a boolean result type. Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be comparable as defined in "Comparison operators". Another form of the IN predicate creates the expression list from a result of a SelectStmt. The SelectStmt must select only one column. The produced expression list is resource limited by the memory available to the process. NULL values produced by the SelectStmt are ignored, but if all records of the SelectStmt are NULL the predicate yields NULL. The select statement is evaluated only once. If the type of expr is not the same as the type of the field returned by the SelectStmt then the set operation yields false. The type of the column returned by the SelectStmt must be one of the simple (non blob-like) types: Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be ordered as defined in "Comparison operators". Expressions of the form yield a boolean value true if expr does not have a specific type (case A) or if expr has a specific type (case B). In other cases the result is a boolean value false. Unary operators have the highest precedence. There are five precedence levels for binary operators. Multiplication operators bind strongest, followed by addition operators, comparison operators, && (logical AND), and finally || (logical OR) Binary operators of the same precedence associate from left to right. For instance, x / y * z is the same as (x / y) * z. Note that the operator precedence is reflected explicitly by the grammar. Arithmetic operators apply to numeric values and yield a result of the same type as the first operand. The four standard arithmetic operators (+, -, *, /) apply to integer, rational, floating-point, and complex types; + also applies to strings; +,- also applies to times. All other arithmetic operators apply to integers only. sum integers, rationals, floats, complex values, strings difference integers, rationals, floats, complex values, times product integers, rationals, floats, complex values / quotient integers, rationals, floats, complex values % remainder integers & bitwise AND integers | bitwise OR integers ^ bitwise XOR integers &^ bit clear (AND NOT) integers << left shift integer << unsigned integer >> right shift integer >> unsigned integer Strings can be concatenated using the + operator String addition creates a new string by concatenating the operands. A value of type duration can be added to or subtracted from a value of type time. Times can subtracted from each other producing a value of type duration. For two integer values x and y, the integer quotient q = x / y and remainder r = x % y satisfy the following relationships with x / y truncated towards zero ("truncated division"). As an exception to this rule, if the dividend x is the most negative value for the int type of x, the quotient q = x / -1 is equal to x (and r = 0). If the divisor is a constant expression, it must not be zero. If the divisor is zero at run time, a run-time error occurs. If the dividend is non-negative and the divisor is a constant power of 2, the division may be replaced by a right shift, and computing the remainder may be replaced by a bitwise AND operation The shift operators shift the left operand by the shift count specified by the right operand. They implement arithmetic shifts if the left operand is a signed integer and logical shifts if it is an unsigned integer. There is no upper limit on the shift count. Shifts behave as if the left operand is shifted n times by 1 for a shift count of n. As a result, x << 1 is the same as x*2 and x >> 1 is the same as x/2 but truncated towards negative infinity. For integer operands, the unary operators +, -, and ^ are defined as follows For floating-point and complex numbers, +x is the same as x, while -x is the negation of x. The result of a floating-point or complex division by zero is not specified beyond the IEEE-754 standard; whether a run-time error occurs is implementation-specific. Whenever any operand of any arithmetic operation, unary or binary, is NULL, as well as in the case of the string concatenating operation, the result is NULL. For unsigned integer values, the operations +, -, *, and << are computed modulo 2n, where n is the bit width of the unsigned integer's type. Loosely speaking, these unsigned integer operations discard high bits upon overflow, and expressions may rely on “wrap around”. For signed integers with a finite bit width, the operations +, -, *, and << may legally overflow and the resulting value exists and is deterministically defined by the signed integer representation, the operation, and its operands. No exception is raised as a result of overflow. An evaluator may not optimize an expression under the assumption that overflow does not occur. For instance, it may not assume that x < x + 1 is always true. Integers of type bigint and rationals do not overflow but their handling is limited by the memory resources available to the program. Comparison operators compare two operands and yield a boolean value. In any comparison, the first operand must be of same type as is the second operand, or vice versa. The equality operators == and != apply to operands that are comparable. The ordering operators <, <=, >, and >= apply to operands that are ordered. These terms and the result of the comparisons are defined as follows - Boolean values are comparable. Two boolean values are equal if they are either both true or both false. - Complex values are comparable. Two complex values u and v are equal if both real(u) == real(v) and imag(u) == imag(v). - Integer values are comparable and ordered, in the usual way. Note that durations are integers. - Floating point values are comparable and ordered, as defined by the IEEE-754 standard. - Rational values are comparable and ordered, in the usual way. - String and Blob values are comparable and ordered, lexically byte-wise. - Time values are comparable and ordered. Whenever any operand of any comparison operation is NULL, the result is NULL. Note that slices are always of type string. Logical operators apply to boolean values and yield a boolean result. The right operand is evaluated conditionally. The truth tables for logical operations with NULL values Conversions are expressions of the form T(x) where T is a type and x is an expression that can be converted to type T. A constant value x can be converted to type T in any of these cases: - x is representable by a value of type T. - x is a floating-point constant, T is a floating-point type, and x is representable by a value of type T after rounding using IEEE 754 round-to-even rules. The constant T(x) is the rounded value. - x is an integer constant and T is a string type. The same rule as for non-constant x applies in this case. Converting a constant yields a typed constant as result. A non-constant value x can be converted to type T in any of these cases: - x has type T. - x's type and T are both integer or floating point types. - x's type and T are both complex types. - x is an integer, except bigint or duration, and T is a string type. Specific rules apply to (non-constant) conversions between numeric types or to and from a string type. These conversions may change the representation of x and incur a run-time cost. All other conversions only change the type but not the representation of x. A conversion of NULL to any type yields NULL. For the conversion of non-constant numeric values, the following rules apply 1. When converting between integer types, if the value is a signed integer, it is sign extended to implicit infinite precision; otherwise it is zero extended. It is then truncated to fit in the result type's size. For example, if v == uint16(0x10F0), then uint32(int8(v)) == 0xFFFFFFF0. The conversion always yields a valid value; there is no indication of overflow. 2. When converting a floating-point number to an integer, the fraction is discarded (truncation towards zero). 3. When converting an integer or floating-point number to a floating-point type, or a complex number to another complex type, the result value is rounded to the precision specified by the destination type. For instance, the value of a variable x of type float32 may be stored using additional precision beyond that of an IEEE-754 32-bit number, but float32(x) represents the result of rounding x's value to 32-bit precision. Similarly, x + 0.1 may use more than 32 bits of precision, but float32(x + 0.1) does not. In all non-constant conversions involving floating-point or complex values, if the result type cannot represent the value the conversion succeeds but the result value is implementation-dependent. 1. Converting a signed or unsigned integer value to a string type yields a string containing the UTF-8 representation of the integer. Values outside the range of valid Unicode code points are converted to "\uFFFD". 2. Converting a blob to a string type yields a string whose successive bytes are the elements of the blob. 3. Converting a value of a string type to a blob yields a blob whose successive elements are the bytes of the string. 4. Converting a value of a bigint type to a string yields a string containing the decimal decimal representation of the integer. 5. Converting a value of a string type to a bigint yields a bigint value containing the integer represented by the string value. A prefix of “0x” or “0X” selects base 16; the “0” prefix selects base 8, and a “0b” or “0B” prefix selects base 2. Otherwise the value is interpreted in base 10. An error occurs if the string value is not in any valid format. 6. Converting a value of a rational type to a string yields a string containing the decimal decimal representation of the rational in the form "a/b" (even if b == 1). 7. Converting a value of a string type to a bigrat yields a bigrat value containing the rational represented by the string value. The string can be given as a fraction "a/b" or as a floating-point number optionally followed by an exponent. An error occurs if the string value is not in any valid format. 8. Converting a value of a duration type to a string returns a string representing the duration in the form "72h3m0.5s". Leading zero units are omitted. As a special case, durations less than one second format using a smaller unit (milli-, micro-, or nanoseconds) to ensure that the leading digit is non-zero. The zero duration formats as 0, with no unit. 9. Converting a string value to a duration yields a duration represented by the string. A duration string is a possibly signed sequence of decimal numbers, each with optional fraction and a unit suffix, such as "300ms", "-1.5h" or "2h45m". Valid time units are "ns", "us" (or "µs"), "ms", "s", "m", "h". 10. Converting a time value to a string returns the time formatted using the format string When evaluating the operands of an expression or of function calls, operations are evaluated in lexical left-to-right order. For example, in the evaluation of the function calls and evaluation of c happen in the order h(), i(), j(), c. Floating-point operations within a single expression are evaluated according to the associativity of the operators. Explicit parentheses affect the evaluation by overriding the default associativity. In the expression x + (y + z) the addition y + z is performed before adding x. Statements control execution. The empty statement does nothing. Alter table statements modify existing tables. With the ADD clause it adds a new column to the table. The column must not exist. With the DROP clause it removes an existing column from a table. The column must exist and it must be not the only (last) column of the table. IOW, there cannot be a table with no columns. For example When adding a column to a table with existing data, the constraint clause of the ColumnDef cannot be used. Adding a constrained column to an empty table is fine. Begin transactions statements introduce a new transaction level. Every transaction level must be eventually balanced by exactly one of COMMIT or ROLLBACK statements. Note that when a transaction is roll-backed because of a statement failure then no explicit balancing of the respective BEGIN TRANSACTION is statement is required nor permitted. Failure to properly balance any opened transaction level may cause dead locks and/or lose of data updated in the uppermost opened but never properly closed transaction level. For example A database cannot be updated (mutated) outside of a transaction. Statements requiring a transaction A database is effectively read only outside of a transaction. Statements not requiring a transaction The commit statement closes the innermost transaction nesting level. If that's the outermost level then the updates to the DB made by the transaction are atomically made persistent. For example Create index statements create new indices. Index is a named projection of ordered values of a table column to the respective records. As a special case the id() of the record can be indexed. Index name must not be the same as any of the existing tables and it also cannot be the same as of any column name of the table the index is on. For example Now certain SELECT statements may use the indices to speed up joins and/or to speed up record set filtering when the WHERE clause is used; or the indices might be used to improve the performance when the ORDER BY clause is present. The UNIQUE modifier requires the indexed values tuple to be index-wise unique or have all values NULL. The optional IF NOT EXISTS clause makes the statement a no operation if the index already exists. A simple index consists of only one expression which must be either a column name or the built-in id(). A more complex and more general index is one that consists of more than one expression or its single expression does not qualify as a simple index. In this case the type of all expressions in the list must be one of the non blob-like types. Note: Blob-like types are blob, bigint, bigrat, time and duration. Create table statements create new tables. A column definition declares the column name and type. Table names and column names are case sensitive. Neither a table or an index of the same name may exist in the DB. For example The optional IF NOT EXISTS clause makes the statement a no operation if the table already exists. The optional constraint clause has two forms. The first one is found in many SQL dialects. This form prevents the data in column DepartmentName to be NULL. The second form allows an arbitrary boolean expression to be used to validate the column. If the value of the expression is true then the validation succeeded. If the value of the expression is false or NULL then the validation fails. If the value of the expression is not of type bool an error occurs. The optional DEFAULT clause is an expression which, if present, is substituted instead of a NULL value when the colum is assigned a value. Note that the constraint and/or default expressions may refer to other columns by name: When a table row is inserted by the INSERT INTO statement or when a table row is updated by the UPDATE statement, the order of operations is as follows: 1. The new values of the affected columns are set and the values of all the row columns become the named values which can be referred to in default expressions evaluated in step 2. 2. If any row column value is NULL and the DEFAULT clause is present in the column's definition, the default expression is evaluated and its value is set as the respective column value. 3. The values, potentially updated, of row columns become the named values which can be referred to in constraint expressions evaluated during step 4. 4. All row columns which definition has the constraint clause present will have that constraint checked. If any constraint violation is detected, the overall operation fails and no changes to the table are made. Delete from statements remove rows from a table, which must exist. For example If the WHERE clause is not present then all rows are removed and the statement is equivalent to the TRUNCATE TABLE statement. Drop index statements remove indices from the DB. The index must exist. For example The optional IF EXISTS clause makes the statement a no operation if the index does not exist. Drop table statements remove tables from the DB. The table must exist. For example The optional IF EXISTS clause makes the statement a no operation if the table does not exist. Insert into statements insert new rows into tables. New rows come from literal data, if using the VALUES clause, or are a result of select statement. In the later case the select statement is fully evaluated before the insertion of any rows is performed, allowing to insert values calculated from the same table rows are to be inserted into. If the ColumnNameList part is omitted then the number of values inserted in the row must be the same as are columns in the table. If the ColumnNameList part is present then the number of values per row must be same as the same number of column names. All other columns of the record are set to NULL. The type of the value assigned to a column must be the same as is the column's type or the value must be NULL. For example If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. Explain statement produces a recordset consisting of lines of text which describe the execution plan of a statement, if any. For example, the QL tool treats the explain statement specially and outputs the joined lines: The explanation may aid in uderstanding how a statement/query would be executed and if indices are used as expected - or which indices may possibly improve the statement performance. The create index statements above were directly copy/pasted in the terminal from the suggestions provided by the filter recordset pipeline part returned by the explain statement. If the statement has nothing special in its plan, the result is the original statement. To get an explanation of the select statement of the IN predicate, use the EXPLAIN statement with that particular select statement. The rollback statement closes the innermost transaction nesting level discarding any updates to the DB made by it. If that's the outermost level then the effects on the DB are as if the transaction never happened. For example The (temporary) record set from the last statement is returned and can be processed by the client. In this case the rollback is the same as 'DROP TABLE tmp;' but it can be a more complex operation. Select from statements produce recordsets. The optional DISTINCT modifier ensures all rows in the result recordset are unique. Either all of the resulting fields are returned ('*') or only those named in FieldList. RecordSetList is a list of table names or parenthesized select statements, optionally (re)named using the AS clause. The result can be filtered using a WhereClause and orderd by the OrderBy clause. For example If Recordset is a nested, parenthesized SelectStmt then it must be given a name using the AS clause if its field are to be accessible in expressions. A field is an named expression. Identifiers, not used as a type in conversion or a function name in the Call clause, denote names of (other) fields, values of which should be used in the expression. The expression can be named using the AS clause. If the AS clause is not present and the expression consists solely of a field name, then that field name is used as the name of the resulting field. Otherwise the field is unnamed. For example The SELECT statement can optionally enumerate the desired/resulting fields in a list. No two identical field names can appear in the list. When more than one record set is used in the FROM clause record set list, the result record set field names are rewritten to be qualified using the record set names. If a particular record set doesn't have a name, its respective fields became unnamed. The optional JOIN clause, for example is mostly equal to except that the rows from a which, when they appear in the cross join, never made expr to evaluate to true, are combined with a virtual row from b, containing all nulls, and added to the result set. For the RIGHT JOIN variant the discussed rules are used for rows from b not satisfying expr == true and the virtual, all-null row "comes" from a. The FULL JOIN adds the respective rows which would be otherwise provided by the separate executions of the LEFT JOIN and RIGHT JOIN variants. For more thorough OUTER JOIN discussion please see the Wikipedia article at [10]. Resultins rows of a SELECT statement can be optionally ordered by the ORDER BY clause. Collating proceeds by considering the expressions in the expression list left to right until a collating order is determined. Any possibly remaining expressions are not evaluated. All of the expression values must yield an ordered type or NULL. Ordered types are defined in "Comparison operators". Collating of elements having a NULL value is different compared to what the comparison operators yield in expression evaluation (NULL result instead of a boolean value). Below, T denotes a non NULL value of any QL type. NULL collates before any non NULL value (is considered smaller than T). Two NULLs have no collating order (are considered equal). The WHERE clause restricts records considered by some statements, like SELECT FROM, DELETE FROM, or UPDATE. It is an error if the expression evaluates to a non null value of non bool type. Another form of the WHERE clause is an existence predicate of a parenthesized select statement. The EXISTS form evaluates to true if the parenthesized SELECT statement produces a non empty record set. The NOT EXISTS form evaluates to true if the parenthesized SELECT statement produces an empty record set. The parenthesized SELECT statement is evaluated only once (TODO issue #159). The GROUP BY clause is used to project rows having common values into a smaller set of rows. For example Using the GROUP BY without any aggregate functions in the selected fields is in certain cases equal to using the DISTINCT modifier. The last two examples above produce the same resultsets. The optional OFFSET clause allows to ignore first N records. For example The above will produce only rows 11, 12, ... of the record set, if they exist. The value of the expression must a non negative integer, but not bigint or duration. The optional LIMIT clause allows to ignore all but first N records. For example The above will return at most the first 10 records of the record set. The value of the expression must a non negative integer, but not bigint or duration. The LIMIT and OFFSET clauses can be combined. For example Considering table t has, say 10 records, the above will produce only records 4 - 8. After returning record #8, no more result rows/records are computed. 1. The FROM clause is evaluated, producing a Cartesian product of its source record sets (tables or nested SELECT statements). 2. If present, the JOIN cluase is evaluated on the result set of the previous evaluation and the recordset specified by the JOIN clause. (... JOIN Recordset ON ...) 3. If present, the WHERE clause is evaluated on the result set of the previous evaluation. 4. If present, the GROUP BY clause is evaluated on the result set of the previous evaluation(s). 5. The SELECT field expressions are evaluated on the result set of the previous evaluation(s). 6. If present, the DISTINCT modifier is evaluated on the result set of the previous evaluation(s). 7. If present, the ORDER BY clause is evaluated on the result set of the previous evaluation(s). 8. If present, the OFFSET clause is evaluated on the result set of the previous evaluation(s). The offset expression is evaluated once for the first record produced by the previous evaluations. 9. If present, the LIMIT clause is evaluated on the result set of the previous evaluation(s). The limit expression is evaluated once for the first record produced by the previous evaluations. Truncate table statements remove all records from a table. The table must exist. For example Update statements change values of fields in rows of a table. For example Note: The SET clause is optional. If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. To allow to query for DB meta data, there exist specially named tables, some of them being virtual. Note: Virtual system tables may have fake table-wise unique but meaningless and unstable record IDs. Do not apply the built-in id() to any system table. The table __Table lists all tables in the DB. The schema is The Schema column returns the statement to (re)create table Name. This table is virtual. The table __Colum lists all columns of all tables in the DB. The schema is The Ordinal column defines the 1-based index of the column in the record. This table is virtual. The table __Colum2 lists all columns of all tables in the DB which have the constraint NOT NULL or which have a constraint expression defined or which have a default expression defined. The schema is It's possible to obtain a consolidated recordset for all properties of all DB columns using The Name column is the column name in TableName. The table __Index lists all indices in the DB. The schema is The IsUnique columns reflects if the index was created using the optional UNIQUE clause. This table is virtual. Built-in functions are predeclared. The built-in aggregate function avg returns the average of values of an expression. Avg ignores NULL values, but returns NULL if all values of a column are NULL or if avg is applied to an empty record set. The column values must be of a numeric type. The built-in function contains returns true if substr is within s. If any argument to contains is NULL the result is NULL. The built-in aggregate function count returns how many times an expression has a non NULL values or the number of rows in a record set. Note: count() returns 0 for an empty record set. For example Date returns the time corresponding to in the appropriate zone for that time in the given location. The month, day, hour, min, sec, and nsec values may be outside their usual ranges and will be normalized during the conversion. For example, October 32 converts to November 1. A daylight savings time transition skips or repeats times. For example, in the United States, March 13, 2011 2:15am never occurred, while November 6, 2011 1:15am occurred twice. In such cases, the choice of time zone, and therefore the time, is not well-defined. Date returns a time that is correct in one of the two zones involved in the transition, but it does not guarantee which. A location maps time instants to the zone in use at that time. Typically, the location represents the collection of time offsets in use in a geographical area, such as "CEST" and "CET" for central Europe. "local" represents the system's local time zone. "UTC" represents Universal Coordinated Time (UTC). The month specifies a month of the year (January = 1, ...). If any argument to date is NULL the result is NULL. The built-in function day returns the day of the month specified by t. If the argument to day is NULL the result is NULL. The built-in function formatTime returns a textual representation of the time value formatted according to layout, which defines the format by showing how the reference time, would be displayed if it were the value; it serves as an example of the desired output. The same display rules will then be applied to the time value. If any argument to formatTime is NULL the result is NULL. NOTE: The string value of the time zone, like "CET" or "ACDT", is dependent on the time zone of the machine the function is run on. For example, if the t value is in "CET", but the machine is in "ACDT", instead of "CET" the result is "+0100". This is the same what Go (time.Time).String() returns and in fact formatTime directly calls t.String(). returns on a machine in the CET time zone, but may return on a machine in the ACDT zone. The time value is in both cases the same so its ordering and comparing is correct. Only the display value can differ. The built-in functions formatFloat and formatInt format numbers to strings using go's number format functions in the `strconv` package. For all three functions, only the first argument is mandatory. The default values of the rest are shown in the examples. If the first argument is NULL, the result is NULL. returns returns returns Unlike the `strconv` equivalent, the formatInt function handles all integer types, both signed and unsigned. The built-in function hasPrefix tests whether the string s begins with prefix. If any argument to hasPrefix is NULL the result is NULL. The built-in function hasSuffix tests whether the string s ends with suffix. If any argument to hasSuffix is NULL the result is NULL. The built-in function hour returns the hour within the day specified by t, in the range [0, 23]. If the argument to hour is NULL the result is NULL. The built-in function hours returns the duration as a floating point number of hours. If the argument to hours is NULL the result is NULL. The built-in function id takes zero or one arguments. If no argument is provided, id() returns a table-unique automatically assigned numeric identifier of type int. Ids of deleted records are not reused unless the DB becomes completely empty (has no tables). For example If id() without arguments is called for a row which is not a table record then the result value is NULL. For example If id() has one argument it must be a table name of a table in a cross join. For example The built-in function len takes a string argument and returns the lentgh of the string in bytes. The expression len(s) is constant if s is a string constant. If the argument to len is NULL the result is NULL. The built-in aggregate function max returns the largest value of an expression in a record set. Max ignores NULL values, but returns NULL if all values of a column are NULL or if max is applied to an empty record set. The expression values must be of an ordered type. For example The built-in aggregate function min returns the smallest value of an expression in a record set. Min ignores NULL values, but returns NULL if all values of a column are NULL or if min is applied to an empty record set. For example The column values must be of an ordered type. The built-in function minute returns the minute offset within the hour specified by t, in the range [0, 59]. If the argument to minute is NULL the result is NULL. The built-in function minutes returns the duration as a floating point number of minutes. If the argument to minutes is NULL the result is NULL. The built-in function month returns the month of the year specified by t (January = 1, ...). If the argument to month is NULL the result is NULL. The built-in function nanosecond returns the nanosecond offset within the second specified by t, in the range [0, 999999999]. If the argument to nanosecond is NULL the result is NULL. The built-in function nanoseconds returns the duration as an integer nanosecond count. If the argument to nanoseconds is NULL the result is NULL. The built-in function now returns the current local time. The built-in function parseTime parses a formatted string and returns the time value it represents. The layout defines the format by showing how the reference time, would be interpreted if it were the value; it serves as an example of the input format. The same interpretation will then be made to the input string. Elements omitted from the value are assumed to be zero or, when zero is impossible, one, so parsing "3:04pm" returns the time corresponding to Jan 1, year 0, 15:04:00 UTC (note that because the year is 0, this time is before the zero Time). Years must be in the range 0000..9999. The day of the week is checked for syntax but it is otherwise ignored. In the absence of a time zone indicator, parseTime returns a time in UTC. When parsing a time with a zone offset like -0700, if the offset corresponds to a time zone used by the current location, then parseTime uses that location and zone in the returned time. Otherwise it records the time as being in a fabricated location with time fixed at the given zone offset. When parsing a time with a zone abbreviation like MST, if the zone abbreviation has a defined offset in the current location, then that offset is used. The zone abbreviation "UTC" is recognized as UTC regardless of location. If the zone abbreviation is unknown, Parse records the time as being in a fabricated location with the given zone abbreviation and a zero offset. This choice means that such a time can be parses and reformatted with the same layout losslessly, but the exact instant used in the representation will differ by the actual zone offset. To avoid such problems, prefer time layouts that use a numeric zone offset. If any argument to parseTime is NULL the result is NULL. The built-in function second returns the second offset within the minute specified by t, in the range [0, 59]. If the argument to second is NULL the result is NULL. The built-in function seconds returns the duration as a floating point number of seconds. If the argument to seconds is NULL the result is NULL. The built-in function since returns the time elapsed since t. It is shorthand for now()-t. If the argument to since is NULL the result is NULL. The built-in aggregate function sum returns the sum of values of an expression for all rows of a record set. Sum ignores NULL values, but returns NULL if all values of a column are NULL or if sum is applied to an empty record set. The column values must be of a numeric type. The built-in function timeIn returns t with the location information set to loc. For discussion of the loc argument please see date(). If any argument to timeIn is NULL the result is NULL. The built-in function weekday returns the day of the week specified by t. Sunday == 0, Monday == 1, ... If the argument to weekday is NULL the result is NULL. The built-in function year returns the year in which t occurs. If the argument to year is NULL the result is NULL. The built-in function yearDay returns the day of the year specified by t, in the range [1,365] for non-leap years, and [1,366] in leap years. If the argument to yearDay is NULL the result is NULL. Three functions assemble and disassemble complex numbers. The built-in function complex constructs a complex value from a floating-point real and imaginary part, while real and imag extract the real and imaginary parts of a complex value. The type of the arguments and return value correspond. For complex, the two arguments must be of the same floating-point type and the return type is the complex type with the corresponding floating-point constituents: complex64 for float32, complex128 for float64. The real and imag functions together form the inverse, so for a complex value z, z == complex(real(z), imag(z)). If the operands of these functions are all constants, the return value is a constant. If any argument to any of complex, real, imag functions is NULL the result is NULL. For the numeric types, the following sizes are guaranteed Portions of this specification page are modifications based on work[2] created and shared by Google[3] and used according to terms described in the Creative Commons 3.0 Attribution License[4]. This specification is licensed under the Creative Commons Attribution 3.0 License, and code is licensed under a BSD license[5]. Links from the above documentation This section is not part of the specification. WARNING: The implementation of indices is new and it surely needs more time to become mature. Indices are used currently used only by the WHERE clause. The following expression patterns of 'WHERE expression' are recognized and trigger index use. The relOp is one of the relation operators <, <=, ==, >=, >. For the equality operator both operands must be of comparable types. For all other operators both operands must be of ordered types. The constant expression is a compile time constant expression. Some constant folding is still a TODO. Parameter is a QL parameter ($1 etc.). Consider tables t and u, both with an indexed field f. The WHERE expression doesn't comply with the above simple detected cases. However, such query is now automatically rewritten to which will use both of the indices. The impact of using the indices can be substantial (cf. BenchmarkCrossJoin*) if the resulting rows have low "selectivity", ie. only few rows from both tables are selected by the respective WHERE filtering. Note: Existing QL DBs can be used and indices can be added to them. However, once any indices are present in the DB, the old QL versions cannot work with such DB anymore. Running a benchmark with -v (-test.v) outputs information about the scale used to report records/s and a brief description of the benchmark. For example Running the full suite of benchmarks takes a lot of time. Use the -timeout flag to avoid them being killed after the default time limit (10 minutes).
