Compression

Package lz4 implements reading and writing lz4 compressed data (a frame), as specified in http://fastcompression.blogspot.fr/2013/04/lz4-streaming-format-final.html. Although the block level compression and decompression functions are exposed and are fully compatible with the lz4 block format definition, they are low level and should not be used directly. For a complete description of an lz4 compressed block, see: http://fastcompression.blogspot.fr/2011/05/lz4-explained.html See https://github.com/Cyan4973/lz4 for the reference C implementation.

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). If you want to cache your MFA logins, use AuthTypeUsernamePasswordMFA authenticator. To use programmatic access tokens, specify programmatic_access_token. 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 with token, specify oauth and provide an OAuth Access Token (see the token parameter below). To authenticate via full OAuth flow, specify oauth_authorization_code or oauth_client_credentials and fill relevant parameters (oauthClientId, oauthClientSecret, oauthAuthorizationUrl, oauthTokenRequestUrl, oauthRedirectUri, oauthScope). Specify URLs if you want to use external OAuth2 IdP, otherwise Snowflake will be used as a default IdP. If oauthScope is not configured, the role is used (giving session:role:<roleName> scope). For more information, please reach to official Snowflake documentation. application: Identifies your application to Snowflake Support. disableOCSPChecks: 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. insecureMode: deprecated. Use disableOCSPChecks instead. 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. 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{}. You can load the connnection configuration with .toml file format. With two environment variables, `SNOWFLAKE_HOME` (`connections.toml` file directory) and `SNOWFLAKE_DEFAULT_CONNECTION_NAME` (DSN name), the driver will search the config file and load the connection. You can find how to use this connection way at ./cmd/tomlfileconnection or Snowflake doc: https://docs.snowflake.com/en/developer-guide/snowflake-cli-v2/connecting/specify-credentials 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. If you want to define S3 client logging, override S3LoggingMode variable using configuration: https://pkg.go.dev/github.com/aws/aws-sdk-go-v2/aws#ClientLogMode Example: 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. 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. 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 differentiate from semistructured types by having specific schema. In all rows of the table, values must conform to this schema. Example table definition: To retrieve structured objects, follow these steps: 1. Create a struct implementing sql.Scanner interface, example: a) b) Automatic scan goes through all fields in a struct and read object fields. Struct fields have to be public. Embedded structs have to be pointers. Matching name is built using struct field name with first letter lowercase. Additionally, `sf` tag can be added: - first value is always a name of a field in an SQL object - additionally `ignore` parameter can be passed to omit this field 2. Use WithStructuredTypesEnabled context while querying data. 3. Use it in regular scan: See StructuredObject for all available operations including null support, embedding nested structs, etc. Retrieving array of simple types works exactly the same like normal values - using Scan function. You can use WithMapValuesNullable and WithArrayValuesNullable contexts to handle null values in, respectively, maps and arrays of simple types in the database. In that case, sql null types will be used: If you want to scan array of structs, you have to use a helper function ScanArrayOfScanners: Retrieving structured maps is very similar to retrieving arrays: To bind structured objects use: 1. Create a type which implements a StructuredObjectWriter interface, example: a) b) 2. Use an instance as regular bind. 3. If you need to bind nil value, use special syntax: Binding structured arrays are like any other parameter. The only difference is - if you want to insert empty array (not nil but empty), you have to use: 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: You can retrieve data in a columnar format similar to the format a server returns, without transposing them to rows. When working with the arrow columnar format in go driver, ArrowBatch structs are used. These are structs mostly corresponding to data chunks received from the backend. They allow for access to specific arrow.Record structs. An ArrowBatch can exist in a state where the underlying data has not yet been loaded. The data is downloaded and translated only on demand. Translation options are retrieved from a context.Context interface, which is either passed from query context or set by the user using WithContext(ctx) method. In order to access them you must use `WithArrowBatches` context, similar to the following: This returns []*ArrowBatch. ArrowBatch functions: GetRowCount(): Returns the number of rows in the ArrowBatch. Note that this returns 0 if the data has not yet been loaded, irrespective of it’s actual size. WithContext(ctx context.Context): Sets the context of the ArrowBatch to the one provided. Note that the context will not retroactively apply to data that has already been downloaded. For example: will produce the same result in records1 and records2, irrespective of the newly provided ctx. Context worth noting are: -WithArrowBatchesTimestampOption -WithHigherPrecision -WithArrowBatchesUtf8Validation described in more detail later. Fetch(): Returns the underlying records as *[]arrow.Record. When this function is called, the ArrowBatch checks whether the underlying data has already been loaded, and downloads it if not. Limitations: How to handle 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: How to handle 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 WithArrowBatchesUtf8Validation, 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. How to handle higher precision 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. WHen using NUMBERs with non zero scale, the value is returned as an integer type and a scale is provided in record metadata. Example. When we have a 123.45 value that comes from NUMBER(9, 4), it will be represented as 1234500 with scale equal to 4. It is a client responsibility to interpret it correctly. Also - see limitations section above. How to handle JSON responses in Arrow batches: Due to technical limitations Snowflake backend may return JSON even if client expects Arrow. In that case Arrow batches are not available and the error with code ErrNonArrowResponseInArrowBatches is returned. The response is parsed to regular rows. You can read rows in a way described in transform_batches_to_rows.go example. This has a very strong limitation though - this is a very low level API (Go driver API), so there are no conversions ready. All values are returned as strings. Alternative approach is to rerun a query, but without enabling Arrow batches and use a general Go SQL API instead of driver API. It can be optimized by using `WithRequestID`, so backend returns results from cache. 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: To download a file into an in-memory stream (rather than a file) use code similar to the code below. Note: GET statements are not supported for multi-statement queries. 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. Default behaviour is to propagate the potential underlying errors encountered during executing calls associated with the PUT or GET commands to the caller, for increased awareness and easier handling or troubleshooting them. The behaviour is governed by the `RaisePutGetError` flag on `SnowflakeFileTransferOptions` (default: `true`) If you wish to ignore those errors instead, you can set `RaisePutGetError: false`. Example snippet:

Package xz supports the compression and decompression of xz files. It supports version 1.0.4 of the specification without the non-LZMA2 filters. See http://tukaani.org/xz/xz-file-format-1.0.4.txt

Package zipfs provides an implementation of the net/http.FileSystem interface based on the contents of a ZIP file. It also provides the FileServer function, which returns a net/http.Handler that serves static files from a ZIP file. This HTTP handler exploits the fact that most files are stored in a ZIP file using the deflate compression algorithm, and that most HTTP user agents will accept deflate as a content-encoding. When possible the HTTP handler will send the compressed file contents back to the user agent without having to decompress the ZIP file contents.

Package compress is a collection of compression libraries.

Package websocket implements the WebSocket protocol defined in RFC 6455. The Conn type represents a WebSocket connection. A server application calls the Upgrader.Upgrade method from an HTTP request handler to get a *Conn: net/http valyala/fasthttp Call the connection's WriteMessage and ReadMessage methods to send and receive messages as a slice of bytes. This snippet of code shows how to echo messages using these methods: In above snippet of code, p is a []byte and messageType is an int with value websocket.BinaryMessage or websocket.TextMessage. An application can also send and receive messages using the io.WriteCloser and io.Reader interfaces. To send a message, call the connection NextWriter method to get an io.WriteCloser, write the message to the writer and close the writer when done. To receive a message, call the connection NextReader method to get an io.Reader and read until io.EOF is returned. This snippet shows how to echo messages using the NextWriter and NextReader methods: The WebSocket protocol distinguishes between text and binary data messages. Text messages are interpreted as UTF-8 encoded text. The interpretation of binary messages is left to the application. This package uses the TextMessage and BinaryMessage integer constants to identify the two data message types. The ReadMessage and NextReader methods return the type of the received message. The messageType argument to the WriteMessage and NextWriter methods specifies the type of a sent message. It is the application's responsibility to ensure that text messages are valid UTF-8 encoded text. The WebSocket protocol defines three types of control messages: close, ping and pong. Call the connection WriteControl, WriteMessage or NextWriter methods to send a control message to the peer. Connections handle received close messages by calling the handler function set with the SetCloseHandler method and by returning a *CloseError from the NextReader, ReadMessage or the message Read method. The default close handler sends a close message to the peer. Connections handle received ping messages by calling the handler function set with the SetPingHandler method. The default ping handler sends a pong message to the peer. Connections handle received pong messages by calling the handler function set with the SetPongHandler method. The default pong handler does nothing. If an application sends ping messages, then the application should set a pong handler to receive the corresponding pong. The control message handler functions are called from the NextReader, ReadMessage and message reader Read methods. The default close and ping handlers can block these methods for a short time when the handler writes to the connection. The application must read the connection to process close, ping and pong messages sent from the peer. If the application is not otherwise interested in messages from the peer, then the application should start a goroutine to read and discard messages from the peer. A simple example is: Connections support one concurrent reader and one concurrent writer. Applications are responsible for ensuring that no more than one goroutine calls the write methods (NextWriter, SetWriteDeadline, WriteMessage, WriteJSON, EnableWriteCompression, SetCompressionLevel) concurrently and that no more than one goroutine calls the read methods (NextReader, SetReadDeadline, ReadMessage, ReadJSON, SetPongHandler, SetPingHandler) concurrently. The Close and WriteControl methods can be called concurrently with all other methods. Web browsers allow Javascript applications to open a WebSocket connection to any host. It's up to the server to enforce an origin policy using the Origin request header sent by the browser. The Upgrader calls the function specified in the CheckOrigin field to check the origin. If the CheckOrigin function returns false, then the Upgrade method fails the WebSocket handshake with HTTP status 403. If the CheckOrigin field is nil, then the Upgrader uses a safe default: fail the handshake if the Origin request header is present and the Origin host is not equal to the Host request header. The deprecated package-level Upgrade function does not perform origin checking. The application is responsible for checking the Origin header before calling the Upgrade function. Connections buffer network input and output to reduce the number of system calls when reading or writing messages. Write buffers are also used for constructing WebSocket frames. See RFC 6455, Section 5 for a discussion of message framing. A WebSocket frame header is written to the network each time a write buffer is flushed to the network. Decreasing the size of the write buffer can increase the amount of framing overhead on the connection. The buffer sizes in bytes are specified by the ReadBufferSize and WriteBufferSize fields in the Dialer and Upgrader. The Dialer uses a default size of 4096 when a buffer size field is set to zero. The Upgrader reuses buffers created by the HTTP server when a buffer size field is set to zero. The HTTP server buffers have a size of 4096 at the time of this writing. The buffer sizes do not limit the size of a message that can be read or written by a connection. Buffers are held for the lifetime of the connection by default. If the Dialer or Upgrader WriteBufferPool field is set, then a connection holds the write buffer only when writing a message. Applications should tune the buffer sizes to balance memory use and performance. Increasing the buffer size uses more memory, but can reduce the number of system calls to read or write the network. In the case of writing, increasing the buffer size can reduce the number of frame headers written to the network. Some guidelines for setting buffer parameters are: Limit the buffer sizes to the maximum expected message size. Buffers larger than the largest message do not provide any benefit. Depending on the distribution of message sizes, setting the buffer size to a value less than the maximum expected message size can greatly reduce memory use with a small impact on performance. Here's an example: If 99% of the messages are smaller than 256 bytes and the maximum message size is 512 bytes, then a buffer size of 256 bytes will result in 1.01 more system calls than a buffer size of 512 bytes. The memory savings is 50%. A write buffer pool is useful when the application has a modest number writes over a large number of connections. when buffers are pooled, a larger buffer size has a reduced impact on total memory use and has the benefit of reducing system calls and frame overhead. Per message compression extensions (RFC 7692) are experimentally supported by this package in a limited capacity. Setting the EnableCompression option to true in Dialer or Upgrader will attempt to negotiate per message deflate support. If compression was successfully negotiated with the connection's peer, any message received in compressed form will be automatically decompressed. All Read methods will return uncompressed bytes. Per message compression of messages written to a connection can be enabled or disabled by calling the corresponding Conn method: Currently this package does not support compression with "context takeover". This means that messages must be compressed and decompressed in isolation, without retaining sliding window or dictionary state across messages. For more details refer to RFC 7692. Use of compression is experimental and may result in decreased performance.