Package jsonschema provides json-schema compilation and validation. This implementation of JSON Schema, supports draft4, draft6 and draft7. Passes all tests(including optional) in https://github.com/json-schema/JSON-Schema-Test-Suite An example of using this package: The schema is compiled against the version specified in `$schema` property. If `$schema` property is missing, it uses latest draft which currently is draft7. You can force to use draft4 when `$schema` is missing, as follows: you can also validate go value using schema.ValidateInterface(interface{}) method. but the argument should not be user-defined struct. This package supports loading json-schema from filePath and fileURL. To load json-schema from HTTPURL, add following import: Loading from urls for other schemes (such as ftp), can be plugged in. see package jsonschema/httploader for an example To load json-schema from in-memory: This package supports json string formats: date-time, date, time, hostname, email, ip-address, ipv4, ipv6, uri, uriref, regex, format, json-pointer, relative-json-pointer, uri-template (limited validation). Developers can register their own formats using package "github.com/santhosh-tekuri/jsonschema/formats". "base64" contentEncoding is supported. Custom decoders can be registered using package "github.com/santhosh-tekuri/jsonschema/decoders". "application/json" contentMediaType is supported. Custom mediatypes can be registered using package "github.com/santhosh-tekuri/jsonschema/mediatypes". The ValidationError returned by Validate method contains detailed context to understand why and where the error is.
Package gosnowflake is a pure Go Snowflake driver for the database/sql package. Clients can use the database/sql package directly. For example: Use the Open() function to create a database handle with connection parameters: The Go Snowflake Driver supports the following connection syntaxes (or data source name (DSN) formats): where all parameters must be escaped or use Config and DSN to construct a DSN string. For information about account identifiers, see the Snowflake documentation (https://docs.snowflake.com/en/user-guide/admin-account-identifier.html). The following example opens a database handle with the Snowflake account named "my_account" under the organization named "my_organization", where the username is "jsmith", password is "mypassword", database is "mydb", schema is "testschema", and warehouse is "mywh": The connection string (DSN) can contain both connection parameters (described below) and session parameters (https://docs.snowflake.com/en/sql-reference/parameters.html). The following connection parameters are supported: account <string>: Specifies your Snowflake account, where "<string>" is the account identifier assigned to your account by Snowflake. For information about account identifiers, see the Snowflake documentation (https://docs.snowflake.com/en/user-guide/admin-account-identifier.html). If you are using a global URL, then append the connection group and ".global" (e.g. "<account_identifier>-<connection_group>.global"). The account identifier and the connection group are separated by a dash ("-"), as shown above. This parameter is optional if your account identifier is specified after the "@" character in the connection string. region <string>: DEPRECATED. You may specify a region, such as "eu-central-1", with this parameter. However, since this parameter is deprecated, it is best to specify the region as part of the account parameter. For details, see the description of the account parameter. database: Specifies the database to use by default in the client session (can be changed after login). schema: Specifies the database schema to use by default in the client session (can be changed after login). warehouse: Specifies the virtual warehouse to use by default for queries, loading, etc. in the client session (can be changed after login). role: Specifies the role to use by default for accessing Snowflake objects in the client session (can be changed after login). passcode: Specifies the passcode provided by Duo when using multi-factor authentication (MFA) for login. passcodeInPassword: false by default. Set to true if the MFA passcode is embedded in the login password. Appends the MFA passcode to the end of the password. loginTimeout: Specifies the timeout, in seconds, for login. The default is 60 seconds. The login request gives up after the timeout length if the HTTP response is success. requestTimeout: Specifies the timeout, in seconds, for a query to complete. 0 (zero) specifies that the driver should wait indefinitely. The default is 0 seconds. The query request gives up after the timeout length if the HTTP response is success. authenticator: Specifies the authenticator to use for authenticating user credentials: To use the internal Snowflake authenticator, specify snowflake (Default). To authenticate through Okta, specify https://<okta_account_name>.okta.com (URL prefix for Okta). To authenticate using your IDP via a browser, specify externalbrowser. To authenticate via OAuth, specify oauth and provide an OAuth Access Token (see the token parameter below). application: Identifies your application to Snowflake Support. insecureMode: false by default. Set to true to bypass the Online Certificate Status Protocol (OCSP) certificate revocation check. IMPORTANT: Change the default value for testing or emergency situations only. token: a token that can be used to authenticate. Should be used in conjunction with the "oauth" authenticator. client_session_keep_alive: Set to true have a heartbeat in the background every hour to keep the connection alive such that the connection session will never expire. Care should be taken in using this option as it opens up the access forever as long as the process is alive. ocspFailOpen: true by default. Set to false to make OCSP check fail closed mode. validateDefaultParameters: true by default. Set to false to disable checks on existence and privileges check for Database, Schema, Warehouse and Role when setting up the connection tracing: Specifies the logging level to be used. Set to error by default. Valid values are trace, debug, info, print, warning, error, fatal, panic. disableQueryContextCache: disables parsing of query context returned from server and resending it to server as well. Default value is false. clientConfigFile: specifies the location of the client configuration json file. In this file you can configure Easy Logging feature. disableSamlURLCheck: disables the SAML URL check. Default value is false. All other parameters are interpreted as session parameters (https://docs.snowflake.com/en/sql-reference/parameters.html). For example, the TIMESTAMP_OUTPUT_FORMAT session parameter can be set by adding: A complete connection string looks similar to the following: Session-level parameters can also be set by using the SQL command "ALTER SESSION" (https://docs.snowflake.com/en/sql-reference/sql/alter-session.html). Alternatively, use OpenWithConfig() function to create a database handle with the specified Config. # Connection Config You can also connect to your warehouse using the connection config. The dbSql library states that when you want to take advantage of driver-specific connection features that aren’t available in a connection string. Each driver supports its own set of connection properties, often providing ways to customize the connection request specific to the DBMS For example: If you are using this method, you dont need to pass a driver name to specify the driver type in which you are looking to connect. Since the driver name is not needed, you can optionally bypass driver registration on startup. To do this, set `GOSNOWFLAKE_SKIP_REGISTERATION` in your environment. This is useful you wish to register multiple verions of the driver. Note: GOSNOWFLAKE_SKIP_REGISTERATION should not be used if sql.Open() is used as the method to connect to the server, as sql.Open will require registration so it can map the driver name to the driver type, which in this case is "snowflake" and SnowflakeDriver{}. The Go Snowflake Driver honors the environment variables HTTP_PROXY, HTTPS_PROXY and NO_PROXY for the forward proxy setting. NO_PROXY specifies which hostname endings should be allowed to bypass the proxy server, e.g. no_proxy=.amazonaws.com means that Amazon S3 access does not need to go through the proxy. NO_PROXY does not support wildcards. Each value specified should be one of the following: The end of a hostname (or a complete hostname), for example: ".amazonaws.com" or "xy12345.snowflakecomputing.com". An IP address, for example "192.196.1.15". If more than one value is specified, values should be separated by commas, for example: By default, the driver's builtin logger is exposing logrus's FieldLogger and default at INFO level. Users can use SetLogger in driver.go to set a customized logger for gosnowflake package. In order to enable debug logging for the driver, user could use SetLogLevel("debug") in SFLogger interface as shown in demo code at cmd/logger.go. To redirect the logs SFlogger.SetOutput method could do the work. A custom query tag can be set in the context. Each query run with this context will include the custom query tag as metadata that will appear in the Query Tag column in the Query History log. For example: A specific query request ID can be set in the context and will be passed through in place of the default randomized request ID. For example: If you need query ID for your query you have to use raw connection. For queries: ``` ``` For execs: ``` ``` The result of your query can be retrieved by setting the query ID in the WithFetchResultByID context. ``` ``` From 0.5.0, a signal handling responsibility has moved to the applications. If you want to cancel a query/command by Ctrl+C, add a os.Interrupt trap in context to execute methods that can take the context parameter (e.g. QueryContext, ExecContext). See cmd/selectmany.go for the full example. The Go Snowflake Driver now supports the Arrow data format for data transfers between Snowflake and the Golang client. The Arrow data format avoids extra conversions between binary and textual representations of the data. The Arrow data format can improve performance and reduce memory consumption in clients. Snowflake continues to support the JSON data format. The data format is controlled by the session-level parameter GO_QUERY_RESULT_FORMAT. To use JSON format, execute: The valid values for the parameter are: If the user attempts to set the parameter to an invalid value, an error is returned. The parameter name and the parameter value are case-insensitive. This parameter can be set only at the session level. Usage notes: The Arrow data format reduces rounding errors in floating point numbers. You might see slightly different values for floating point numbers when using Arrow format than when using JSON format. In order to take advantage of the increased precision, you must pass in the context.Context object provided by the WithHigherPrecision function when querying. Traditionally, the rows.Scan() method returned a string when a variable of types interface was passed in. Turning on the flag ENABLE_HIGHER_PRECISION via WithHigherPrecision will return the natural, expected data type as well. For some numeric data types, the driver can retrieve larger values when using the Arrow format than when using the JSON format. For example, using Arrow format allows the full range of SQL NUMERIC(38,0) values to be retrieved, while using JSON format allows only values in the range supported by the Golang int64 data type. Users should ensure that Golang variables are declared using the appropriate data type for the full range of values contained in the column. For an example, see below. When using the Arrow format, the driver supports more Golang data types and more ways to convert SQL values to those Golang data types. The table below lists the supported Snowflake SQL data types and the corresponding Golang data types. The columns are: The SQL data type. The default Golang data type that is returned when you use snowflakeRows.Scan() to read data from Arrow data format via an interface{}. The possible Golang data types that can be returned when you use snowflakeRows.Scan() to read data from Arrow data format directly. The default Golang data type that is returned when you use snowflakeRows.Scan() to read data from JSON data format via an interface{}. (All returned values are strings.) The standard Golang data type that is returned when you use snowflakeRows.Scan() to read data from JSON data format directly. Go Data Types for Scan() =================================================================================================================== | ARROW | JSON =================================================================================================================== SQL Data Type | Default Go Data Type | Supported Go Data | Default Go Data Type | Supported Go Data | for Scan() interface{} | Types for Scan() | for Scan() interface{} | Types for Scan() =================================================================================================================== BOOLEAN | bool | string | bool ------------------------------------------------------------------------------------------------------------------- VARCHAR | string | string ------------------------------------------------------------------------------------------------------------------- DOUBLE | float32, float64 [1] , [2] | string | float32, float64 ------------------------------------------------------------------------------------------------------------------- INTEGER that | int, int8, int16, int32, int64 | string | int, int8, int16, fits in int64 | [1] , [2] | | int32, int64 ------------------------------------------------------------------------------------------------------------------- INTEGER that doesn't | int, int8, int16, int32, int64, *big.Int | string | error fit in int64 | [1] , [2] , [3] , [4] | ------------------------------------------------------------------------------------------------------------------- NUMBER(P, S) | float32, float64, *big.Float | string | float32, float64 where S > 0 | [1] , [2] , [3] , [5] | ------------------------------------------------------------------------------------------------------------------- DATE | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIME | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_LTZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_NTZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_TZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- BINARY | []byte | string | []byte ------------------------------------------------------------------------------------------------------------------- ARRAY [6] | string / array | string / array ------------------------------------------------------------------------------------------------------------------- OBJECT [6] | string / struct | string / struct ------------------------------------------------------------------------------------------------------------------- VARIANT | string | string ------------------------------------------------------------------------------------------------------------------- MAP | map | map [1] Converting from a higher precision data type to a lower precision data type via the snowflakeRows.Scan() method can lose low bits (lose precision), lose high bits (completely change the value), or result in error. [2] Attempting to convert from a higher precision data type to a lower precision data type via interface{} causes an error. [3] Higher precision data types like *big.Int and *big.Float can be accessed by querying with a context returned by WithHigherPrecision(). [4] You cannot directly Scan() into the alternative data types via snowflakeRows.Scan(), but can convert to those data types by using .Int64()/.String()/.Uint64() methods. For an example, see below. [5] You cannot directly Scan() into the alternative data types via snowflakeRows.Scan(), but can convert to those data types by using .Float32()/.String()/.Float64() methods. For an example, see below. [6] Arrays and objects can be either semistructured or structured, see more info in section below. Note: SQL NULL values are converted to Golang nil values, and vice-versa. ## Semistructured and structured types Snowflake supports two flavours of "structured data" - semistructured and structured. Semistructured types are variants, objects and arrays without schema. When data is fetched, it's represented as strings and the client is responsible for its interpretation. Example table definition: The data not have any corresponding schema, so values in table may be slightly different. ### Semistructured types Semistuctured variants, objects and arrays are always represented as strings for scanning: When inserting, a marker indicating correct type must be used, for example: ### Structured types Structured types differentiate from semistructured types by having specific schema. In all rows of the table, values must conform to this schema. Example table definition: #### Retrieving structured objects 1. Create a struct, example: 2. Implement sql.Scanner interface: 3. Use it in regular scan: See StructuredObject for all available operations including null support, embedding nested structs, etc. #### Retrieving structured arrays Retrieving array of simple types works exactly the same like normal values - using Scan function. If you want to scan array of structs, you have to use a helper function ScanArrayOfScanners: #### Retrieving structured maps ## Using higher precision numbers The following example shows how to retrieve very large values using the math/big package. This example retrieves a large INTEGER value to an interface and then extracts a big.Int value from that interface. If the value fits into an int64, then the code also copies the value to a variable of type int64. Note that a context that enables higher precision must be passed in with the query. If the variable named "rows" is known to contain a big.Int, then you can use the following instead of scanning into an interface and then converting to a big.Int: If the variable named "rows" contains a big.Int, then each of the following fails: Similar code and rules also apply to big.Float values. If you are not sure what data type will be returned, you can use code similar to the following to check the data type of the returned value: ## Arrow batches You can retrieve data in a columnar format similar to the format a server returns. You must use `WithArrowBatches` context, similar to the following: Limitations: 1. For some queries Snowflake may decide to return data in JSON format (examples: `SHOW PARAMETERS` or `ls @stage`). You cannot use JSON with Arrow batches context. 2. Snowflake handles timestamps in a range which is higher than available space in Arrow timestamp type. Because of that special treatment should be used (see below). ### Handling timestamps in Arrow batches Snowflake returns timestamps natively (from backend to driver) in multiple formats. The Arrow timestamp is an 8-byte data type, which is insufficient to handle the larger date and time ranges used by Snowflake. Also, Snowflake supports 0-9 (nanosecond) digit precision for seconds, while Arrow supports only 3 (millisecond), 6 (microsecond), an 9 (nanosecond) precision. Consequently, Snowflake uses a custom timestamp format in Arrow, which differs on timestamp type and precision. If you want to use timestamps in Arrow batches, you have two options: ### Invalid UTF-8 characters in Arrow batches Snowflake previously allowed users to upload data with invalid UTF-8 characters. Consequently, Arrow records containing string columns in Snowflake could include these invalid UTF-8 characters. However, according to the Arrow specifications (https://arrow.apache.org/docs/cpp/api/datatype.html and https://github.com/apache/arrow/blob/a03d957b5b8d0425f9d5b6c98b6ee1efa56a1248/go/arrow/datatype.go#L73-L74), Arrow string columns should only contain UTF-8 characters. To address this issue and prevent potential downstream disruptions, the context `enableArrowBatchesUtf8Validation`, is introduced. When enabled, this feature iterates through all values in string columns, identifying and replacing any invalid characters with `�`. This ensures that Arrow records conform to the UTF-8 standards, preventing validation failures in downstream services like the Rust Arrow library that impose strict validation checks. ### WithHigherPrecision in Arrow batches To preserve BigDecimal values within Arrow batches, use `WithHigherPrecision`. This offers two main benefits: it helps avoid precision loss and defers the conversion to upstream services. Alternatively, without this setting, all non-zero scale numbers will be converted to float64, potentially resulting in loss of precision. Zero-scale numbers (DECIMAL256, DECIMAL128) will be converted to int64, which could lead to overflow. Binding allows a SQL statement to use a value that is stored in a Golang variable. Without binding, a SQL statement specifies values by specifying literals inside the statement. For example, the following statement uses the literal value “42“ in an UPDATE statement: With binding, you can execute a SQL statement that uses a value that is inside a variable. For example: The “?“ inside the “VALUES“ clause specifies that the SQL statement uses the value from a variable. Binding data that involves time zones can require special handling. For details, see the section titled "Timestamps with Time Zones". Version 1.6.23 (and later) of the driver takes advantage of sql.Null types which enables the proper handling of null parameters inside function calls, i.e.: The timestamp nullability had to be achieved by wrapping the sql.NullTime type as the Snowflake provides several date and time types which are mapped to single Go time.Time type: Version 1.3.9 (and later) of the Go Snowflake Driver supports the ability to bind an array variable to a parameter in a SQL INSERT statement. You can use this technique to insert multiple rows in a single batch. As an example, the following code inserts rows into a table that contains integer, float, boolean, and string columns. The example binds arrays to the parameters in the INSERT statement. If the array contains SQL NULL values, use slice []interface{}, which allows Golang nil values. This feature is available in version 1.6.12 (and later) of the driver. For example, For slices []interface{} containing time.Time values, a binding parameter flag is required for the preceding array variable in the Array() function. This feature is available in version 1.6.13 (and later) of the driver. For example, Note: For alternative ways to load data into the Snowflake database (including bulk loading using the COPY command), see Loading Data into Snowflake (https://docs.snowflake.com/en/user-guide-data-load.html). When you use array binding to insert a large number of values, the driver can improve performance by streaming the data (without creating files on the local machine) to a temporary stage for ingestion. The driver automatically does this when the number of values exceeds a threshold (no changes are needed to user code). In order for the driver to send the data to a temporary stage, the user must have the following privilege on the schema: If the user does not have this privilege, the driver falls back to sending the data with the query to the Snowflake database. In addition, the current database and schema for the session must be set. If these are not set, the CREATE TEMPORARY STAGE command executed by the driver can fail with the following error: For alternative ways to load data into the Snowflake database (including bulk loading using the COPY command), see Loading Data into Snowflake (https://docs.snowflake.com/en/user-guide-data-load.html). Go's database/sql package supports the ability to bind a parameter in a SQL statement to a time.Time variable. However, when the client binds data to send to the server, the driver cannot determine the correct Snowflake date/timestamp data type to associate with the binding parameter. For example: To resolve this issue, a binding parameter flag is introduced that associates any subsequent time.Time type to the DATE, TIME, TIMESTAMP_LTZ, TIMESTAMP_NTZ or BINARY data type. The above example could be rewritten as follows: The driver fetches TIMESTAMP_TZ (timestamp with time zone) data using the offset-based Location types, which represent a collection of time offsets in use in a geographical area, such as CET (Central European Time) or UTC (Coordinated Universal Time). The offset-based Location data is generated and cached when a Go Snowflake Driver application starts, and if the given offset is not in the cache, it is generated dynamically. Currently, Snowflake does not support the name-based Location types (e.g. "America/Los_Angeles"). For more information about Location types, see the Go documentation for https://golang.org/pkg/time/#Location. Internally, this feature leverages the []byte data type. As a result, BINARY data cannot be bound without the binding parameter flag. In the following example, sf is an alias for the gosnowflake package: The driver directly downloads a result set from the cloud storage if the size is large. It is required to shift workloads from the Snowflake database to the clients for scale. The download takes place by goroutine named "Chunk Downloader" asynchronously so that the driver can fetch the next result set while the application can consume the current result set. The application may change the number of result set chunk downloader if required. Note this does not help reduce memory footprint by itself. Consider Custom JSON Decoder. Custom JSON Decoder for Parsing Result Set (Experimental) The application may have the driver use a custom JSON decoder that incrementally parses the result set as follows. This option will reduce the memory footprint to half or even quarter, but it can significantly degrade the performance depending on the environment. The test cases running on Travis Ubuntu box show five times less memory footprint while four times slower. Be cautious when using the option. The Go Snowflake Driver supports JWT (JSON Web Token) authentication. To enable this feature, construct the DSN with fields "authenticator=SNOWFLAKE_JWT&privateKey=<your_private_key>", or using a Config structure specifying: The <your_private_key> should be a base64 URL encoded PKCS8 rsa private key string. One way to encode a byte slice to URL base 64 URL format is through the base64.URLEncoding.EncodeToString() function. On the server side, you can alter the public key with the SQL command: The <your_public_key> should be a base64 Standard encoded PKI public key string. One way to encode a byte slice to base 64 Standard format is through the base64.StdEncoding.EncodeToString() function. To generate the valid key pair, you can execute the following commands in the shell: Note: As of February 2020, Golang's official library does not support passcode-encrypted PKCS8 private key. For security purposes, Snowflake highly recommends that you store the passcode-encrypted private key on the disk and decrypt the key in your application using a library you trust. JWT tokens are recreated on each retry and they are valid (`exp` claim) for `jwtTimeout` seconds. Each retry timeout is configured by `jwtClientTimeout`. Retries are limited by total time of `loginTimeout`. The driver allows to authenticate using the external browser. When a connection is created, the driver will open the browser window and ask the user to sign in. To enable this feature, construct the DSN with field "authenticator=EXTERNALBROWSER" or using a Config structure with following Authenticator specified: The external browser authentication implements timeout mechanism. This prevents the driver from hanging interminably when browser window was closed, or not responding. Timeout defaults to 120s and can be changed through setting DSN field "externalBrowserTimeout=240" (time in seconds) or using a Config structure with following ExternalBrowserTimeout specified: This feature is available in version 1.3.8 or later of the driver. By default, Snowflake returns an error for queries issued with multiple statements. This restriction helps protect against SQL Injection attacks (https://en.wikipedia.org/wiki/SQL_injection). The multi-statement feature allows users skip this restriction and execute multiple SQL statements through a single Golang function call. However, this opens up the possibility for SQL injection, so it should be used carefully. The risk can be reduced by specifying the exact number of statements to be executed, which makes it more difficult to inject a statement by appending it. More details are below. The Go Snowflake Driver provides two functions that can execute multiple SQL statements in a single call: To compose a multi-statement query, simply create a string that contains all the queries, separated by semicolons, in the order in which the statements should be executed. To protect against SQL Injection attacks while using the multi-statement feature, pass a Context that specifies the number of statements in the string. For example: When multiple queries are executed by a single call to QueryContext(), multiple result sets are returned. After you process the first result set, get the next result set (for the next SQL statement) by calling NextResultSet(). The following pseudo-code shows how to process multiple result sets: The function db.ExecContext() returns a single result, which is the sum of the number of rows changed by each individual statement. For example, if your multi-statement query executed two UPDATE statements, each of which updated 10 rows, then the result returned would be 20. Individual row counts for individual statements are not available. The following code shows how to retrieve the result of a multi-statement query executed through db.ExecContext(): Note: Because a multi-statement ExecContext() returns a single value, you cannot detect offsetting errors. For example, suppose you expected the return value to be 20 because you expected each UPDATE statement to update 10 rows. If one UPDATE statement updated 15 rows and the other UPDATE statement updated only 5 rows, the total would still be 20. You would see no indication that the UPDATES had not functioned as expected. The ExecContext() function does not return an error if passed a query (e.g. a SELECT statement). However, it still returns only a single value, not a result set, so using it to execute queries (or a mix of queries and non-query statements) is impractical. The QueryContext() function does not return an error if passed non-query statements (e.g. DML). The function returns a result set for each statement, whether or not the statement is a query. For each non-query statement, the result set contains a single row that contains a single column; the value is the number of rows changed by the statement. If you want to execute a mix of query and non-query statements (e.g. a mix of SELECT and DML statements) in a multi-statement query, use QueryContext(). You can retrieve the result sets for the queries, and you can retrieve or ignore the row counts for the non-query statements. Note: PUT statements are not supported for multi-statement queries. If a SQL statement passed to ExecQuery() or QueryContext() fails to compile or execute, that statement is aborted, and subsequent statements are not executed. Any statements prior to the aborted statement are unaffected. For example, if the statements below are run as one multi-statement query, the multi-statement query fails on the third statement, and an exception is thrown. If you then query the contents of the table named "test", the values 1 and 2 would be present. When using the QueryContext() and ExecContext() functions, golang code can check for errors the usual way. For example: Preparing statements and using bind variables are also not supported for multi-statement queries. The Go Snowflake Driver supports asynchronous execution of SQL statements. Asynchronous execution allows you to start executing a statement and then retrieve the result later without being blocked while waiting. While waiting for the result of a SQL statement, you can perform other tasks, including executing other SQL statements. Most of the steps to execute an asynchronous query are the same as the steps to execute a synchronous query. However, there is an additional step, which is that you must call the WithAsyncMode() function to update your Context object to specify that asynchronous mode is enabled. In the code below, the call to "WithAsyncMode()" is specific to asynchronous mode. The rest of the code is compatible with both asynchronous mode and synchronous mode. The function db.QueryContext() returns an object of type snowflakeRows regardless of whether the query is synchronous or asynchronous. However: The call to the Next() function of snowflakeRows is always synchronous (i.e. blocking). If the query has not yet completed and the snowflakeRows object (named "rows" in this example) has not been filled in yet, then rows.Next() waits until the result set has been filled in. More generally, calls to any Golang SQL API function implemented in snowflakeRows or snowflakeResult are blocking calls, and wait if results are not yet available. (Examples of other synchronous calls include: snowflakeRows.Err(), snowflakeRows.Columns(), snowflakeRows.columnTypes(), snowflakeRows.Scan(), and snowflakeResult.RowsAffected().) Because the example code above executes only one query and no other activity, there is no significant difference in behavior between asynchronous and synchronous behavior. The differences become significant if, for example, you want to perform some other activity after the query starts and before it completes. The example code below starts a query, which run in the background, and then retrieves the results later. This example uses small SELECT statements that do not retrieve enough data to require asynchronous handling. However, the technique works for larger data sets, and for situations where the programmer might want to do other work after starting the queries and before retrieving the results. For a more elaborative example please see cmd/async/async.go The Go Snowflake Driver supports the PUT and GET commands. The PUT command copies a file from a local computer (the computer where the Golang client is running) to a stage on the cloud platform. The GET command copies data files from a stage on the cloud platform to a local computer. See the following for information on the syntax and supported parameters: ## Using PUT The following example shows how to run a PUT command by passing a string to the db.Query() function: "<local_file>" should include the file path as well as the name. Snowflake recommends using an absolute path rather than a relative path. For example: Different client platforms (e.g. linux, Windows) have different path name conventions. Ensure that you specify path names appropriately. This is particularly important on Windows, which uses the backslash character as both an escape character and as a separator in path names. To send information from a stream (rather than a file) use code similar to the code below. (The ReplaceAll() function is needed on Windows to handle backslashes in the path to the file.) Note: PUT statements are not supported for multi-statement queries. ## Using GET The following example shows how to run a GET command by passing a string to the db.Query() function: "<local_file>" should include the file path as well as the name. Snowflake recommends using an absolute path rather than a relative path. For example: ## Specifying temporary directory for encryption and compression Putting and getting requires compression and/or encryption, which is done in the OS temporary directory. If you cannot use default temporary directory for your OS or you want to specify it yourself, you can use "tmpDirPath" DSN parameter. Remember, to encode slashes. Example: ## Using custom configuration for PUT/GET If you want to override some default configuration options, you can use `WithFileTransferOptions` context. There are multiple config parameters including progress bars or compression.
Package budgets provides the API client, operations, and parameter types for AWS Budgets. Use the Amazon Web Services Budgets API to plan your service usage, service costs, and instance reservations. This API reference provides descriptions, syntax, and usage examples for each of the actions and data types for the Amazon Web Services Budgets feature. Budgets provide you with a way to see the following information: How close your plan is to your budgeted amount or to the free tier limits Your usage-to-date, including how much you've used of your Reserved Instances (RIs) Your current estimated charges from Amazon Web Services, and how much your predicted usage will accrue in charges by the end of the month How much of your budget has been used Amazon Web Services updates your budget status several times a day. Budgets track your unblended costs, subscriptions, refunds, and RIs. You can create the following types of budgets: Cost budgets - Plan how much you want to spend on a service. Usage budgets - Plan how much you want to use one or more services. RI utilization budgets - Define a utilization threshold, and receive alerts when your RI usage falls below that threshold. This lets you see if your RIs are unused or under-utilized. RI coverage budgets - Define a coverage threshold, and receive alerts when the number of your instance hours that are covered by RIs fall below that threshold. This lets you see how much of your instance usage is covered by a reservation. The Amazon Web Services Budgets API provides the following endpoint: For information about costs that are associated with the Amazon Web Services Budgets API, see Amazon Web Services Cost Management Pricing.
Package cleanup provides a unified way to defer running functions until a later date. Cleanup provides a way for tooling to defer running functions until a later date. A typical example would be wanting to defer running a shutdown function until main() exits: cleanup.Add(shutdown)
Package fallback embeds a set of fallback X.509 trusted roots in the application by automatically invoking x509.SetFallbackRoots. This allows the application to work correctly even if the operating system does not provide a verifier or system roots pool. To use it, import the package like It's recommended that only binaries, and not libraries, import this package. This package must be kept up to date for security and compatibility reasons. Use govulncheck to be notified of when new versions of the package are available.
Package jsonschema provides json-schema compilation and validation. This implementation of JSON Schema, supports draft4, draft6 and draft7. Passes all tests(including optional) in https://github.com/json-schema/JSON-Schema-Test-Suite An example of using this package: The schema is compiled against the version specified in `$schema` property. If `$schema` property is missing, it uses latest draft which currently is draft7. You can force to use draft4 when `$schema` is missing, as follows: you can also validate go value using schema.ValidateInterface(interface{}) method. but the argument should not be user-defined struct. This package supports loading json-schema from filePath and fileURL. To load json-schema from HTTPURL, add following import: Loading from urls for other schemes (such as ftp), can be plugged in. see package jsonschema/httploader for an example To load json-schema from in-memory: This package supports json string formats: date-time, date, time, hostname, email, ip-address, ipv4, ipv6, uri, uriref, regex, format, json-pointer, relative-json-pointer, uri-template (limited validation). Developers can register their own formats by adding them to jsonschema.Formats map. "base64" contentEncoding is supported. Custom decoders can be registered by adding them to jsonschema.Decoders map. "application/json" contentMediaType is supported. Custom mediatypes can be registered by adding them to jsonschema.MediaTypes map. The ValidationError returned by Validate method contains detailed context to understand why and where the error is. Custom Extensions can be registered as shown in extension_test.go
Package libvirt provides a Go binding to the libvirt C library Through conditional compilation it supports libvirt versions 1.2.0 onwards. This is done automatically, with no requirement to use magic Go build tags. If an API was not available in the particular version of libvirt this package was built against, an error will be returned with a code of ERR_NO_SUPPORT. This is the same code seen if using a new libvirt library to talk to an old libvirtd lacking the API, or if a hypervisor does not support a given feature, so an application can easily handle all scenarios together. The Go binding is a fairly direct mapping of the underling C API which seeks to maximise the use of the Go type system to allow strong compiler type checking. The following rules describe how APIs/constants are mapped from C to Go For structs, the 'vir' prefix and 'Ptr' suffix are removed from the name. e.g. virConnectPtr in C becomes 'Connect' in Go. For structs which are reference counted at the C level, it is neccessary to explicitly release the reference at the Go level. e.g. if a Go method returns a '* Domain' struct, it is neccessary to call 'Free' on this when no longer required. The use of 'defer' is recommended for this purpose If multiple goroutines are using the same libvirt object struct, it may not be possible to determine which goroutine should call 'Free'. In such scenarios each new goroutine should call 'Ref' to obtain a private reference on the underlying C struct. All goroutines can call 'Free' unconditionally with the final one causing the release of the C object. For methods, the 'vir' prefix and object name prefix are remove from the name. The C functions become methods with an object receiver. e.g. 'virDomainScreenshot' in C becomes 'Screenshot' with a 'Domain *' receiver. For methods which accept a 'unsigned int flags' parameter in the C level, the corresponding Go parameter will be a named type corresponding to the C enum that defines the valid flags. For example, the ListAllDomains method takes a 'flags ConnectListAllDomainsFlags' parameter. If there are not currently any flags defined for a method in the C API, then the Go method parameter will be declared as a "flags uint32". Callers should always pass the literal integer value 0 for such parameters, without forcing any specific type. This will allow compatibility with future updates to the libvirt-go binding which may replace the 'uint32' type with a enum type at a later date. For enums, the VIR_ prefix is removed from the name. The enums get a dedicated type defined in Go. e.g. the VIR_NODE_SUSPEND_TARGET_MEM enum constant in C, becomes NODE_SUSPEND_TARGET_MEM with a type of NodeSuspendTarget. Methods accepting or returning virTypedParameter arrays in C will map the parameters into a Go struct. The struct will contain two fields for each possible parameter. One boolean field with a suffix of 'Set' indicates whether the parameter has a value set, and the other custom typed field provides the parameter value. This makes it possible to distinguish a parameter with a default value of '0' from a parameter which is 0 because it isn't supported by the hypervisor. If the C API defines additional typed parameters, then the corresponding Go struct will be extended to have further fields. e.g. the GetMemoryStats method in Go (which is backed by virNodeGetMemoryStats in C) will return a NodeMemoryStats struct containing the typed parameter values. Every method that can fail will include an 'error' object as the last return value. This will be an instance of the Error struct if an error occurred. To check for specific libvirt error codes, it is neccessary to cast the error. To connect to libvirt
Package config is an encoding-agnostic configuration abstraction. It supports merging multiple configuration files, expanding environment variables, and a variety of other small niceties. It currently supports YAML, but may be extended in the future to support more restrictive encodings like JSON or TOML. It's often convenient to separate configuration into multiple files; for example, an application may want to first load some universally-applicable configuration and then merge in some environment-specific overrides. This package supports this pattern in a variety of ways, all of which use the same merge logic. Simple types (numbers, strings, dates, and anything else YAML would consider a scalar) are merged by replacing lower-priority values with higher-priority overrides. For example, consider this merge of base.yaml and override.yaml: Slices, arrays, and anything else YAML would consider a sequence are also replaced. Again merging base.yaml and override.yaml: Maps are recursively deep-merged, handling scalars and sequences as described above. Consider a merge between a more complex set of YAML files: In all cases, explicit nils (represented in YAML with a tilde) override any pre-existing configuration. For example, By default, the NewYAML constructor enables gopkg.in/yaml.v2's strict unmarshalling mode. This prevents a variety of common programmer errors, especially when deep-merging loosely-typed YAML files. In strict mode, providers throw errors if keys are duplicated in the same configuration source, all keys aren't used when populating a struct, or a merge encounters incompatible data types. This behavior can be disabled with the Permissive option. To maintain backward compatibility, all other constructors default to permissive unmarshalling. YAML allows strings to appear quoted or unquoted, so these two lines are identical: However, the YAML specification special-cases some unquoted strings. Most obviously, true and false are interpreted as Booleans (unless quoted). Less obviously, yes, no, on, off, and many variants of these words are also treated as Booleans (see http://yaml.org/type/bool.html for the complete specification). Correctly deep-merging sources requires this package to unmarshal and then remarshal all YAML, which implicitly converts these special-cased unquoted strings to their canonical representation. For example, Quoting special-cased strings prevents this surprising behavior. Unfortunately, this package was released with a variety of bugs and an overly large API. The internals of the configuration provider have been completely reworked and all known bugs have been addressed, but many duplicative exported functions were retained to preserve backward compatibility. New users should rely on the NewYAML constructor. In particular, avoid NewValue - it's unnecessary, complex, and may panic. Deprecated functions are documented in the format expected by the staticcheck linter, available at https://staticcheck.io/.
Package pgx is a PostgreSQL database driver. pgx provides lower level access to PostgreSQL than the standard database/sql It remains as similar to the database/sql interface as possible while providing better speed and access to PostgreSQL specific features. Import github.com/jack/pgx/stdlib to use pgx as a database/sql compatible driver. pgx implements Query and Scan in the familiar database/sql style. pgx also implements QueryRow in the same style as database/sql. Use Exec to execute a query that does not return a result set. Connection pool usage is explicit and configurable. In pgx, a connection can be created and managed directly, or a connection pool with a configurable maximum connections can be used. Also, the connection pool offers an after connect hook that allows every connection to be automatically setup before being made available in the connection pool. This is especially useful to ensure all connections have the same prepared statements available or to change any other connection settings. It delegates Query, QueryRow, Exec, and Begin functions to an automatically checked out and released connection so you can avoid manually acquiring and releasing connections when you do not need that level of control. pgx maps between all common base types directly between Go and PostgreSQL. In particular: pgx can map nulls in two ways. The first is Null* types that have a data field and a valid field. They work in a similar fashion to database/sql. The second is to use a pointer to a pointer. pgx maps between int16, int32, int64, float32, float64, and string Go slices and the equivalent PostgreSQL array type. Go slices of native types do not support nulls, so if a PostgreSQL array that contains a null is read into a native Go slice an error will occur. pgx includes an Hstore type and a NullHstore type. Hstore is simply a map[string]string and is preferred when the hstore contains no nulls. NullHstore follows the Null* pattern and supports null values. pgx includes built-in support to marshal and unmarshal between Go types and the PostgreSQL JSON and JSONB. pgx encodes from net.IPNet to and from inet and cidr PostgreSQL types. In addition, as a convenience pgx will encode from a net.IP; it will assume a /32 netmask for IPv4 and a /128 for IPv6. pgx includes support for the common data types like integers, floats, strings, dates, and times that have direct mappings between Go and SQL. Support can be added for additional types like point, hstore, numeric, etc. that do not have direct mappings in Go by the types implementing ScannerPgx and Encoder. Custom types can support text or binary formats. Binary format can provide a large performance increase. The natural place for deciding the format for a value would be in ScannerPgx as it is responsible for decoding the returned data. However, that is impossible as the query has already been sent by the time the ScannerPgx is invoked. The solution to this is the global DefaultTypeFormats. If a custom type prefers binary format it should register it there. Note that the type is referred to by name, not by OID. This is because custom PostgreSQL types like hstore will have different OIDs on different servers. When pgx establishes a connection it queries the pg_type table for all types. It then matches the names in DefaultTypeFormats with the returned OIDs and stores it in Conn.PgTypes. See example_custom_type_test.go for an example of a custom type for the PostgreSQL point type. pgx also includes support for custom types implementing the database/sql.Scanner and database/sql/driver.Valuer interfaces. []byte passed as arguments to Query, QueryRow, and Exec are passed unmodified to PostgreSQL. In like manner, a *[]byte passed to Scan will be filled with the raw bytes returned by PostgreSQL. This can be especially useful for reading varchar, text, json, and jsonb values directly into a []byte and avoiding the type conversion from string. Transactions are started by calling Begin or BeginIso. The BeginIso variant creates a transaction with a specified isolation level. Use CopyFrom to efficiently insert multiple rows at a time using the PostgreSQL copy protocol. CopyFrom accepts a CopyFromSource interface. If the data is already in a [][]interface{} use CopyFromRows to wrap it in a CopyFromSource interface. Or implement CopyFromSource to avoid buffering the entire data set in memory. CopyFrom can be faster than an insert with as few as 5 rows. pgx can listen to the PostgreSQL notification system with the WaitForNotification function. It takes a maximum time to wait for a notification. The pgx ConnConfig struct has a TLSConfig field. If this field is nil, then TLS will be disabled. If it is present, then it will be used to configure the TLS connection. This allows total configuration of the TLS connection. pgx defines a simple logger interface. Connections optionally accept a logger that satisfies this interface. The log15 package (http://gopkg.in/inconshreveable/log15.v2) satisfies this interface and it is simple to define adapters for other loggers. Set LogLevel to control logging verbosity.