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. This repository will not be maintained, at least for some unknown duration. But it is hoped that gofpdf has a bright future in the open source world. Due to Go’s promise of compatibility, gofpdf should continue to function without modification for a longer time than would be the case with many other languages. Forks should be based on the last viable commit. Tools such as active-forks can be used to select a fork that looks promising for your needs. If a particular fork looks like it has taken the lead in attracting followers, this README will be updated to point people in that direction. The efforts of all contributors to this project have been deeply appreciated. Best wishes to all of you. If you currently use the $GOPATH scheme, install the package with the following command. To test the installation, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package goparquet is an implementation of the parquet file format in Go. It provides functionality to both read and write parquet files, as well as high-level functionality to manage the data schema of parquet files, to directly write Go objects to parquet files using automatic or custom marshalling and to read records from parquet files into Go objects using automatic or custom marshalling. parquet is a file format to store nested data structures in a flat columnar format. By storing in a column-oriented way, it allows for efficient reading of individual columns without having to read and decode complete rows. This allows for efficient reading and faster processing when using the file format in conjunction with distributed data processing frameworks like Apache Hadoop or distributed SQL query engines like Presto and AWS Athena. This particular implementation is divided into several packages. The top-level package that you're currently viewing is the low-level implementation of the file format. It is accompanied by the sub-packages parquetschema and floor. parquetschema provides functionality to parse textual schema definitions as well as the data types to manually or programmatically construct schema definitions by other means that are open to the user. The textual schema definition format is based on the barely documented schema definition format that is implemented in the parquet Java implementation. See the parquetschema sub-package for further documentation on how to use this package and the grammar of the schema definition format as well as examples. floor is a high-level wrapper around the low-level package. It provides functionality to open parquet files to read from them or to write to them. When reading from parquet files, floor takes care of automatically unmarshal the low-level data into the user-provided Go object. When writing to parquet files, user-provided Go objects are first marshalled to a low-level data structure that is then written to the parquet file. These mechanisms allow to directly read and write Go objects without having to deal with the details of the low-level parquet format. Alternatively, marshalling and unmarshalling can be implemented in a custom manner, giving the user maximum flexibility in case of disparities between the parquet schema definition and the actual Go data structure. For more information, please refer to the floor sub-package's documentation. To aid in working with parquet files, this package also provides a commandline tool named "parquet-tool" that allows you to inspect a parquet file's schema, meta data, row count and content as well as to merge and split parquet files. When operating with parquet files, most users should be able to cover their regular use cases of reading and writing files using just the high-level floor package as well as the parquetschema package. Only if a user has more special requirements in how to work with the parquet files, it is advisable to use this low-level package. To write to a parquet file, the type provided by this package is the FileWriter. Create a new *FileWriter object using the NewFileWriter function. You have a number of options available with which you can influence the FileWriter's behaviour. You can use these options to e.g. set meta data, the compression algorithm to use, the schema definition to use, or whether the data should be written in the V2 format. If you didn't set a schema definition, you then need to manually create columns using the functions NewDataColumn, NewListColumn and NewMapColumn, and then add them to the FileWriter by using the AddColumn method. To further structure your data into groups, use AddGroup to create groups. When you add columns to groups, you need to provide the full column name using dotted notation (e.g. "groupname.fieldname") to AddColumn. Using the AddData method, you can then add records. The provided data is of type map[string]interface{}. This data can be nested: to provide data for a repeated field, the data type to use for the map value is []interface{}. When the provided data is a group, the data type for the group itself again needs to be map[string]interface{}. The data within a parquet file is divided into row groups of a certain size. You can either set the desired row group size as a FileWriterOption, or you can manually check the estimated data size of the current row group using the CurrentRowGroupSize method, and use FlushRowGroup to write the data to disk and start a new row group. Please note that CurrentRowGroupSize only estimates the _uncompressed_ data size. If you've enabled compression, it is impossible to predict the compressed data size, so the actual row groups written to disk may be a lot smaller than uncompressed, depending on how efficiently your data can be compressed. When you're done writing, always use the Close method to flush any remaining data and to write the file's footer. To read from files, create a FileReader object using the NewFileReader function. You can optionally provide a list of columns to read. If these are set, only these columns are read from the file, while all other columns are ignored. If no columns are proided, then all columns are read. With the FileReader, you can then go through the row groups (using PreLoad and SkipRowGroup). and iterate through the row data in each row group (using NextRow). To find out how many rows to expect in total and per row group, use the NumRows and RowGroupNumRows methods. The number of row groups can be determined using the RowGroupCount method.