Package redisc implements a redis cluster client on top of the redigo client package. It supports all commands that can be executed on a redis cluster, including pub-sub, scripts and read-only connections to read data from replicas. See http://redis.io/topics/cluster-spec for details. The package defines two main types: Cluster and Conn. Both are described in more details below, but the Cluster manages the mapping of keys (or more exactly, hash slots computed from keys) to a group of nodes that form a redis cluster, and a Conn manages a connection to this cluster. The package is designed such that for simple uses, or when keys have been carefully named to play well with a redis cluster, a Cluster value can be used as a drop-in replacement for a redis.Pool from the redigo package. Similarly, the Conn type implements redigo's redis.Conn interface (and the augmented redis.ConnWithTimeout one too), so the API to execute commands is the same - in fact the redisc package uses the redigo package as its only third-party dependency. When more control is needed, the package offers some extra behaviour specific to working with a redis cluster: Slot and SplitBySlot functions to compute the slot for a given key and to split a list of keys into groups of keys from the same slot, so that each group can safely be handled using the same connection. *Conn.Bind (or the BindConn package-level helper function) to explicitly specify the keys that will be used with the connection so that the right node is selected, instead of relying on the automatic detection based on the first parameter of the command. *Conn.ReadOnly (or the ReadOnlyConn package-level helper function) to mark a connection as read-only, allowing commands to be served by a replica instead of the master. RetryConn to wrap a connection into one that automatically follows redirections when the cluster moves slots around. Helper functions to deal with cluster-specific errors. The Cluster type manages a redis cluster and offers an interface compatible with redigo's redis.Pool: Along with some additional methods specific to a cluster: If the CreatePool function field is set, then a redis.Pool is created to manage connections to each of the cluster's nodes. A call to Get returns a connection from that pool. The Dial method, on the other hand, guarantees that the returned connection will not be managed by a pool, even if CreatePool is set. It calls redigo's redis.Dial function to create the unpooled connection, passing along any DialOptions set on the cluster. If the cluster's CreatePool field is nil, Get behaves the same as Dial. The Refresh method refreshes the cluster's internal mapping of hash slots to nodes. It should typically be called only once, after the cluster is created and before it is used, so that the first connections already benefit from smart routing. It is automatically kept up-to-date based on the redis MOVED responses afterwards. The EachNode method visits each node in the cluster and calls the provided function with a connection to that node, which may be useful to run diagnostics commands on each node or to collect keys across the whole cluster. The Stats method returns the pool statistics for each node, with the node's address as key of the map. A cluster must be closed once it is no longer used to release its resources. The connection returned from Get or Dial is a redigo redis.Conn interface (that also implements redis.ConnWithTimeout), with a concrete type of *Conn. In addition to the interface's required methods, *Conn adds the following methods: The returned connection is not yet connected to any node; it is "bound" to a specific node only when a call to Do, Send, Receive or Bind is made. For Do, Send and Receive, the node selection is implicit, it uses the first parameter of the command, and computes the hash slot assuming that first parameter is a key. It then binds the connection to the node corresponding to that slot. If there are no parameters for the command, or if there is no command (e.g. in a call to Receive), a random node is selected. Bind is explicit, it gives control to the caller over which node to select by specifying a list of keys that the caller wishes to handle with the connection. All keys must belong to the same slot, and the connection must not already be bound to a node, otherwise an error is returned. On success, the connection is bound to the node holding the slot of the specified key(s). Because the connection is returned as a redis.Conn interface, a type assertion must be used to access the underlying *Conn and to be able to call Bind: The BindConn package-level function is provided as a helper for this common use-case. The ReadOnly method marks the connection as read-only, meaning that it will attempt to connect to a replica instead of the master node for its slot. Once bound to a node, the READONLY redis command is sent automatically, so it doesn't have to be sent explicitly before use. ReadOnly must be called before the connection is bound to a node, otherwise an error is returned. For the same reason as for Bind, a type assertion must be used to call ReadOnly on a *Conn, so a package-level helper function is also provided, ReadOnlyConn. There is no ReadWrite method, because it can be sent as a normal redis command and will essentially end that connection (all commands will now return MOVED errors). If the connection was wrapped in a RetryConn call, then it will automatically follow the redirection to the master node (see the Redirections section). The connection must be closed after use, to release the underlying resources. The redis cluster may return MOVED and ASK errors when the node that received the command doesn't currently hold the slot corresponding to the key. The package cannot reliably handle those redirections automatically because the redirection error may be returned for a pipeline of commands, some of which may have succeeded. However, a connection can be wrapped by a call to RetryConn, which returns a redis.Conn interface where only calls to Do, Close and Err can succeed. That means pipelining is not supported, and only a single command can be executed at a time, but it will automatically handle MOVED and ASK replies, as well as TRYAGAIN errors. Note that even if RetryConn is not used, the cluster always updates its mapping of slots to nodes automatically by keeping track of MOVED replies. The concurrency model is similar to that of the redigo package: Cluster methods are safe to call concurrently (like redis.Pool). Connections do not support concurrent calls to write methods (Send, Flush) or concurrent calls to the read method (Receive). Connections do allow a concurrent reader and writer. Because the Do method combines the functionality of Send, Flush and Receive, it cannot be called concurrently with other methods. The Bind and ReadOnly methods are safe to call concurrently, but there is not much point in doing so for as both will fail if the connection is already bound. Create and use a cluster.
Package imagebuilder provides the API client, operations, and parameter types for EC2 Image Builder. EC2 Image Builder is a fully managed Amazon Web Services service that makes it easier to automate the creation, management, and deployment of customized, secure, and up-to-date "golden" server images that are pre-installed and pre-configured with software and settings to meet specific IT standards.
Package httpdate provides functions that deal the date formats used by the HTTP protocol (and then some more). Only the two functions, Time2Str() and Str2Time(), are provided. Str2Time() is tremendous function which automatically detect various date format and returns `time.Time`. Is is golang porting of perl's HTTP::Date - https://metacpan.org/pod/HTTP::Date
Package validator implements value validations for structs and individual fields based on tags. It can also handle Cross-Field and Cross-Struct validation for nested structs and has the ability to dive into arrays and maps of any type. see more examples https://github.com/go-playground/validator/tree/v9/_examples Doing things this way is actually the way the standard library does, see the file.Open method here: The authors return type "error" to avoid the issue discussed in the following, where err is always != nil: Validator only InvalidValidationError for bad validation input, nil or ValidationErrors as type error; so, in your code all you need to do is check if the error returned is not nil, and if it's not check if error is InvalidValidationError ( if necessary, most of the time it isn't ) type cast it to type ValidationErrors like so err.(validator.ValidationErrors). Custom Validation functions can be added. Example: Cross-Field Validation can be done via the following tags: If, however, some custom cross-field validation is required, it can be done using a custom validation. Why not just have cross-fields validation tags (i.e. only eqcsfield and not eqfield)? The reason is efficiency. If you want to check a field within the same struct "eqfield" only has to find the field on the same struct (1 level). But, if we used "eqcsfield" it could be multiple levels down. Example: Multiple validators on a field will process in the order defined. Example: Bad Validator definitions are not handled by the library. Example: Baked In Cross-Field validation only compares fields on the same struct. If Cross-Field + Cross-Struct validation is needed you should implement your own custom validator. Comma (",") is the default separator of validation tags. If you wish to have a comma included within the parameter (i.e. excludesall=,) you will need to use the UTF-8 hex representation 0x2C, which is replaced in the code as a comma, so the above will become excludesall=0x2C. Pipe ("|") is the 'or' validation tags deparator. If you wish to have a pipe included within the parameter i.e. excludesall=| you will need to use the UTF-8 hex representation 0x7C, which is replaced in the code as a pipe, so the above will become excludesall=0x7C Here is a list of the current built in validators: Tells the validation to skip this struct field; this is particularly handy in ignoring embedded structs from being validated. (Usage: -) This is the 'or' operator allowing multiple validators to be used and accepted. (Usage: rbg|rgba) <-- this would allow either rgb or rgba colors to be accepted. This can also be combined with 'and' for example ( Usage: omitempty,rgb|rgba) When a field that is a nested struct is encountered, and contains this flag any validation on the nested struct will be run, but none of the nested struct fields will be validated. This is useful if inside of your program you know the struct will be valid, but need to verify it has been assigned. NOTE: only "required" and "omitempty" can be used on a struct itself. Same as structonly tag except that any struct level validations will not run. Allows conditional validation, for example if a field is not set with a value (Determined by the "required" validator) then other validation such as min or max won't run, but if a value is set validation will run. This tells the validator to dive into a slice, array or map and validate that level of the slice, array or map with the validation tags that follow. Multidimensional nesting is also supported, each level you wish to dive will require another dive tag. dive has some sub-tags, 'keys' & 'endkeys', please see the Keys & EndKeys section just below. Example #1 Example #2 Keys & EndKeys These are to be used together directly after the dive tag and tells the validator that anything between 'keys' and 'endkeys' applies to the keys of a map and not the values; think of it like the 'dive' tag, but for map keys instead of values. Multidimensional nesting is also supported, each level you wish to validate will require another 'keys' and 'endkeys' tag. These tags are only valid for maps. Example #1 Example #2 This validates that the value is not the data types default zero value. For numbers ensures value is not zero. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. The field under validation must be present and not empty only if any of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only if all of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: The field under validation must be present and not empty only when any of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only when all of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: This validates that the value is the default value and is almost the opposite of required. For numbers, length will ensure that the value is equal to the parameter given. For strings, it checks that the string length is exactly that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, max will ensure that the value is less than or equal to the parameter given. For strings, it checks that the string length is at most that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, min will ensure that the value is greater or equal to the parameter given. For strings, it checks that the string length is at least that number of characters. For slices, arrays, and maps, validates the number of items. For strings & numbers, eq will ensure that the value is equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings & numbers, ne will ensure that the value is not equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings, ints, and uints, oneof will ensure that the value is one of the values in the parameter. The parameter should be a list of values separated by whitespace. Values may be strings or numbers. For numbers, this will ensure that the value is greater than the parameter given. For strings, it checks that the string length is greater than that number of characters. For slices, arrays and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than time.Now.UTC(). Same as 'min' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than or equal to time.Now.UTC(). For numbers, this will ensure that the value is less than the parameter given. For strings, it checks that the string length is less than that number of characters. For slices, arrays, and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than time.Now.UTC(). Same as 'max' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than or equal to time.Now.UTC(). This will validate the field value against another fields value either within a struct or passed in field. Example #1: Example #2: Field Equals Another Field (relative) This does the same as eqfield except that it validates the field provided relative to the top level struct. This will validate the field value against another fields value either within a struct or passed in field. Examples: Field Does Not Equal Another Field (relative) This does the same as nefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltefield except that it validates the field provided relative to the top level struct. This does the same as contains except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. This does the same as excludes except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. For arrays & slices, unique will ensure that there are no duplicates. For maps, unique will ensure that there are no duplicate values. For slices of struct, unique will ensure that there are no duplicate values in a field of the struct specified via a parameter. This validates that a string value contains ASCII alpha characters only This validates that a string value contains ASCII alphanumeric characters only This validates that a string value contains unicode alpha characters only This validates that a string value contains unicode alphanumeric characters only This validates that a string value contains a basic numeric value. basic excludes exponents etc... for integers or float it returns true. This validates that a string value contains a valid hexadecimal. This validates that a string value contains a valid hex color including hashtag (#) This validates that a string value contains a valid rgb color This validates that a string value contains a valid rgba color This validates that a string value contains a valid hsl color This validates that a string value contains a valid hsla color This validates that a string value contains a valid email This may not conform to all possibilities of any rfc standard, but neither does any email provider accept all possibilities. This validates that a string value contains a valid file path and that the file exists on the machine. This is done using os.Stat, which is a platform independent function. This validates that a string value contains a valid url This will accept any url the golang request uri accepts but must contain a schema for example http:// or rtmp:// This validates that a string value contains a valid uri This will accept any uri the golang request uri accepts This validataes that a string value contains a valid URN according to the RFC 2141 spec. This validates that a string value contains a valid base64 value. Although an empty string is valid base64 this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid base64 URL safe value according the the RFC4648 spec. Although an empty string is a valid base64 URL safe value, this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid bitcoin address. The format of the string is checked to ensure it matches one of the three formats P2PKH, P2SH and performs checksum validation. Bitcoin Bech32 Address (segwit) This validates that a string value contains a valid bitcoin Bech32 address as defined by bip-0173 (https://github.com/bitcoin/bips/blob/master/bip-0173.mediawiki) Special thanks to Pieter Wuille for providng reference implementations. This validates that a string value contains a valid ethereum address. The format of the string is checked to ensure it matches the standard Ethereum address format Full validation is blocked by https://github.com/golang/crypto/pull/28 This validates that a string value contains the substring value. This validates that a string value contains any Unicode code points in the substring value. This validates that a string value contains the supplied rune value. This validates that a string value does not contain the substring value. This validates that a string value does not contain any Unicode code points in the substring value. This validates that a string value does not contain the supplied rune value. This validates that a string value starts with the supplied string value This validates that a string value ends with the supplied string value This validates that a string value contains a valid isbn10 or isbn13 value. This validates that a string value contains a valid isbn10 value. This validates that a string value contains a valid isbn13 value. This validates that a string value contains a valid UUID. Uppercase UUID values will not pass - use `uuid_rfc4122` instead. This validates that a string value contains a valid version 3 UUID. Uppercase UUID values will not pass - use `uuid3_rfc4122` instead. This validates that a string value contains a valid version 4 UUID. Uppercase UUID values will not pass - use `uuid4_rfc4122` instead. This validates that a string value contains a valid version 5 UUID. Uppercase UUID values will not pass - use `uuid5_rfc4122` instead. This validates that a string value contains only ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains only printable ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains one or more multibyte characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains a valid DataURI. NOTE: this will also validate that the data portion is valid base64 This validates that a string value contains a valid latitude. This validates that a string value contains a valid longitude. This validates that a string value contains a valid U.S. Social Security Number. This validates that a string value contains a valid IP Address. This validates that a string value contains a valid v4 IP Address. This validates that a string value contains a valid v6 IP Address. This validates that a string value contains a valid CIDR Address. This validates that a string value contains a valid v4 CIDR Address. This validates that a string value contains a valid v6 CIDR Address. This validates that a string value contains a valid resolvable TCP Address. This validates that a string value contains a valid resolvable v4 TCP Address. This validates that a string value contains a valid resolvable v6 TCP Address. This validates that a string value contains a valid resolvable UDP Address. This validates that a string value contains a valid resolvable v4 UDP Address. This validates that a string value contains a valid resolvable v6 UDP Address. This validates that a string value contains a valid resolvable IP Address. This validates that a string value contains a valid resolvable v4 IP Address. This validates that a string value contains a valid resolvable v6 IP Address. This validates that a string value contains a valid Unix Address. This validates that a string value contains a valid MAC Address. Note: See Go's ParseMAC for accepted formats and types: This validates that a string value is a valid Hostname according to RFC 952 https://tools.ietf.org/html/rfc952 This validates that a string value is a valid Hostname according to RFC 1123 https://tools.ietf.org/html/rfc1123 Full Qualified Domain Name (FQDN) This validates that a string value contains a valid FQDN. This validates that a string value appears to be an HTML element tag including those described at https://developer.mozilla.org/en-US/docs/Web/HTML/Element This validates that a string value is a proper character reference in decimal or hexadecimal format This validates that a string value is percent-encoded (URL encoded) according to https://tools.ietf.org/html/rfc3986#section-2.1 This validates that a string value contains a valid directory and that it exists on the machine. This is done using os.Stat, which is a platform independent function. NOTE: When returning an error, the tag returned in "FieldError" will be the alias tag unless the dive tag is part of the alias. Everything after the dive tag is not reported as the alias tag. Also, the "ActualTag" in the before case will be the actual tag within the alias that failed. Here is a list of the current built in alias tags: Validator notes: A collection of validation rules that are frequently needed but are more complex than the ones found in the baked in validators. A non standard validator must be registered manually like you would with your own custom validation functions. Example of registration and use: Here is a list of the current non standard validators: This package panics when bad input is provided, this is by design, bad code like that should not make it to production.
Package jsonschema provides json-schema compilation and validation. This implementation of JSON Schema, supports draft4, draft6 and draft7. Passes all tests(including optional) in https://github.com/json-schema/JSON-Schema-Test-Suite An example of using this package: The schema is compiled against the version specified in `$schema` property. If `$schema` property is missing, it uses latest draft which currently is draft7. You can force to use draft4 when `$schema` is missing, as follows: you can also validate go value using schema.ValidateInterface(interface{}) method. but the argument should not be user-defined struct. This package supports loading json-schema from filePath and fileURL. To load json-schema from HTTPURL, add following import: Loading from urls for other schemes (such as ftp), can be plugged in. see package jsonschema/httploader for an example To load json-schema from in-memory: alternatively: This package supports json string formats: date-time, date, time, duration, uuid, hostname, email, ip-address, ipv4, ipv6, uri, uriref, regex, format, json-pointer, relative-json-pointer, uri-template (limited validation). Developers can register their own formats by adding them to jsonschema.Formats map. "base64" contentEncoding is supported. Custom decoders can be registered by adding them to jsonschema.Decoders map. "application/json" contentMediaType is supported. Custom mediatypes can be registered by adding them to jsonschema.MediaTypes map. The ValidationError returned by Validate method contains detailed context to understand why and where the error is. Custom Extensions can be registered as shown in extension_test.go
Package cal provides extensions to the time package for handling holidays and work days (business days). Work days are defined as Monday through Friday on dates that are not holidays or the alternate observation dates for holidays. As in the time package, all calculations assume a Gregorian calendar.
Package minimock is a command line tool that parses the input Go source file that contains an interface declaration and generates implementation of this interface that can be used as a mock. 1. It's integrated with the standard Go "testing" package 2. It supports variadic methods and embedded interfaces 3. It's very convenient to use generated mocks in table tests because it implements builder pattern to set up several mocks 4. It provides a useful Wait(time.Duration) helper to test concurrent code 5. It generates helpers to check if the mocked methods have been called and keeps your tests clean and up to date 6. It generates concurrent-safe mock execution counters that you can use in your mocks to implement sophisticated mocks behaviour Let's say we have the following interface declaration in github.com/gojuno/minimock/tests package: Here is how to generate the mock for this interface: The result file ./tests/formatter_mock_test.go will contain the following code: Setting up a mock using direct assignment: Setting up a mock using builder pattern and Return method: Setting up a mock using builder and Set method: Builder pattern is convenient when you have to mock more than one method of an interface. Let's say we have an io.ReadCloser interface which has two methods: Read and Close Then you can set up a mock using just one assignment: You can also use invocation counters in your mocks and tests: minimock.Controller When you have to mock multiple dependencies in your test it's recommended to use minimock.Controller and its Finish or Wait methods. All you have to do is instantiate the Controller and pass it as an argument to the mocks' constructors: Every mock is registered in the controller so by calling mc.Finish() you can verify that all the registered mocks have been called within your test. Sometimes we write tons of mocks for our tests but over time the tested code stops using mocked dependencies, however mocks are still present and being initialized in the test files. So while tested code can shrink, tests are only growing. To prevent this minimock provides Finish() method that verifies that all your mocks have been called at least once during the test run. Testing concurrent code is tough. Fortunately minimock provides you with the helper method that makes testing concurrent code easy. Here is how it works: Minimock comman line args:
Package telnet provides TELNET and TELNETS client and server implementations in a style similar to the "net/http" library that is part of the Go standard library, including support for "middleware"; TELNETS is secure TELNET, with the TELNET protocol over a secured TLS (or SSL) connection. ListenAndServe starts a (un-secure) TELNET server with a given address and handler. ListenAndServeTLS starts a (secure) TELNETS server with a given address and handler, using the specified "cert.pem" and "key.pem" files. Example TELNET Client: DialToAndCall creates a (un-secure) TELNET client, which connects to a given address using the specified caller. Example TELNETS Client: DialToAndCallTLS creates a (secure) TELNETS client, which connects to a given address using the specified caller. If you are communicating over the open Internet, you should be using (the secure) TELNETS protocol and ListenAndServeTLS. If you are communicating just on localhost, then using just (the un-secure) TELNET protocol and telnet.ListenAndServe may be OK. If you are not sure which to use, use TELNETS and ListenAndServeTLS. The previous 2 exaple servers were very very simple. Specifically, they just echoed back whatever you submitted to it. If you typed: ... it would send back: (Exactly the same data you sent it.) A more useful TELNET server can be made using the "github.com/reiver/go-telnet/telsh" sub-package. The `telsh` sub-package provides "middleware" that enables you to create a "shell" interface (also called a "command line interface" or "CLI") which most people would expect when using TELNET OR TELNETS. For example: Note that in the example, so far, we have registered 2 commands: `date` and `animate`. For this to actually work, we need to have code for the `date` and `animate` commands. The actual implemenation for the `date` command could be done like the following: Note that your "real" work is in the `dateHandlerFunc` func. And the actual implementation for the `animate` command could be done as follows: Again, note that your "real" work is in the `animateHandlerFunc` func. If you are using the telnet.ListenAndServeTLS func or the telnet.Server.ListenAndServeTLS method, you will need to supply "cert.pem" and "key.pem" files. If you do not already have these files, the Go soure code contains a tool for generating these files for you. It can be found at: So, for example, if your `$GOROOT` is the "/usr/local/go" directory, then it would be at: If you run the command: ... then you get the help information for "generate_cert.go". Of course, you would replace or set `$GOROOT` with whatever your path actually is. Again, for example, if your `$GOROOT` is the "/usr/local/go" directory, then it would be: To demonstrate the usage of "generate_cert.go", you might run the following to generate certificates that were bound to the hosts `127.0.0.1` and `localhost`: If you are not sure where "generate_cert.go" is on your computer, on Linux and Unix based systems, you might be able to find the file with the command: (If it finds it, it should output the full path to this file.) You can make a simple (un-secure) TELNET client with code like the following: You can make a simple (secure) TELNETS client with code like the following: The TELNET protocol is best known for providing a means of connecting to a remote computer, using a (text-based) shell interface, and being able to interact with it, (more or less) as if you were sitting at that computer. (Shells are also known as command-line interfaces or CLIs.) Although this was the original usage of the TELNET protocol, it can be (and is) used for other purposes as well. The TELNET protocol came from an era in computing when text-based shell interface where the common way of interacting with computers. The common interface for computers during this era was a keyboard and a monochromatic (i.e., single color) text-based monitors called "video terminals". (The word "video" in that era of computing did not refer to things such as movies. But instead was meant to contrast it with paper. In particular, the teletype machines, which were typewriter like devices that had a keyboard, but instead of having a monitor had paper that was printed onto.) In that era, in the early days of office computers, it was rare that an individual would have a computer at their desk. (A single computer was much too expensive.) Instead, there would be a single central computer that everyone would share. The style of computer used (for the single central shared computer) was called a "mainframe". What individuals would have at their desks, instead of their own compuer, would be some type of video terminal. The different types of video terminals had named such as: • VT52 • VT100 • VT220 • VT240 ("VT" in those named was short for "video terminal".) To understand this era, we need to go back a bit in time to what came before it: teletypes. Terminal codes (also sometimes called 'terminal control codes') are used to issue various kinds of commands to the terminal. (Note that 'terminal control codes' are a completely separate concept for 'TELNET commands', and the two should NOT be conflated or confused.) The most common types of 'terminal codes' are the 'ANSI escape codes'. (Although there are other types too.) ANSI escape codes (also sometimes called 'ANSI escape sequences') are a common type of 'terminal code' used to do things such as: • moving the cursor, • erasing the display, • erasing the line, • setting the graphics mode, • setting the foregroup color, • setting the background color, • setting the screen resolution, and • setting keyboard strings. One of the abilities of ANSI escape codes is to set the foreground color. Here is a table showing codes for this: (Note that in the `[]byte` that the first `byte` is the number `27` (which is the "escape" character) where the third and fouth characters are the **not** number literals, but instead character literals `'3'` and whatever.) Another of the abilities of ANSI escape codes is to set the background color. (Note that in the `[]byte` that the first `byte` is the number `27` (which is the "escape" character) where the third and fouth characters are the **not** number literals, but instead character literals `'4'` and whatever.) In Go code, if I wanted to use an ANSI escape code to use a blue background, a white foreground, and bold, I could do that with the ANSI escape code: Note that that start with byte value 27, which we have encoded as hexadecimal as \x1b. Followed by the '[' character. Coming after that is the sub-string "44", which is the code that sets our background color to blue. We follow that with the ';' character (which separates codes). And the after that comes the sub-string "37", which is the code that set our foreground color to white. After that, we follow with another ";" character (which, again, separates codes). And then we follow it the sub-string "1", which is the code that makes things bold. And finally, the ANSI escape sequence is finished off with the 'm' character. To show this in a more complete example, our `dateHandlerFunc` from before could incorporate ANSI escape sequences as follows: Note that in that example, in addition to using the ANSI escape sequence "\x1b[44;37;1m" to set the background color to blue, set the foreground color to white, and make it bold, we also used the ANSI escape sequence "\x1b[0m" to reset the background and foreground colors and boldness back to "normal".
Package date provides time.Time derivatives that conform to the Swagger.io (https://swagger.io/) defined date formats: Date and DateTime. Both types may, in most cases, be used in lieu of time.Time types. And both convert to time.Time through a ToTime method.
Package ora implements an Oracle database driver. ### Golang Oracle Database Driver ### #### TL;DR; just use it #### Call stored procedure with OUT parameters: An Oracle database may be accessed through the database/sql(http://golang.org/pkg/database/sql) package or through the ora package directly. database/sql offers connection pooling, thread safety, a consistent API to multiple database technologies and a common set of Go types. The ora package offers additional features including pointers, slices, nullable types, numerics of various sizes, Oracle-specific types, Go return type configuration, and Oracle abstractions such as environment, server and session. The ora package is written with the Oracle Call Interface (OCI) C-language libraries provided by Oracle. The OCI libraries are a standard for client application communication and driver communication with Oracle databases. The ora package has been verified to work with: * Oracle Standard 11g (11.2.0.4.0), Linux x86_64 (RHEL6) * Oracle Enterprise 12c (12.1.0.1.0), Windows 8.1 and AMD64. --- * [Installation](https://github.com/rana/ora#installation) * [Data Types](https://github.com/rana/ora#data-types) * [SQL Placeholder Syntax](https://github.com/rana/ora#sql-placeholder-syntax) * [Working With The Sql Package](https://github.com/rana/ora#working-with-the-sql-package) * [Working With The Oracle Package Directly](https://github.com/rana/ora#working-with-the-oracle-package-directly) * [Logging](https://github.com/rana/ora#logging) * [Test Database Setup](https://github.com/rana/ora#test-database-setup) * [Limitations](https://github.com/rana/ora#limitations) * [License](https://github.com/rana/ora#license) * [API Reference](http://godoc.org/github.com/rana/ora#pkg-index) * [Examples](./examples) --- Minimum requirements are Go 1.3 with CGO enabled, a GCC C compiler, and Oracle 11g (11.2.0.4.0) or Oracle Instant Client (11.2.0.4.0). Install Oracle or Oracle Instant Client. Copy the [oci8.pc](contrib/oci8.pc) from the `contrib` folder (or the one for your system, maybe tailored to your specific locations) to a folder in `$PKG_CONFIG_PATH` or a system folder, such as The ora package has no external Go dependencies and is available on GitHub and gopkg.in: *WARNING*: If you have Oracle Instant Client 11.2, you'll need to add "=lnnz11" to the list of linked libs! Otherwise, you may encounter "undefined reference to `nzosSCSP_SetCertSelectionParams' " errors. Oracle Instant Client 12.1 does not need this. The ora package supports all built-in Oracle data types. The supported Oracle built-in data types are NUMBER, BINARY_DOUBLE, BINARY_FLOAT, FLOAT, DATE, TIMESTAMP, TIMESTAMP WITH TIME ZONE, TIMESTAMP WITH LOCAL TIME ZONE, INTERVAL YEAR TO MONTH, INTERVAL DAY TO SECOND, CHAR, NCHAR, VARCHAR, VARCHAR2, NVARCHAR2, LONG, CLOB, NCLOB, BLOB, LONG RAW, RAW, ROWID and BFILE. SYS_REFCURSOR is also supported. Oracle does not provide a built-in boolean type. Oracle provides a single-byte character type. A common practice is to define two single-byte characters which represent true and false. The ora package adopts this approach. The oracle package associates a Go bool value to a Go rune and sends and receives the rune to a CHAR(1 BYTE) column or CHAR(1 CHAR) column. The default false rune is zero '0'. The default true rune is one '1'. The bool rune association may be configured or disabled when directly using the ora package but not with the database/sql package. Within a SQL string a placeholder may be specified to indicate where a Go variable is placed. The SQL placeholder is an Oracle identifier, from 1 to 30 characters, prefixed with a colon (:). For example: Placeholders within a SQL statement are bound by position. The actual name is not used by the ora package driver e.g., placeholder names :c1, :1, or :xyz are treated equally. The `database/sql` package provides a LastInsertId method to return the last inserted row's id. Oracle does not provide such functionality, but if you append `... RETURNING col /*LastInsertId*/` to your SQL, then it will be presented as LastInsertId. Note that you have to mark with a `/*LastInsertId*/` (case insensitive) your `RETURNING` part, to allow ora to return the last column as `LastInsertId()`. That column must fit in `int64`, though! You may access an Oracle database through the database/sql package. The database/sql package offers a consistent API across different databases, connection pooling, thread safety and a set of common Go types. database/sql makes working with Oracle straight-forward. The ora package implements interfaces in the database/sql/driver package enabling database/sql to communicate with an Oracle database. Using database/sql ensures you never have to call the ora package directly. When using database/sql, the mapping between Go types and Oracle types may be changed slightly. The database/sql package has strict expectations on Go return types. The Go-to-Oracle type mapping for database/sql is: The "ora" driver is automatically registered for use with sql.Open, but you can call ora.SetCfg to set the used configuration options including statement configuration and Rset configuration. When configuring the driver for use with database/sql, keep in mind that database/sql has strict Go type-to-Oracle type mapping expectations. The ora package allows programming with pointers, slices, nullable types, numerics of various sizes, Oracle-specific types, Go return type configuration, and Oracle abstractions such as environment, server and session. When working with the ora package directly, the API is slightly different than database/sql. When using the ora package directly, the mapping between Go types and Oracle types may be changed. The Go-to-Oracle type mapping for the ora package is: An example of using the ora package directly: Pointers may be used to capture out-bound values from a SQL statement such as an insert or stored procedure call. For example, a numeric pointer captures an identity value: A string pointer captures an out parameter from a stored procedure: Slices may be used to insert multiple records with a single insert statement: The ora package provides nullable Go types to support DML operations such as insert and select. The nullable Go types provided by the ora package are Int64, Int32, Int16, Int8, Uint64, Uint32, Uint16, Uint8, Float64, Float32, Time, IntervalYM, IntervalDS, String, Bool, Binary and Bfile. For example, you may insert nullable Strings and select nullable Strings: The `Stmt.Prep` method is variadic accepting zero or more `GoColumnType` which define a Go return type for a select-list column. For example, a Prep call can be configured to return an int64 and a nullable Int64 from the same column: Go numerics of various sizes are supported in DML operations. The ora package supports int64, int32, int16, int8, uint64, uint32, uint16, uint8, float64 and float32. For example, you may insert a uint16 and select numerics of various sizes: If a non-nullable type is defined for a nullable column returning null, the Go type's zero value is returned. GoColumnTypes defined by the ora package are: When Stmt.Prep doesn't receive a GoColumnType, or receives an incorrect GoColumnType, the default value defined in RsetCfg is used. EnvCfg, SrvCfg, SesCfg, StmtCfg and RsetCfg are the main configuration structs. EnvCfg configures aspects of an Env. SrvCfg configures aspects of a Srv. SesCfg configures aspects of a Ses. StmtCfg configures aspects of a Stmt. RsetCfg configures aspects of Rset. StmtCfg and RsetCfg have the most options to configure. RsetCfg defines the default mapping between an Oracle select-list column and a Go type. StmtCfg may be set in an EnvCfg, SrvCfg, SesCfg and StmtCfg. RsetCfg may be set in a Stmt. EnvCfg.StmtCfg, SrvCfg.StmtCfg, SesCfg.StmtCfg may optionally be specified to configure a statement. If StmtCfg isn't specified default values are applied. EnvCfg.StmtCfg, SrvCfg.StmtCfg, SesCfg.StmtCfg cascade to new descendent structs. When ora.OpenEnv() is called a specified EnvCfg is used or a default EnvCfg is created. Creating a Srv with env.OpenSrv() will use SrvCfg.StmtCfg if it is specified; otherwise, EnvCfg.StmtCfg is copied by value to SrvCfg.StmtCfg. Creating a Ses with srv.OpenSes() will use SesCfg.StmtCfg if it is specified; otherwise, SrvCfg.StmtCfg is copied by value to SesCfg.StmtCfg. Creating a Stmt with ses.Prep() will use SesCfg.StmtCfg if it is specified; otherwise, a new StmtCfg with default values is set on the Stmt. Call Stmt.Cfg() to change a Stmt's configuration. An Env may contain multiple Srv. A Srv may contain multiple Ses. A Ses may contain multiple Stmt. A Stmt may contain multiple Rset. Setting a RsetCfg on a StmtCfg does not cascade through descendent structs. Configuration of Stmt.Cfg takes effect prior to calls to Stmt.Exe and Stmt.Qry; consequently, any updates to Stmt.Cfg after a call to Stmt.Exe or Stmt.Qry are not observed. One configuration scenario may be to set a server's select statements to return nullable Go types by default: Another scenario may be to configure the runes mapped to bool values: Oracle-specific types offered by the ora package are ora.Rset, ora.IntervalYM, ora.IntervalDS, ora.Raw, ora.Lob and ora.Bfile. ora.Rset represents an Oracle SYS_REFCURSOR. ora.IntervalYM represents an Oracle INTERVAL YEAR TO MONTH. ora.IntervalDS represents an Oracle INTERVAL DAY TO SECOND. ora.Raw represents an Oracle RAW or LONG RAW. ora.Lob may represent an Oracle BLOB or Oracle CLOB. And ora.Bfile represents an Oracle BFILE. ROWID columns are returned as strings and don't have a unique Go type. #### LOBs The default for SELECTing [BC]LOB columns is a safe Bin or S, which means all the contents of the LOB is slurped into memory and returned as a []byte or string. The DefaultLOBFetchLen says LOBs are prefetched only a minimal way, to minimize extra memory usage - you can override this using `stmt.SetCfg(stmt.Cfg().SetLOBFetchLen(100))`. If you want more control, you can use ora.L in Prep, Qry or `ses.SetCfg(ses.Cfg().SetBlob(ora.L))`. But keep in mind that Oracle restricts the use of LOBs: it is forbidden to do ANYTHING while reading the LOB! No another query, no exec, no close of the Rset - even *advance* to the next record in the result set is forbidden! Failing to adhere these rules results in "Invalid handle" and ORA-03127 errors. You cannot start reading another LOB till you haven't finished reading the previous LOB, not even in the same row! Failing this results in ORA-24804! For examples, see [z_lob_test.go](z_lob_test.go). #### Rset Rset is used to obtain Go values from a SQL select statement. Methods Rset.Next, Rset.NextRow, and Rset.Len are available. Fields Rset.Row, Rset.Err, Rset.Index, and Rset.ColumnNames are also available. The Next method attempts to load data from an Oracle buffer into Row, returning true when successful. When no data is available, or if an error occurs, Next returns false setting Row to nil. Any error in Next is assigned to Err. Calling Next increments Index and method Len returns the total number of rows processed. The NextRow method is convenient for returning a single row. NextRow calls Next and returns Row. ColumnNames returns the names of columns defined by the SQL select statement. Rset has two usages. Rset may be returned from Stmt.Qry when prepared with a SQL select statement: Or, *Rset may be passed to Stmt.Exe when prepared with a stored procedure accepting an OUT SYS_REFCURSOR parameter: Stored procedures with multiple OUT SYS_REFCURSOR parameters enable a single Exe call to obtain multiple Rsets: The types of values assigned to Row may be configured in StmtCfg.Rset. For configuration to take effect, assign StmtCfg.Rset prior to calling Stmt.Qry or Stmt.Exe. Rset prefetching may be controlled by StmtCfg.PrefetchRowCount and StmtCfg.PrefetchMemorySize. PrefetchRowCount works in coordination with PrefetchMemorySize. When PrefetchRowCount is set to zero only PrefetchMemorySize is used; otherwise, the minimum of PrefetchRowCount and PrefetchMemorySize is used. The default uses a PrefetchMemorySize of 134MB. Opening and closing Rsets is managed internally. Rset does not have an Open method or Close method. IntervalYM may be be inserted and selected: IntervalDS may be be inserted and selected: Transactions on an Oracle server are supported. DML statements auto-commit unless a transaction has started: Ses.PrepAndExe, Ses.PrepAndQry, Ses.Ins, Ses.Upd, and Ses.Sel are convenient one-line methods. Ses.PrepAndExe offers a convenient one-line call to Ses.Prep and Stmt.Exe. Ses.PrepAndQry offers a convenient one-line call to Ses.Prep and Stmt.Qry. Ses.Ins composes, prepares and executes a sql INSERT statement. Ses.Ins is useful when you have to create and maintain a simple INSERT statement with a long list of columns. As table columns are added and dropped over the lifetime of a table Ses.Ins is easy to read and revise. Ses.Upd composes, prepares and executes a sql UPDATE statement. Ses.Upd is useful when you have to create and maintain a simple UPDATE statement with a long list of columns. As table columns are added and dropped over the lifetime of a table Ses.Upd is easy to read and revise. Ses.Sel composes, prepares and queries a sql SELECT statement. Ses.Sel is useful when you have to create and maintain a simple SELECT statement with a long list of columns that have non-default GoColumnTypes. As table columns are added and dropped over the lifetime of a table Ses.Sel is easy to read and revise. The Ses.Ping method checks whether the client's connection to an Oracle server is valid. A call to Ping requires an open Ses. Ping will return a nil error when the connection is fine: The Srv.Version method is available to obtain the Oracle server version. A call to Version requires an open Ses: Further code examples are available in the [example file](https://github.com/rana/ora/blob/master/z_example_test.go), test files and [samples folder](https://github.com/rana/ora/tree/master/samples). The ora package provides a simple ora.Logger interface for logging. Logging is disabled by default. Specify one of three optional built-in logging packages to enable logging; or, use your own logging package. ora.Cfg().Log offers various options to enable or disable logging of specific ora driver methods. For example: To use the standard Go log package: which produces a sample log of: Messages are prefixed with 'ORA I' for information or 'ORA E' for an error. The log package is configured to write to os.Stderr by default. Use the ora/lg.Std type to configure an alternative io.Writer. To use the glog package: which produces a sample log of: To use the log15 package: which produces a sample log of: See https://github.com/rana/ora/tree/master/samples/lg15/main.go for sample code which uses the log15 package. Tests are available and require some setup. Setup varies depending on whether the Oracle server is configured as a container database or non-container database. It's simpler to setup a non-container database. An example for each setup is explained. Non-container test database setup steps: Container test database setup steps: Some helpful SQL maintenance statements: Run the tests. database/sql method Stmt.QueryRow is not supported. Go 1.6 introduced stricter cgo (call C from Go) rules, and introduced runtime checks. This is good, as the possibility of C code corrupting Go code is almost completely eliminated, but it also means a severe call overhead grow. [Sometimes](https://groups.google.com/forum/#!topic/golang-nuts/ccMkPG6Bi5k) this can be 22x the go 1.5.3 call time! So if you need performance more than correctness, start your programs with "GODEBUG=cgocheck=0" environment setting. Copyright 2017 Rana Ian, Tamás Gulácsi. All rights reserved. Use of this source code is governed by The MIT License found in the accompanying LICENSE file.
Package minimock is a command line tool that parses the input Go source file that contains an interface declaration and generates implementation of this interface that can be used as a mock. 1. It's integrated with the standard Go "testing" package 2. It supports variadic methods and embedded interfaces 3. It's very convenient to use generated mocks in table tests because it implements builder pattern to set up several mocks 4. It provides a useful Wait(time.Duration) helper to test concurrent code 5. It generates helpers to check if the mocked methods have been called and keeps your tests clean and up to date 6. It generates concurrent-safe mock execution counters that you can use in your mocks to implement sophisticated mocks behaviour Let's say we have the following interface declaration in github.com/gojuno/minimock/tests package: Here is how to generate the mock for this interface: The result file ./tests/formatter_mock_test.go will contain the following code: Setting up a mock using direct assignment: Setting up a mock using builder pattern and Return method: Setting up a mock using builder and Set method: Builder pattern is convenient when you have to mock more than one method of an interface. Let's say we have an io.ReadCloser interface which has two methods: Read and Close Then you can set up a mock using just one assignment: You can also use invocation counters in your mocks and tests: minimock.Controller When you have to mock multiple dependencies in your test it's recommended to use minimock.Controller and its Finish or Wait methods. All you have to do is instantiate the Controller and pass it as an argument to the mocks' constructors: Every mock is registered in the controller so by calling mc.Finish() you can verify that all the registered mocks have been called within your test. Sometimes we write tons of mocks for our tests but over time the tested code stops using mocked dependencies, however mocks are still present and being initialized in the test files. So while tested code can shrink, tests are only growing. To prevent this minimock provides Finish() method that verifies that all your mocks have been called at least once during the test run. Testing concurrent code is tough. Fortunately minimock provides you with the helper method that makes testing concurrent code easy. Here is how it works: Minimock comman line args:
Package timefmt provides functions for formatting and parsing date time strings.
The depaware command makes you aware of your dependencies by putting them in your face in git and during code review. The idea is that you store the depaware output next to any desired packages or binaries and check them in to git, making it a CI failure if they're out of date, and thus make you aware of dependency changes during code review. See https://github.com/tailscale/depaware
Package validator implements value validations for structs and individual fields based on tags. It can also handle Cross-Field and Cross-Struct validation for nested structs and has the ability to dive into arrays and maps of any type. see more examples https://github.com/go-playground/validator/tree/v9/_examples Doing things this way is actually the way the standard library does, see the file.Open method here: The authors return type "error" to avoid the issue discussed in the following, where err is always != nil: Validator only InvalidValidationError for bad validation input, nil or ValidationErrors as type error; so, in your code all you need to do is check if the error returned is not nil, and if it's not check if error is InvalidValidationError ( if necessary, most of the time it isn't ) type cast it to type ValidationErrors like so err.(validator.ValidationErrors). Custom Validation functions can be added. Example: Cross-Field Validation can be done via the following tags: If, however, some custom cross-field validation is required, it can be done using a custom validation. Why not just have cross-fields validation tags (i.e. only eqcsfield and not eqfield)? The reason is efficiency. If you want to check a field within the same struct "eqfield" only has to find the field on the same struct (1 level). But, if we used "eqcsfield" it could be multiple levels down. Example: Multiple validators on a field will process in the order defined. Example: Bad Validator definitions are not handled by the library. Example: Baked In Cross-Field validation only compares fields on the same struct. If Cross-Field + Cross-Struct validation is needed you should implement your own custom validator. Comma (",") is the default separator of validation tags. If you wish to have a comma included within the parameter (i.e. excludesall=,) you will need to use the UTF-8 hex representation 0x2C, which is replaced in the code as a comma, so the above will become excludesall=0x2C. Pipe ("|") is the 'or' validation tags deparator. If you wish to have a pipe included within the parameter i.e. excludesall=| you will need to use the UTF-8 hex representation 0x7C, which is replaced in the code as a pipe, so the above will become excludesall=0x7C Here is a list of the current built in validators: Tells the validation to skip this struct field; this is particularly handy in ignoring embedded structs from being validated. (Usage: -) This is the 'or' operator allowing multiple validators to be used and accepted. (Usage: rbg|rgba) <-- this would allow either rgb or rgba colors to be accepted. This can also be combined with 'and' for example ( Usage: omitempty,rgb|rgba) When a field that is a nested struct is encountered, and contains this flag any validation on the nested struct will be run, but none of the nested struct fields will be validated. This is useful if inside of your program you know the struct will be valid, but need to verify it has been assigned. NOTE: only "required" and "omitempty" can be used on a struct itself. Same as structonly tag except that any struct level validations will not run. Allows conditional validation, for example if a field is not set with a value (Determined by the "required" validator) then other validation such as min or max won't run, but if a value is set validation will run. This tells the validator to dive into a slice, array or map and validate that level of the slice, array or map with the validation tags that follow. Multidimensional nesting is also supported, each level you wish to dive will require another dive tag. dive has some sub-tags, 'keys' & 'endkeys', please see the Keys & EndKeys section just below. Example #1 Example #2 Keys & EndKeys These are to be used together directly after the dive tag and tells the validator that anything between 'keys' and 'endkeys' applies to the keys of a map and not the values; think of it like the 'dive' tag, but for map keys instead of values. Multidimensional nesting is also supported, each level you wish to validate will require another 'keys' and 'endkeys' tag. These tags are only valid for maps. Example #1 Example #2 This validates that the value is not the data types default zero value. For numbers ensures value is not zero. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. The field under validation must be present and not empty only if any of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only if all of the other specified fields are present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: The field under validation must be present and not empty only when any of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Examples: The field under validation must be present and not empty only when all of the other specified fields are not present. For strings ensures value is not "". For slices, maps, pointers, interfaces, channels and functions ensures the value is not nil. Example: This validates that the value is the default value and is almost the opposite of required. For numbers, length will ensure that the value is equal to the parameter given. For strings, it checks that the string length is exactly that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, max will ensure that the value is less than or equal to the parameter given. For strings, it checks that the string length is at most that number of characters. For slices, arrays, and maps, validates the number of items. For numbers, min will ensure that the value is greater or equal to the parameter given. For strings, it checks that the string length is at least that number of characters. For slices, arrays, and maps, validates the number of items. For strings & numbers, eq will ensure that the value is equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings & numbers, ne will ensure that the value is not equal to the parameter given. For slices, arrays, and maps, validates the number of items. For strings, ints, and uints, oneof will ensure that the value is one of the values in the parameter. The parameter should be a list of values separated by whitespace. Values may be strings or numbers. For numbers, this will ensure that the value is greater than the parameter given. For strings, it checks that the string length is greater than that number of characters. For slices, arrays and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than time.Now.UTC(). Same as 'min' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is greater than or equal to time.Now.UTC(). For numbers, this will ensure that the value is less than the parameter given. For strings, it checks that the string length is less than that number of characters. For slices, arrays, and maps it validates the number of items. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than time.Now.UTC(). Same as 'max' above. Kept both to make terminology with 'len' easier. Example #1 Example #2 (time.Time) For time.Time ensures the time value is less than or equal to time.Now.UTC(). This will validate the field value against another fields value either within a struct or passed in field. Example #1: Example #2: Field Equals Another Field (relative) This does the same as eqfield except that it validates the field provided relative to the top level struct. This will validate the field value against another fields value either within a struct or passed in field. Examples: Field Does Not Equal Another Field (relative) This does the same as nefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as gtefield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltfield except that it validates the field provided relative to the top level struct. Only valid for Numbers and time.Time types, this will validate the field value against another fields value either within a struct or passed in field. usage examples are for validation of a Start and End date: Example #1: Example #2: This does the same as ltefield except that it validates the field provided relative to the top level struct. This does the same as contains except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. This does the same as excludes except for struct fields. It should only be used with string types. See the behavior of reflect.Value.String() for behavior on other types. For arrays & slices, unique will ensure that there are no duplicates. For maps, unique will ensure that there are no duplicate values. For slices of struct, unique will ensure that there are no duplicate values in a field of the struct specified via a parameter. This validates that a string value contains ASCII alpha characters only This validates that a string value contains ASCII alphanumeric characters only This validates that a string value contains unicode alpha characters only This validates that a string value contains unicode alphanumeric characters only This validates that a string value contains a basic numeric value. basic excludes exponents etc... for integers or float it returns true. This validates that a string value contains a valid hexadecimal. This validates that a string value contains a valid hex color including hashtag (#) This validates that a string value contains a valid rgb color This validates that a string value contains a valid rgba color This validates that a string value contains a valid hsl color This validates that a string value contains a valid hsla color This validates that a string value contains a valid email This may not conform to all possibilities of any rfc standard, but neither does any email provider accept all possibilities. This validates that a string value contains a valid file path and that the file exists on the machine. This is done using os.Stat, which is a platform independent function. This validates that a string value contains a valid url This will accept any url the golang request uri accepts but must contain a schema for example http:// or rtmp:// This validates that a string value contains a valid uri This will accept any uri the golang request uri accepts This validataes that a string value contains a valid URN according to the RFC 2141 spec. This validates that a string value contains a valid base64 value. Although an empty string is valid base64 this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid base64 URL safe value according the the RFC4648 spec. Although an empty string is a valid base64 URL safe value, this will report an empty string as an error, if you wish to accept an empty string as valid you can use this with the omitempty tag. This validates that a string value contains a valid bitcoin address. The format of the string is checked to ensure it matches one of the three formats P2PKH, P2SH and performs checksum validation. Bitcoin Bech32 Address (segwit) This validates that a string value contains a valid bitcoin Bech32 address as defined by bip-0173 (https://github.com/bitcoin/bips/blob/master/bip-0173.mediawiki) Special thanks to Pieter Wuille for providng reference implementations. This validates that a string value contains a valid ethereum address. The format of the string is checked to ensure it matches the standard Ethereum address format Full validation is blocked by https://github.com/golang/crypto/pull/28 This validates that a string value contains the substring value. This validates that a string value contains any Unicode code points in the substring value. This validates that a string value contains the supplied rune value. This validates that a string value does not contain the substring value. This validates that a string value does not contain any Unicode code points in the substring value. This validates that a string value does not contain the supplied rune value. This validates that a string value starts with the supplied string value This validates that a string value ends with the supplied string value This validates that a string value contains a valid isbn10 or isbn13 value. This validates that a string value contains a valid isbn10 value. This validates that a string value contains a valid isbn13 value. This validates that a string value contains a valid UUID. Uppercase UUID values will not pass - use `uuid_rfc4122` instead. This validates that a string value contains a valid version 3 UUID. Uppercase UUID values will not pass - use `uuid3_rfc4122` instead. This validates that a string value contains a valid version 4 UUID. Uppercase UUID values will not pass - use `uuid4_rfc4122` instead. This validates that a string value contains a valid version 5 UUID. Uppercase UUID values will not pass - use `uuid5_rfc4122` instead. This validates that a string value contains only ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains only printable ASCII characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains one or more multibyte characters. NOTE: if the string is blank, this validates as true. This validates that a string value contains a valid DataURI. NOTE: this will also validate that the data portion is valid base64 This validates that a string value contains a valid latitude. This validates that a string value contains a valid longitude. This validates that a string value contains a valid U.S. Social Security Number. This validates that a string value contains a valid IP Address. This validates that a string value contains a valid v4 IP Address. This validates that a string value contains a valid v6 IP Address. This validates that a string value contains a valid CIDR Address. This validates that a string value contains a valid v4 CIDR Address. This validates that a string value contains a valid v6 CIDR Address. This validates that a string value contains a valid resolvable TCP Address. This validates that a string value contains a valid resolvable v4 TCP Address. This validates that a string value contains a valid resolvable v6 TCP Address. This validates that a string value contains a valid resolvable UDP Address. This validates that a string value contains a valid resolvable v4 UDP Address. This validates that a string value contains a valid resolvable v6 UDP Address. This validates that a string value contains a valid resolvable IP Address. This validates that a string value contains a valid resolvable v4 IP Address. This validates that a string value contains a valid resolvable v6 IP Address. This validates that a string value contains a valid Unix Address. This validates that a string value contains a valid MAC Address. Note: See Go's ParseMAC for accepted formats and types: This validates that a string value is a valid Hostname according to RFC 952 https://tools.ietf.org/html/rfc952 This validates that a string value is a valid Hostname according to RFC 1123 https://tools.ietf.org/html/rfc1123 Full Qualified Domain Name (FQDN) This validates that a string value contains a valid FQDN. This validates that a string value appears to be an HTML element tag including those described at https://developer.mozilla.org/en-US/docs/Web/HTML/Element This validates that a string value is a proper character reference in decimal or hexadecimal format This validates that a string value is percent-encoded (URL encoded) according to https://tools.ietf.org/html/rfc3986#section-2.1 This validates that a string value contains a valid directory and that it exists on the machine. This is done using os.Stat, which is a platform independent function. NOTE: When returning an error, the tag returned in "FieldError" will be the alias tag unless the dive tag is part of the alias. Everything after the dive tag is not reported as the alias tag. Also, the "ActualTag" in the before case will be the actual tag within the alias that failed. Here is a list of the current built in alias tags: Validator notes: A collection of validation rules that are frequently needed but are more complex than the ones found in the baked in validators. A non standard validator must be registered manually like you would with your own custom validation functions. Example of registration and use: Here is a list of the current non standard validators: This package panics when bad input is provided, this is by design, bad code like that should not make it to production.
Package datemath provides an expression language for relative dates based on Elasticsearch's date math. This package is useful for letting end-users describe dates in a simple format similar to Grafana and Kibana and for persisting them as relative dates. The expression starts with an anchor date, which can either be "now", or an ISO8601 date string ending with ||. This anchor date can optionally be followed by one or more date math expressions, for example: The supported time units are: This package aims to be a superset of Elasticsearch's expressions. That is, any datemath expression that is valid for Elasticsearch should evaluate in the same way here. In addition to the expressions supported by Elasticsearch, this package also supports business days, annual quarters, and fiscal years/quarters.
Package validator implements value validations for structs and individual fields based on tags. It can also handle Cross Field and Cross Struct validation for nested structs and has the ability to dive into arrays and maps of any type. Why not a better error message? because this library intends for you to handle your own error messages. Why should I handle my own errors? Many reasons, for us building an internationalized application I needed to know the field and what validation failed so that I could provide an error in the users specific language. Custom functions can be added Cross Field Validation can be implemented, for example Start & End Date range validation Multiple validators on a field will process in the order defined Bad Validator definitions are not handled by the library NOTE: Baked In Cross field validation only compares fields on the same struct, if cross field + cross struct validation is needed your own custom validator should be implemented. NOTE2: comma is the default separator of validation tags, if you wish to have a comma included within the parameter i.e. excludesall=, you will need to use the UTF-8 hex representation 0x2C, which is replaced in the code as a comma, so the above will become excludesall=0x2C NOTE3: pipe is the default separator of or validation tags, if you wish to have a pipe included within the parameter i.e. excludesall=| you will need to use the UTF-8 hex representation 0x7C, which is replaced in the code as a pipe, so the above will become excludesall=0x7C Here is a list of the current built in validators: Validator notes: This package panics when bad input is provided, this is by design, bad code like that should not make it to production.
fmtdate provides a date formatter and parser using the syntax of Microsoft Excel (TM). Additionally it offers default conversions for date time and datetime. Why? Microsoft Excel (TM) has a well known syntax for date formatting, that more memorable than the syntax chosen in the time package in the go library. Usage
Copyright (c) 2018-2019 The kaspanet developers Copyright (c) 2013-2018 The btcsuite developers Copyright (c) 2015-2016 The Decred developers Copyright (c) 2013-2014 Conformal Systems LLC. Use of this source code is governed by an ISC license that can be found in the LICENSE file. Kaspad is a full-node kaspa implementation written in Go. The default options are sane for most users. This means kaspad will work 'out of the box' for most users. However, there are also a wide variety of flags that can be used to control it. Usage: For an up-to-date help message: The long form of all option flags (except -C) can be specified in a configuration file that is automatically parsed when kaspad starts up. By default, the configuration file is located at ~/.kaspad/kaspad.conf on POSIX-style operating systems and %LOCALAPPDATA%\kaspad\kaspad.conf on Windows. The -C (--configfile) flag can be used to override this location.
Package datetime provides a ParseTime function for turning commonly-used ISO 8601 date/time formats into Golang time.Time variables. Unlike Go's built-in RFC-3339 time format, this package automatically supports ISO 8601 date and time stamps with varying levels of granularity. Examples:
Package raft sends and receives messages in the Protocol Buffer format defined in the raftpb package. Raft is a protocol with which a cluster of nodes can maintain a replicated state machine. The state machine is kept in sync through the use of a replicated log. For more details on Raft, see "In Search of an Understandable Consensus Algorithm" (https://raft.github.io/raft.pdf) by Diego Ongaro and John Ousterhout. A simple example application, _raftexample_, is also available to help illustrate how to use this package in practice: https://github.com/etcd-io/etcd/tree/main/contrib/raftexample The primary object in raft is a Node. You either start a Node from scratch using raft.StartNode or start a Node from some initial state using raft.RestartNode. To start a node from scratch: To restart a node from previous state: Now that you are holding onto a Node you have a few responsibilities: First, you must read from the Node.Ready() channel and process the updates it contains. These steps may be performed in parallel, except as noted in step 2. 1. Write HardState, Entries, and Snapshot to persistent storage if they are not empty. Note that when writing an Entry with Index i, any previously-persisted entries with Index >= i must be discarded. 2. Send all Messages to the nodes named in the To field. It is important that no messages be sent until the latest HardState has been persisted to disk, and all Entries written by any previous Ready batch (Messages may be sent while entries from the same batch are being persisted). To reduce the I/O latency, an optimization can be applied to make leader write to disk in parallel with its followers (as explained at section 10.2.1 in Raft thesis). If any Message has type MsgSnap, call Node.ReportSnapshot() after it has been sent (these messages may be large). Note: Marshalling messages is not thread-safe; it is important that you make sure that no new entries are persisted while marshalling. The easiest way to achieve this is to serialize the messages directly inside your main raft loop. 3. Apply Snapshot (if any) and CommittedEntries to the state machine. If any committed Entry has Type EntryConfChange, call Node.ApplyConfChange() to apply it to the node. The configuration change may be cancelled at this point by setting the NodeID field to zero before calling ApplyConfChange (but ApplyConfChange must be called one way or the other, and the decision to cancel must be based solely on the state machine and not external information such as the observed health of the node). 4. Call Node.Advance() to signal readiness for the next batch of updates. This may be done at any time after step 1, although all updates must be processed in the order they were returned by Ready. Second, all persisted log entries must be made available via an implementation of the Storage interface. The provided MemoryStorage type can be used for this (if you repopulate its state upon a restart), or you can supply your own disk-backed implementation. Third, when you receive a message from another node, pass it to Node.Step: Finally, you need to call Node.Tick() at regular intervals (probably via a time.Ticker). Raft has two important timeouts: heartbeat and the election timeout. However, internally to the raft package time is represented by an abstract "tick". The total state machine handling loop will look something like this: To propose changes to the state machine from your node take your application data, serialize it into a byte slice and call: If the proposal is committed, data will appear in committed entries with type raftpb.EntryNormal. There is no guarantee that a proposed command will be committed; you may have to re-propose after a timeout. To add or remove a node in a cluster, build ConfChange struct 'cc' and call: After config change is committed, some committed entry with type raftpb.EntryConfChange will be returned. You must apply it to node through: Note: An ID represents a unique node in a cluster for all time. A given ID MUST be used only once even if the old node has been removed. This means that for example IP addresses make poor node IDs since they may be reused. Node IDs must be non-zero. The library can be configured with an alternate interface for local storage writes that can provide better performance in the presence of high proposal concurrency by minimizing interference between proposals. This feature is called AsynchronousStorageWrites, and can be enabled using the flag on the Config struct with the same name. When Asynchronous Storage Writes is enabled, the responsibility of code using the library is different from what was presented above. Users still read from the Node.Ready() channel. However, they process the updates it contains in a different manner. Users no longer consult the HardState, Entries, and Snapshot fields (steps 1 and 3 above). They also no longer call Node.Advance() to indicate that they have processed all entries in the Ready (step 4 above). Instead, all local storage operations are also communicated through messages present in the Ready.Message slice. The local storage messages come in two flavors. The first flavor is log append messages, which target a LocalAppendThread and carry Entries, HardState, and a Snapshot. The second flavor is entry application messages, which target a LocalApplyThread and carry CommittedEntries. Messages to the same target must be reliably processed in order. Messages to different targets can be processed in any order. Each local storage message carries a slice of response messages that must delivered after the corresponding storage write has been completed. These responses may target the same node or may target other nodes. With Asynchronous Storage Writes enabled, the total state machine handling loop will look something like this: Usage of Asynchronous Storage Writes will typically also contain a pair of storage handler threads, one for log writes (append) and one for entry application to the local state machine (apply). Those will look something like: This implementation is up to date with the final Raft thesis (https://github.com/ongardie/dissertation/blob/master/stanford.pdf), although our implementation of the membership change protocol differs somewhat from that described in chapter 4. The key invariant that membership changes happen one node at a time is preserved, but in our implementation the membership change takes effect when its entry is applied, not when it is added to the log (so the entry is committed under the old membership instead of the new). This is equivalent in terms of safety, since the old and new configurations are guaranteed to overlap. To ensure that we do not attempt to commit two membership changes at once by matching log positions (which would be unsafe since they should have different quorum requirements), we simply disallow any proposed membership change while any uncommitted change appears in the leader's log. This approach introduces a problem when you try to remove a member from a two-member cluster: If one of the members dies before the other one receives the commit of the confchange entry, then the member cannot be removed any more since the cluster cannot make progress. For this reason it is highly recommended to use three or more nodes in every cluster. Package raft sends and receives message in Protocol Buffer format (defined in raftpb package). Each state (follower, candidate, leader) implements its own 'step' method ('stepFollower', 'stepCandidate', 'stepLeader') when advancing with the given raftpb.Message. Each step is determined by its raftpb.MessageType. Note that every step is checked by one common method 'Step' that safety-checks the terms of node and incoming message to prevent stale log entries:
Package ql implements a pure Go embedded SQL database engine. Builder results available at QL is a member of the SQL family of languages. It is less complex and less powerful than SQL (whichever specification SQL is considered to be). 2020-12-10: sql/database driver now supports url parameter removeemptywal=N which has the same semantics as passing RemoveEmptyWAL = N != 0 to OpenFile options. 2020-11-09: Add IF NOT EXISTS support for the INSERT INTO statement. Add IsDuplicateUniqueIndexError function. 2018-11-04: Back end file format V2 is now released. To use the new format for newly created databases set the FileFormat field in *Options passed to OpenFile to value 2 or use the driver named "ql2" instead of "ql". - Both the old and new driver will properly open and use, read and write the old (V1) or new file (V2) format of an existing database. - V1 format has a record size limit of ~64 kB. V2 format record size limit is math.MaxInt32. - V1 format uncommitted transaction size is limited by memory resources. V2 format uncommitted transaction is limited by free disk space. - A direct consequence of the previous is that small transactions perform better using V1 format and big transactions perform better using V2 format. - V2 format uses substantially less memory. 2018-08-02: Release v1.2.0 adds initial support for Go modules. 2017-01-10: Release v1.1.0 fixes some bugs and adds a configurable WAL headroom. 2016-07-29: Release v1.0.6 enables alternatively using = instead of == for equality operation. 2016-07-11: Release v1.0.5 undoes vendoring of lldb. QL now uses stable lldb (modernc.org/lldb). 2016-07-06: Release v1.0.4 fixes a panic when closing the WAL file. 2016-04-03: Release v1.0.3 fixes a data race. 2016-03-23: Release v1.0.2 vendors gitlab.com/cznic/exp/lldb and github.com/camlistore/go4/lock. 2016-03-17: Release v1.0.1 adjusts for latest goyacc. Parser error messages are improved and changed, but their exact form is not considered a API change. 2016-03-05: The current version has been tagged v1.0.0. 2015-06-15: To improve compatibility with other SQL implementations, the count built-in aggregate function now accepts * as its argument. 2015-05-29: The execution planner was rewritten from scratch. It should use indices in all places where they were used before plus in some additional situations. It is possible to investigate the plan using the newly added EXPLAIN statement. The QL tool is handy for such analysis. If the planner would have used an index, but no such exists, the plan includes hints in form of copy/paste ready CREATE INDEX statements. The planner is still quite simple and a lot of work on it is yet ahead. You can help this process by filling an issue with a schema and query which fails to use an index or indices when it should, in your opinion. Bonus points for including output of `ql 'explain <query>'`. 2015-05-09: The grammar of the CREATE INDEX statement now accepts an expression list instead of a single expression, which was further limited to just a column name or the built-in id(). As a side effect, composite indices are now functional. However, the values in the expression-list style index are not yet used by other statements or the statement/query planner. The composite index is useful while having UNIQUE clause to check for semantically duplicate rows before they get added to the table or when such a row is mutated using the UPDATE statement and the expression-list style index tuple of the row is thus recomputed. 2015-05-02: The Schema field of table __Table now correctly reflects any column constraints and/or defaults. Also, the (*DB).Info method now has that information provided in new ColumInfo fields NotNull, Constraint and Default. 2015-04-20: Added support for {LEFT,RIGHT,FULL} [OUTER] JOIN. 2015-04-18: Column definitions can now have constraints and defaults. Details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. 2015-03-06: New built-in functions formatFloat and formatInt. Thanks urandom! (https://github.com/urandom) 2015-02-16: IN predicate now accepts a SELECT statement. See the updated "Predicates" section. 2015-01-17: Logical operators || and && have now alternative spellings: OR and AND (case insensitive). AND was a keyword before, but OR is a new one. This can possibly break existing queries. For the record, it's a good idea to not use any name appearing in, for example, [7] in your queries as the list of QL's keywords may expand for gaining better compatibility with existing SQL "standards". 2015-01-12: ACID guarantees were tightened at the cost of performance in some cases. The write collecting window mechanism, a formerly used implementation detail, was removed. Inserting rows one by one in a transaction is now slow. I mean very slow. Try to avoid inserting single rows in a transaction. Instead, whenever possible, perform batch updates of tens to, say thousands of rows in a single transaction. See also: http://www.sqlite.org/faq.html#q19, the discussed synchronization principles involved are the same as for QL, modulo minor details. Note: A side effect is that closing a DB before exiting an application, both for the Go API and through database/sql driver, is no more required, strictly speaking. Beware that exiting an application while there is an open (uncommitted) transaction in progress means losing the transaction data. However, the DB will not become corrupted because of not closing it. Nor that was the case before, but formerly failing to close a DB could have resulted in losing the data of the last transaction. 2014-09-21: id() now optionally accepts a single argument - a table name. 2014-09-01: Added the DB.Flush() method and the LIKE pattern matching predicate. 2014-08-08: The built in functions max and min now accept also time values. Thanks opennota! (https://github.com/opennota) 2014-06-05: RecordSet interface extended by new methods FirstRow and Rows. 2014-06-02: Indices on id() are now used by SELECT statements. 2014-05-07: Introduction of Marshal, Schema, Unmarshal. 2014-04-15: Added optional IF NOT EXISTS clause to CREATE INDEX and optional IF EXISTS clause to DROP INDEX. 2014-04-12: The column Unique in the virtual table __Index was renamed to IsUnique because the old name is a keyword. Unfortunately, this is a breaking change, sorry. 2014-04-11: Introduction of LIMIT, OFFSET. 2014-04-10: Introduction of query rewriting. 2014-04-07: Introduction of indices. QL imports zappy[8], a block-based compressor, which speeds up its performance by using a C version of the compression/decompression algorithms. If a CGO-free (pure Go) version of QL, or an app using QL, is required, please include 'purego' in the -tags option of go {build,get,install}. For example: If zappy was installed before installing QL, it might be necessary to rebuild zappy first (or rebuild QL with all its dependencies using the -a option): The syntax is specified using Extended Backus-Naur Form (EBNF) Lower-case production names are used to identify lexical tokens. Non-terminals are in CamelCase. Lexical tokens are enclosed in double quotes "" or back quotes “. The form a … b represents the set of characters from a through b as alternatives. The horizontal ellipsis … is also used elsewhere in the spec to informally denote various enumerations or code snippets that are not further specified. QL source code is Unicode text encoded in UTF-8. The text is not canonicalized, so a single accented code point is distinct from the same character constructed from combining an accent and a letter; those are treated as two code points. For simplicity, this document will use the unqualified term character to refer to a Unicode code point in the source text. Each code point is distinct; for instance, upper and lower case letters are different characters. Implementation restriction: For compatibility with other tools, the parser may disallow the NUL character (U+0000) in the statement. Implementation restriction: A byte order mark is disallowed anywhere in QL statements. The following terms are used to denote specific character classes The underscore character _ (U+005F) is considered a letter. Lexical elements are comments, tokens, identifiers, keywords, operators and delimiters, integer, floating-point, imaginary, rune and string literals and QL parameters. Line comments start with the character sequence // or -- and stop at the end of the line. A line comment acts like a space. General comments start with the character sequence /* and continue through the character sequence */. A general comment acts like a space. Comments do not nest. Tokens form the vocabulary of QL. There are four classes: identifiers, keywords, operators and delimiters, and literals. White space, formed from spaces (U+0020), horizontal tabs (U+0009), carriage returns (U+000D), and newlines (U+000A), is ignored except as it separates tokens that would otherwise combine into a single token. The formal grammar uses semicolons ";" as separators of QL statements. A single QL statement or the last QL statement in a list of statements can have an optional semicolon terminator. (Actually a separator from the following empty statement.) Identifiers name entities such as tables or record set columns. There are two kinds of identifiers, normal idententifiers and quoted identifiers. An normal identifier is a sequence of one or more letters and digits. The first character in an identifier must be a letter. For example A quoted identifier is a string of any charaters between guillmets «». Quoted identifiers allow QL key words or phrases with spaces to be used as identifiers. The guillemets were chosen because QL already uses double quotes, single quotes, and backticks for other quoting purposes. «TRANSACTION» «duration» «lovely stories» No identifiers are predeclared, however note that no keyword can be used as a normal identifier. Identifiers starting with two underscores are used for meta data virtual tables names. For forward compatibility, users should generally avoid using any identifiers starting with two underscores. For example The following keywords are reserved and may not be used as identifiers. Keywords are not case sensitive. The following character sequences represent operators, delimiters, and other special tokens Operators consisting of more than one character are referred to by names in the rest of the documentation An integer literal is a sequence of digits representing an integer constant. An optional prefix sets a non-decimal base: 0 for octal, 0x or 0X for hexadecimal. In hexadecimal literals, letters a-f and A-F represent values 10 through 15. For example A floating-point literal is a decimal representation of a floating-point constant. It has an integer part, a decimal point, a fractional part, and an exponent part. The integer and fractional part comprise decimal digits; the exponent part is an e or E followed by an optionally signed decimal exponent. One of the integer part or the fractional part may be elided; one of the decimal point or the exponent may be elided. For example An imaginary literal is a decimal representation of the imaginary part of a complex constant. It consists of a floating-point literal or decimal integer followed by the lower-case letter i. For example A rune literal represents a rune constant, an integer value identifying a Unicode code point. A rune literal is expressed as one or more characters enclosed in single quotes. Within the quotes, any character may appear except single quote and newline. A single quoted character represents the Unicode value of the character itself, while multi-character sequences beginning with a backslash encode values in various formats. The simplest form represents the single character within the quotes; since QL statements are Unicode characters encoded in UTF-8, multiple UTF-8-encoded bytes may represent a single integer value. For instance, the literal 'a' holds a single byte representing a literal a, Unicode U+0061, value 0x61, while 'ä' holds two bytes (0xc3 0xa4) representing a literal a-dieresis, U+00E4, value 0xe4. Several backslash escapes allow arbitrary values to be encoded as ASCII text. There are four ways to represent the integer value as a numeric constant: \x followed by exactly two hexadecimal digits; \u followed by exactly four hexadecimal digits; \U followed by exactly eight hexadecimal digits, and a plain backslash \ followed by exactly three octal digits. In each case the value of the literal is the value represented by the digits in the corresponding base. Although these representations all result in an integer, they have different valid ranges. Octal escapes must represent a value between 0 and 255 inclusive. Hexadecimal escapes satisfy this condition by construction. The escapes \u and \U represent Unicode code points so within them some values are illegal, in particular those above 0x10FFFF and surrogate halves. After a backslash, certain single-character escapes represent special values All other sequences starting with a backslash are illegal inside rune literals. For example A string literal represents a string constant obtained from concatenating a sequence of characters. There are two forms: raw string literals and interpreted string literals. Raw string literals are character sequences between back quotes “. Within the quotes, any character is legal except back quote. The value of a raw string literal is the string composed of the uninterpreted (implicitly UTF-8-encoded) characters between the quotes; in particular, backslashes have no special meaning and the string may contain newlines. Carriage returns inside raw string literals are discarded from the raw string value. Interpreted string literals are character sequences between double quotes "". The text between the quotes, which may not contain newlines, forms the value of the literal, with backslash escapes interpreted as they are in rune literals (except that \' is illegal and \" is legal), with the same restrictions. The three-digit octal (\nnn) and two-digit hexadecimal (\xnn) escapes represent individual bytes of the resulting string; all other escapes represent the (possibly multi-byte) UTF-8 encoding of individual characters. Thus inside a string literal \377 and \xFF represent a single byte of value 0xFF=255, while ÿ, \u00FF, \U000000FF and \xc3\xbf represent the two bytes 0xc3 0xbf of the UTF-8 encoding of character U+00FF. For example These examples all represent the same string If the statement source represents a character as two code points, such as a combining form involving an accent and a letter, the result will be an error if placed in a rune literal (it is not a single code point), and will appear as two code points if placed in a string literal. Literals are assigned their values from the respective text representation at "compile" (parse) time. QL parameters provide the same functionality as literals, but their value is assigned at execution time from an expression list passed to DB.Run or DB.Execute. Using '?' or '$' is completely equivalent. For example Keywords 'false' and 'true' (not case sensitive) represent the two possible constant values of type bool (also not case sensitive). Keyword 'NULL' (not case sensitive) represents an untyped constant which is assignable to any type. NULL is distinct from any other value of any type. A type determines the set of values and operations specific to values of that type. A type is specified by a type name. Named instances of the boolean, numeric, and string types are keywords. The names are not case sensitive. Note: The blob type is exchanged between the back end and the API as []byte. On 32 bit platforms this limits the size which the implementation can handle to 2G. A boolean type represents the set of Boolean truth values denoted by the predeclared constants true and false. The predeclared boolean type is bool. A duration type represents the elapsed time between two instants as an int64 nanosecond count. The representation limits the largest representable duration to approximately 290 years. A numeric type represents sets of integer or floating-point values. The predeclared architecture-independent numeric types are The value of an n-bit integer is n bits wide and represented using two's complement arithmetic. Conversions are required when different numeric types are mixed in an expression or assignment. A string type represents the set of string values. A string value is a (possibly empty) sequence of bytes. The case insensitive keyword for the string type is 'string'. The length of a string (its size in bytes) can be discovered using the built-in function len. A time type represents an instant in time with nanosecond precision. Each time has associated with it a location, consulted when computing the presentation form of the time. The following functions are implicitly declared An expression specifies the computation of a value by applying operators and functions to operands. Operands denote the elementary values in an expression. An operand may be a literal, a (possibly qualified) identifier denoting a constant or a function or a table/record set column, or a parenthesized expression. A qualified identifier is an identifier qualified with a table/record set name prefix. For example Primary expression are the operands for unary and binary expressions. For example A primary expression of the form denotes the element of a string indexed by x. Its type is byte. The value x is called the index. The following rules apply - The index x must be of integer type except bigint or duration; it is in range if 0 <= x < len(s), otherwise it is out of range. - A constant index must be non-negative and representable by a value of type int. - A constant index must be in range if the string a is a literal. - If x is out of range at run time, a run-time error occurs. - s[x] is the byte at index x and the type of s[x] is byte. If s is NULL or x is NULL then the result is NULL. Otherwise s[x] is illegal. For a string, the primary expression constructs a substring. The indices low and high select which elements appear in the result. The result has indices starting at 0 and length equal to high - low. For convenience, any of the indices may be omitted. A missing low index defaults to zero; a missing high index defaults to the length of the sliced operand The indices low and high are in range if 0 <= low <= high <= len(a), otherwise they are out of range. A constant index must be non-negative and representable by a value of type int. If both indices are constant, they must satisfy low <= high. If the indices are out of range at run time, a run-time error occurs. Integer values of type bigint or duration cannot be used as indices. If s is NULL the result is NULL. If low or high is not omitted and is NULL then the result is NULL. Given an identifier f denoting a predeclared function, calls f with arguments a1, a2, … an. Arguments are evaluated before the function is called. The type of the expression is the result type of f. In a function call, the function value and arguments are evaluated in the usual order. After they are evaluated, the parameters of the call are passed by value to the function and the called function begins execution. The return value of the function is passed by value when the function returns. Calling an undefined function causes a compile-time error. Operators combine operands into expressions. Comparisons are discussed elsewhere. For other binary operators, the operand types must be identical unless the operation involves shifts or untyped constants. For operations involving constants only, see the section on constant expressions. Except for shift operations, if one operand is an untyped constant and the other operand is not, the constant is converted to the type of the other operand. The right operand in a shift expression must have unsigned integer type or be an untyped constant that can be converted to unsigned integer type. If the left operand of a non-constant shift expression is an untyped constant, the type of the constant is what it would be if the shift expression were replaced by its left operand alone. Expressions of the form yield a boolean value true if expr2, a regular expression, matches expr1 (see also [6]). Both expression must be of type string. If any one of the expressions is NULL the result is NULL. Predicates are special form expressions having a boolean result type. Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be comparable as defined in "Comparison operators". Another form of the IN predicate creates the expression list from a result of a SelectStmt. The SelectStmt must select only one column. The produced expression list is resource limited by the memory available to the process. NULL values produced by the SelectStmt are ignored, but if all records of the SelectStmt are NULL the predicate yields NULL. The select statement is evaluated only once. If the type of expr is not the same as the type of the field returned by the SelectStmt then the set operation yields false. The type of the column returned by the SelectStmt must be one of the simple (non blob-like) types: Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be ordered as defined in "Comparison operators". Expressions of the form yield a boolean value true if expr does not have a specific type (case A) or if expr has a specific type (case B). In other cases the result is a boolean value false. Unary operators have the highest precedence. There are five precedence levels for binary operators. Multiplication operators bind strongest, followed by addition operators, comparison operators, && (logical AND), and finally || (logical OR) Binary operators of the same precedence associate from left to right. For instance, x / y * z is the same as (x / y) * z. Note that the operator precedence is reflected explicitly by the grammar. Arithmetic operators apply to numeric values and yield a result of the same type as the first operand. The four standard arithmetic operators (+, -, *, /) apply to integer, rational, floating-point, and complex types; + also applies to strings; +,- also applies to times. All other arithmetic operators apply to integers only. sum integers, rationals, floats, complex values, strings difference integers, rationals, floats, complex values, times product integers, rationals, floats, complex values / quotient integers, rationals, floats, complex values % remainder integers & bitwise AND integers | bitwise OR integers ^ bitwise XOR integers &^ bit clear (AND NOT) integers << left shift integer << unsigned integer >> right shift integer >> unsigned integer Strings can be concatenated using the + operator String addition creates a new string by concatenating the operands. A value of type duration can be added to or subtracted from a value of type time. Times can subtracted from each other producing a value of type duration. For two integer values x and y, the integer quotient q = x / y and remainder r = x % y satisfy the following relationships with x / y truncated towards zero ("truncated division"). As an exception to this rule, if the dividend x is the most negative value for the int type of x, the quotient q = x / -1 is equal to x (and r = 0). If the divisor is a constant expression, it must not be zero. If the divisor is zero at run time, a run-time error occurs. If the dividend is non-negative and the divisor is a constant power of 2, the division may be replaced by a right shift, and computing the remainder may be replaced by a bitwise AND operation The shift operators shift the left operand by the shift count specified by the right operand. They implement arithmetic shifts if the left operand is a signed integer and logical shifts if it is an unsigned integer. There is no upper limit on the shift count. Shifts behave as if the left operand is shifted n times by 1 for a shift count of n. As a result, x << 1 is the same as x*2 and x >> 1 is the same as x/2 but truncated towards negative infinity. For integer operands, the unary operators +, -, and ^ are defined as follows For floating-point and complex numbers, +x is the same as x, while -x is the negation of x. The result of a floating-point or complex division by zero is not specified beyond the IEEE-754 standard; whether a run-time error occurs is implementation-specific. Whenever any operand of any arithmetic operation, unary or binary, is NULL, as well as in the case of the string concatenating operation, the result is NULL. For unsigned integer values, the operations +, -, *, and << are computed modulo 2n, where n is the bit width of the unsigned integer's type. Loosely speaking, these unsigned integer operations discard high bits upon overflow, and expressions may rely on “wrap around”. For signed integers with a finite bit width, the operations +, -, *, and << may legally overflow and the resulting value exists and is deterministically defined by the signed integer representation, the operation, and its operands. No exception is raised as a result of overflow. An evaluator may not optimize an expression under the assumption that overflow does not occur. For instance, it may not assume that x < x + 1 is always true. Integers of type bigint and rationals do not overflow but their handling is limited by the memory resources available to the program. Comparison operators compare two operands and yield a boolean value. In any comparison, the first operand must be of same type as is the second operand, or vice versa. The equality operators == and != apply to operands that are comparable. The ordering operators <, <=, >, and >= apply to operands that are ordered. These terms and the result of the comparisons are defined as follows - Boolean values are comparable. Two boolean values are equal if they are either both true or both false. - Complex values are comparable. Two complex values u and v are equal if both real(u) == real(v) and imag(u) == imag(v). - Integer values are comparable and ordered, in the usual way. Note that durations are integers. - Floating point values are comparable and ordered, as defined by the IEEE-754 standard. - Rational values are comparable and ordered, in the usual way. - String and Blob values are comparable and ordered, lexically byte-wise. - Time values are comparable and ordered. Whenever any operand of any comparison operation is NULL, the result is NULL. Note that slices are always of type string. Logical operators apply to boolean values and yield a boolean result. The right operand is evaluated conditionally. The truth tables for logical operations with NULL values Conversions are expressions of the form T(x) where T is a type and x is an expression that can be converted to type T. A constant value x can be converted to type T in any of these cases: - x is representable by a value of type T. - x is a floating-point constant, T is a floating-point type, and x is representable by a value of type T after rounding using IEEE 754 round-to-even rules. The constant T(x) is the rounded value. - x is an integer constant and T is a string type. The same rule as for non-constant x applies in this case. Converting a constant yields a typed constant as result. A non-constant value x can be converted to type T in any of these cases: - x has type T. - x's type and T are both integer or floating point types. - x's type and T are both complex types. - x is an integer, except bigint or duration, and T is a string type. Specific rules apply to (non-constant) conversions between numeric types or to and from a string type. These conversions may change the representation of x and incur a run-time cost. All other conversions only change the type but not the representation of x. A conversion of NULL to any type yields NULL. For the conversion of non-constant numeric values, the following rules apply 1. When converting between integer types, if the value is a signed integer, it is sign extended to implicit infinite precision; otherwise it is zero extended. It is then truncated to fit in the result type's size. For example, if v == uint16(0x10F0), then uint32(int8(v)) == 0xFFFFFFF0. The conversion always yields a valid value; there is no indication of overflow. 2. When converting a floating-point number to an integer, the fraction is discarded (truncation towards zero). 3. When converting an integer or floating-point number to a floating-point type, or a complex number to another complex type, the result value is rounded to the precision specified by the destination type. For instance, the value of a variable x of type float32 may be stored using additional precision beyond that of an IEEE-754 32-bit number, but float32(x) represents the result of rounding x's value to 32-bit precision. Similarly, x + 0.1 may use more than 32 bits of precision, but float32(x + 0.1) does not. In all non-constant conversions involving floating-point or complex values, if the result type cannot represent the value the conversion succeeds but the result value is implementation-dependent. 1. Converting a signed or unsigned integer value to a string type yields a string containing the UTF-8 representation of the integer. Values outside the range of valid Unicode code points are converted to "\uFFFD". 2. Converting a blob to a string type yields a string whose successive bytes are the elements of the blob. 3. Converting a value of a string type to a blob yields a blob whose successive elements are the bytes of the string. 4. Converting a value of a bigint type to a string yields a string containing the decimal decimal representation of the integer. 5. Converting a value of a string type to a bigint yields a bigint value containing the integer represented by the string value. A prefix of “0x” or “0X” selects base 16; the “0” prefix selects base 8, and a “0b” or “0B” prefix selects base 2. Otherwise the value is interpreted in base 10. An error occurs if the string value is not in any valid format. 6. Converting a value of a rational type to a string yields a string containing the decimal decimal representation of the rational in the form "a/b" (even if b == 1). 7. Converting a value of a string type to a bigrat yields a bigrat value containing the rational represented by the string value. The string can be given as a fraction "a/b" or as a floating-point number optionally followed by an exponent. An error occurs if the string value is not in any valid format. 8. Converting a value of a duration type to a string returns a string representing the duration in the form "72h3m0.5s". Leading zero units are omitted. As a special case, durations less than one second format using a smaller unit (milli-, micro-, or nanoseconds) to ensure that the leading digit is non-zero. The zero duration formats as 0, with no unit. 9. Converting a string value to a duration yields a duration represented by the string. A duration string is a possibly signed sequence of decimal numbers, each with optional fraction and a unit suffix, such as "300ms", "-1.5h" or "2h45m". Valid time units are "ns", "us" (or "µs"), "ms", "s", "m", "h". 10. Converting a time value to a string returns the time formatted using the format string When evaluating the operands of an expression or of function calls, operations are evaluated in lexical left-to-right order. For example, in the evaluation of the function calls and evaluation of c happen in the order h(), i(), j(), c. Floating-point operations within a single expression are evaluated according to the associativity of the operators. Explicit parentheses affect the evaluation by overriding the default associativity. In the expression x + (y + z) the addition y + z is performed before adding x. Statements control execution. The empty statement does nothing. Alter table statements modify existing tables. With the ADD clause it adds a new column to the table. The column must not exist. With the DROP clause it removes an existing column from a table. The column must exist and it must be not the only (last) column of the table. IOW, there cannot be a table with no columns. For example When adding a column to a table with existing data, the constraint clause of the ColumnDef cannot be used. Adding a constrained column to an empty table is fine. Begin transactions statements introduce a new transaction level. Every transaction level must be eventually balanced by exactly one of COMMIT or ROLLBACK statements. Note that when a transaction is roll-backed because of a statement failure then no explicit balancing of the respective BEGIN TRANSACTION is statement is required nor permitted. Failure to properly balance any opened transaction level may cause dead locks and/or lose of data updated in the uppermost opened but never properly closed transaction level. For example A database cannot be updated (mutated) outside of a transaction. Statements requiring a transaction A database is effectively read only outside of a transaction. Statements not requiring a transaction The commit statement closes the innermost transaction nesting level. If that's the outermost level then the updates to the DB made by the transaction are atomically made persistent. For example Create index statements create new indices. Index is a named projection of ordered values of a table column to the respective records. As a special case the id() of the record can be indexed. Index name must not be the same as any of the existing tables and it also cannot be the same as of any column name of the table the index is on. For example Now certain SELECT statements may use the indices to speed up joins and/or to speed up record set filtering when the WHERE clause is used; or the indices might be used to improve the performance when the ORDER BY clause is present. The UNIQUE modifier requires the indexed values tuple to be index-wise unique or have all values NULL. The optional IF NOT EXISTS clause makes the statement a no operation if the index already exists. A simple index consists of only one expression which must be either a column name or the built-in id(). A more complex and more general index is one that consists of more than one expression or its single expression does not qualify as a simple index. In this case the type of all expressions in the list must be one of the non blob-like types. Note: Blob-like types are blob, bigint, bigrat, time and duration. Create table statements create new tables. A column definition declares the column name and type. Table names and column names are case sensitive. Neither a table or an index of the same name may exist in the DB. For example The optional IF NOT EXISTS clause makes the statement a no operation if the table already exists. The optional constraint clause has two forms. The first one is found in many SQL dialects. This form prevents the data in column DepartmentName to be NULL. The second form allows an arbitrary boolean expression to be used to validate the column. If the value of the expression is true then the validation succeeded. If the value of the expression is false or NULL then the validation fails. If the value of the expression is not of type bool an error occurs. The optional DEFAULT clause is an expression which, if present, is substituted instead of a NULL value when the colum is assigned a value. Note that the constraint and/or default expressions may refer to other columns by name: When a table row is inserted by the INSERT INTO statement or when a table row is updated by the UPDATE statement, the order of operations is as follows: 1. The new values of the affected columns are set and the values of all the row columns become the named values which can be referred to in default expressions evaluated in step 2. 2. If any row column value is NULL and the DEFAULT clause is present in the column's definition, the default expression is evaluated and its value is set as the respective column value. 3. The values, potentially updated, of row columns become the named values which can be referred to in constraint expressions evaluated during step 4. 4. All row columns which definition has the constraint clause present will have that constraint checked. If any constraint violation is detected, the overall operation fails and no changes to the table are made. Delete from statements remove rows from a table, which must exist. For example If the WHERE clause is not present then all rows are removed and the statement is equivalent to the TRUNCATE TABLE statement. Drop index statements remove indices from the DB. The index must exist. For example The optional IF EXISTS clause makes the statement a no operation if the index does not exist. Drop table statements remove tables from the DB. The table must exist. For example The optional IF EXISTS clause makes the statement a no operation if the table does not exist. Insert into statements insert new rows into tables. New rows come from literal data, if using the VALUES clause, or are a result of select statement. In the later case the select statement is fully evaluated before the insertion of any rows is performed, allowing to insert values calculated from the same table rows are to be inserted into. If the ColumnNameList part is omitted then the number of values inserted in the row must be the same as are columns in the table. If the ColumnNameList part is present then the number of values per row must be same as the same number of column names. All other columns of the record are set to NULL. The type of the value assigned to a column must be the same as is the column's type or the value must be NULL. If there exists an unique index that would make the insert statement fail, the optional IF NOT EXISTS turns the insert statement in such case into a no-op. For example If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. Explain statement produces a recordset consisting of lines of text which describe the execution plan of a statement, if any. For example, the QL tool treats the explain statement specially and outputs the joined lines: The explanation may aid in uderstanding how a statement/query would be executed and if indices are used as expected - or which indices may possibly improve the statement performance. The create index statements above were directly copy/pasted in the terminal from the suggestions provided by the filter recordset pipeline part returned by the explain statement. If the statement has nothing special in its plan, the result is the original statement. To get an explanation of the select statement of the IN predicate, use the EXPLAIN statement with that particular select statement. The rollback statement closes the innermost transaction nesting level discarding any updates to the DB made by it. If that's the outermost level then the effects on the DB are as if the transaction never happened. For example The (temporary) record set from the last statement is returned and can be processed by the client. In this case the rollback is the same as 'DROP TABLE tmp;' but it can be a more complex operation. Select from statements produce recordsets. The optional DISTINCT modifier ensures all rows in the result recordset are unique. Either all of the resulting fields are returned ('*') or only those named in FieldList. RecordSetList is a list of table names or parenthesized select statements, optionally (re)named using the AS clause. The result can be filtered using a WhereClause and orderd by the OrderBy clause. For example If Recordset is a nested, parenthesized SelectStmt then it must be given a name using the AS clause if its field are to be accessible in expressions. A field is an named expression. Identifiers, not used as a type in conversion or a function name in the Call clause, denote names of (other) fields, values of which should be used in the expression. The expression can be named using the AS clause. If the AS clause is not present and the expression consists solely of a field name, then that field name is used as the name of the resulting field. Otherwise the field is unnamed. For example The SELECT statement can optionally enumerate the desired/resulting fields in a list. No two identical field names can appear in the list. When more than one record set is used in the FROM clause record set list, the result record set field names are rewritten to be qualified using the record set names. If a particular record set doesn't have a name, its respective fields became unnamed. The optional JOIN clause, for example is mostly equal to except that the rows from a which, when they appear in the cross join, never made expr to evaluate to true, are combined with a virtual row from b, containing all nulls, and added to the result set. For the RIGHT JOIN variant the discussed rules are used for rows from b not satisfying expr == true and the virtual, all-null row "comes" from a. The FULL JOIN adds the respective rows which would be otherwise provided by the separate executions of the LEFT JOIN and RIGHT JOIN variants. For more thorough OUTER JOIN discussion please see the Wikipedia article at [10]. Resultins rows of a SELECT statement can be optionally ordered by the ORDER BY clause. Collating proceeds by considering the expressions in the expression list left to right until a collating order is determined. Any possibly remaining expressions are not evaluated. All of the expression values must yield an ordered type or NULL. Ordered types are defined in "Comparison operators". Collating of elements having a NULL value is different compared to what the comparison operators yield in expression evaluation (NULL result instead of a boolean value). Below, T denotes a non NULL value of any QL type. NULL collates before any non NULL value (is considered smaller than T). Two NULLs have no collating order (are considered equal). The WHERE clause restricts records considered by some statements, like SELECT FROM, DELETE FROM, or UPDATE. It is an error if the expression evaluates to a non null value of non bool type. Another form of the WHERE clause is an existence predicate of a parenthesized select statement. The EXISTS form evaluates to true if the parenthesized SELECT statement produces a non empty record set. The NOT EXISTS form evaluates to true if the parenthesized SELECT statement produces an empty record set. The parenthesized SELECT statement is evaluated only once (TODO issue #159). The GROUP BY clause is used to project rows having common values into a smaller set of rows. For example Using the GROUP BY without any aggregate functions in the selected fields is in certain cases equal to using the DISTINCT modifier. The last two examples above produce the same resultsets. The optional OFFSET clause allows to ignore first N records. For example The above will produce only rows 11, 12, ... of the record set, if they exist. The value of the expression must a non negative integer, but not bigint or duration. The optional LIMIT clause allows to ignore all but first N records. For example The above will return at most the first 10 records of the record set. The value of the expression must a non negative integer, but not bigint or duration. The LIMIT and OFFSET clauses can be combined. For example Considering table t has, say 10 records, the above will produce only records 4 - 8. After returning record #8, no more result rows/records are computed. 1. The FROM clause is evaluated, producing a Cartesian product of its source record sets (tables or nested SELECT statements). 2. If present, the JOIN cluase is evaluated on the result set of the previous evaluation and the recordset specified by the JOIN clause. (... JOIN Recordset ON ...) 3. If present, the WHERE clause is evaluated on the result set of the previous evaluation. 4. If present, the GROUP BY clause is evaluated on the result set of the previous evaluation(s). 5. The SELECT field expressions are evaluated on the result set of the previous evaluation(s). 6. If present, the DISTINCT modifier is evaluated on the result set of the previous evaluation(s). 7. If present, the ORDER BY clause is evaluated on the result set of the previous evaluation(s). 8. If present, the OFFSET clause is evaluated on the result set of the previous evaluation(s). The offset expression is evaluated once for the first record produced by the previous evaluations. 9. If present, the LIMIT clause is evaluated on the result set of the previous evaluation(s). The limit expression is evaluated once for the first record produced by the previous evaluations. Truncate table statements remove all records from a table. The table must exist. For example Update statements change values of fields in rows of a table. For example Note: The SET clause is optional. If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. To allow to query for DB meta data, there exist specially named tables, some of them being virtual. Note: Virtual system tables may have fake table-wise unique but meaningless and unstable record IDs. Do not apply the built-in id() to any system table. The table __Table lists all tables in the DB. The schema is The Schema column returns the statement to (re)create table Name. This table is virtual. The table __Colum lists all columns of all tables in the DB. The schema is The Ordinal column defines the 1-based index of the column in the record. This table is virtual. The table __Colum2 lists all columns of all tables in the DB which have the constraint NOT NULL or which have a constraint expression defined or which have a default expression defined. The schema is It's possible to obtain a consolidated recordset for all properties of all DB columns using The Name column is the column name in TableName. The table __Index lists all indices in the DB. The schema is The IsUnique columns reflects if the index was created using the optional UNIQUE clause. This table is virtual. Built-in functions are predeclared. The built-in aggregate function avg returns the average of values of an expression. Avg ignores NULL values, but returns NULL if all values of a column are NULL or if avg is applied to an empty record set. The column values must be of a numeric type. The built-in function coalesce takes at least one argument and returns the first of its arguments which is not NULL. If all arguments are NULL, this function returns NULL. This is useful for providing defaults for NULL values in a select query. The built-in function contains returns true if substr is within s. If any argument to contains is NULL the result is NULL. The built-in aggregate function count returns how many times an expression has a non NULL values or the number of rows in a record set. Note: count() returns 0 for an empty record set. For example Date returns the time corresponding to in the appropriate zone for that time in the given location. The month, day, hour, min, sec, and nsec values may be outside their usual ranges and will be normalized during the conversion. For example, October 32 converts to November 1. A daylight savings time transition skips or repeats times. For example, in the United States, March 13, 2011 2:15am never occurred, while November 6, 2011 1:15am occurred twice. In such cases, the choice of time zone, and therefore the time, is not well-defined. Date returns a time that is correct in one of the two zones involved in the transition, but it does not guarantee which. A location maps time instants to the zone in use at that time. Typically, the location represents the collection of time offsets in use in a geographical area, such as "CEST" and "CET" for central Europe. "local" represents the system's local time zone. "UTC" represents Universal Coordinated Time (UTC). The month specifies a month of the year (January = 1, ...). If any argument to date is NULL the result is NULL. The built-in function day returns the day of the month specified by t. If the argument to day is NULL the result is NULL. The built-in function formatTime returns a textual representation of the time value formatted according to layout, which defines the format by showing how the reference time, would be displayed if it were the value; it serves as an example of the desired output. The same display rules will then be applied to the time value. If any argument to formatTime is NULL the result is NULL. NOTE: The string value of the time zone, like "CET" or "ACDT", is dependent on the time zone of the machine the function is run on. For example, if the t value is in "CET", but the machine is in "ACDT", instead of "CET" the result is "+0100". This is the same what Go (time.Time).String() returns and in fact formatTime directly calls t.String(). returns on a machine in the CET time zone, but may return on a machine in the ACDT zone. The time value is in both cases the same so its ordering and comparing is correct. Only the display value can differ. The built-in functions formatFloat and formatInt format numbers to strings using go's number format functions in the `strconv` package. For all three functions, only the first argument is mandatory. The default values of the rest are shown in the examples. If the first argument is NULL, the result is NULL. returns returns returns Unlike the `strconv` equivalent, the formatInt function handles all integer types, both signed and unsigned. The built-in function hasPrefix tests whether the string s begins with prefix. If any argument to hasPrefix is NULL the result is NULL. The built-in function hasSuffix tests whether the string s ends with suffix. If any argument to hasSuffix is NULL the result is NULL. The built-in function hour returns the hour within the day specified by t, in the range [0, 23]. If the argument to hour is NULL the result is NULL. The built-in function hours returns the duration as a floating point number of hours. If the argument to hours is NULL the result is NULL. The built-in function id takes zero or one arguments. If no argument is provided, id() returns a table-unique automatically assigned numeric identifier of type int. Ids of deleted records are not reused unless the DB becomes completely empty (has no tables). For example If id() without arguments is called for a row which is not a table record then the result value is NULL. For example If id() has one argument it must be a table name of a table in a cross join. For example The built-in function len takes a string argument and returns the lentgh of the string in bytes. The expression len(s) is constant if s is a string constant. If the argument to len is NULL the result is NULL. The built-in aggregate function max returns the largest value of an expression in a record set. Max ignores NULL values, but returns NULL if all values of a column are NULL or if max is applied to an empty record set. The expression values must be of an ordered type. For example The built-in aggregate function min returns the smallest value of an expression in a record set. Min ignores NULL values, but returns NULL if all values of a column are NULL or if min is applied to an empty record set. For example The column values must be of an ordered type. The built-in function minute returns the minute offset within the hour specified by t, in the range [0, 59]. If the argument to minute is NULL the result is NULL. The built-in function minutes returns the duration as a floating point number of minutes. If the argument to minutes is NULL the result is NULL. The built-in function month returns the month of the year specified by t (January = 1, ...). If the argument to month is NULL the result is NULL. The built-in function nanosecond returns the nanosecond offset within the second specified by t, in the range [0, 999999999]. If the argument to nanosecond is NULL the result is NULL. The built-in function nanoseconds returns the duration as an integer nanosecond count. If the argument to nanoseconds is NULL the result is NULL. The built-in function now returns the current local time. The built-in function parseTime parses a formatted string and returns the time value it represents. The layout defines the format by showing how the reference time, would be interpreted if it were the value; it serves as an example of the input format. The same interpretation will then be made to the input string. Elements omitted from the value are assumed to be zero or, when zero is impossible, one, so parsing "3:04pm" returns the time corresponding to Jan 1, year 0, 15:04:00 UTC (note that because the year is 0, this time is before the zero Time). Years must be in the range 0000..9999. The day of the week is checked for syntax but it is otherwise ignored. In the absence of a time zone indicator, parseTime returns a time in UTC. When parsing a time with a zone offset like -0700, if the offset corresponds to a time zone used by the current location, then parseTime uses that location and zone in the returned time. Otherwise it records the time as being in a fabricated location with time fixed at the given zone offset. When parsing a time with a zone abbreviation like MST, if the zone abbreviation has a defined offset in the current location, then that offset is used. The zone abbreviation "UTC" is recognized as UTC regardless of location. If the zone abbreviation is unknown, Parse records the time as being in a fabricated location with the given zone abbreviation and a zero offset. This choice means that such a time can be parses and reformatted with the same layout losslessly, but the exact instant used in the representation will differ by the actual zone offset. To avoid such problems, prefer time layouts that use a numeric zone offset. If any argument to parseTime is NULL the result is NULL. The built-in function second returns the second offset within the minute specified by t, in the range [0, 59]. If the argument to second is NULL the result is NULL. The built-in function seconds returns the duration as a floating point number of seconds. If the argument to seconds is NULL the result is NULL. The built-in function since returns the time elapsed since t. It is shorthand for now()-t. If the argument to since is NULL the result is NULL. The built-in aggregate function sum returns the sum of values of an expression for all rows of a record set. Sum ignores NULL values, but returns NULL if all values of a column are NULL or if sum is applied to an empty record set. The column values must be of a numeric type. The built-in function timeIn returns t with the location information set to loc. For discussion of the loc argument please see date(). If any argument to timeIn is NULL the result is NULL. The built-in function weekday returns the day of the week specified by t. Sunday == 0, Monday == 1, ... If the argument to weekday is NULL the result is NULL. The built-in function year returns the year in which t occurs. If the argument to year is NULL the result is NULL. The built-in function yearDay returns the day of the year specified by t, in the range [1,365] for non-leap years, and [1,366] in leap years. If the argument to yearDay is NULL the result is NULL. Three functions assemble and disassemble complex numbers. The built-in function complex constructs a complex value from a floating-point real and imaginary part, while real and imag extract the real and imaginary parts of a complex value. The type of the arguments and return value correspond. For complex, the two arguments must be of the same floating-point type and the return type is the complex type with the corresponding floating-point constituents: complex64 for float32, complex128 for float64. The real and imag functions together form the inverse, so for a complex value z, z == complex(real(z), imag(z)). If the operands of these functions are all constants, the return value is a constant. If any argument to any of complex, real, imag functions is NULL the result is NULL. For the numeric types, the following sizes are guaranteed Portions of this specification page are modifications based on work[2] created and shared by Google[3] and used according to terms described in the Creative Commons 3.0 Attribution License[4]. This specification is licensed under the Creative Commons Attribution 3.0 License, and code is licensed under a BSD license[5]. Links from the above documentation This section is not part of the specification. WARNING: The implementation of indices is new and it surely needs more time to become mature. Indices are used currently used only by the WHERE clause. The following expression patterns of 'WHERE expression' are recognized and trigger index use. The relOp is one of the relation operators <, <=, ==, >=, >. For the equality operator both operands must be of comparable types. For all other operators both operands must be of ordered types. The constant expression is a compile time constant expression. Some constant folding is still a TODO. Parameter is a QL parameter ($1 etc.). Consider tables t and u, both with an indexed field f. The WHERE expression doesn't comply with the above simple detected cases. However, such query is now automatically rewritten to which will use both of the indices. The impact of using the indices can be substantial (cf. BenchmarkCrossJoin*) if the resulting rows have low "selectivity", ie. only few rows from both tables are selected by the respective WHERE filtering. Note: Existing QL DBs can be used and indices can be added to them. However, once any indices are present in the DB, the old QL versions cannot work with such DB anymore. Running a benchmark with -v (-test.v) outputs information about the scale used to report records/s and a brief description of the benchmark. For example Running the full suite of benchmarks takes a lot of time. Use the -timeout flag to avoid them being killed after the default time limit (10 minutes).
Package cache implements Cache similar to hashicorp/golang-lru Support LRC, LRU and TTL-based eviction. Package is thread-safe and doesn't spawn any goroutines. On every Set() call, cache deletes single oldest entry in case it's expired. In case MaxSize is set, cache deletes the oldest entry disregarding its expiration date to maintain the size, either using LRC or LRU eviction. In case of default TTL (10 years) and default MaxSize (0, unlimited) the cache will be truly unlimited and will never delete entries from itself automatically. Important: only reliable way of not having expired entries stuck in a cache is to run cache.DeleteExpired periodically using time.Ticker, advisable period is 1/2 of TTL.