Package jose provides high level functions for producing (signing, encrypting and compressing) or consuming (decoding) Json Web Tokens using Java Object Signing and Encryption spec

go-assets is a simple embedding asset generator and consumer library for go. The main use of the library is to generate and embed small in-memory file systems ready to be integrated in webservers or other services which have a small amount of assets used at runtime. This is great for being able to do single binary deployments with assets. The Generator type can be used to generate a go file containing an in-memory file tree from files and directories on disk. The file data can be optionally compressed using gzip to reduce file size. Afterwards, the generated file can be included into your application and the assets can be directly accessed without having to load them from disk. The generated assets variable is of type FileSystem and implements the os.FileInfo and http.FileSystem interfaces so that they can be directly used with http.FileHandler.

Package archiver facilitates convenient, cross-platform, high-level archival and compression operations for a variety of formats and compression algorithms. This package and its dependencies are written in pure Go (not cgo) and have no external dependencies, so they should run on all major platforms. (It also comes with a command for CLI use in the cmd/arc folder.) Each supported format or algorithm has a unique type definition that implements the interfaces corresponding to the tasks they perform. For example, the Tar type implements Reader, Writer, Archiver, Unarchiver, Walker, and several other interfaces. The most common functions are implemented at the package level for convenience: Archive, Unarchive, Walk, Extract, CompressFile, and DecompressFile. With these, the format type is chosen implicitly, and a sane default configuration is used. To customize a format's configuration, create an instance of its struct with its fields set to the desired values. You can also use and customize the handy Default* (replace the wildcard with the format's type name) for a quick, one-off instance of the format's type. To obtain a new instance of a format's struct with the default config, use the provided New*() functions. This is not required, however. An empty struct of any type, for example &Zip{} is perfectly valid, so you may create the structs manually, too. The examples on this page show how either may be done. See the examples in this package for an idea of how to wield this package for common tasks. Most of the examples which are specific to a certain format type, for example Zip, can be applied to other types that implement the same interfaces. For example, using Zip is very similar to using Tar or TarGz (etc), and using Gz is very similar to using Sz or Xz (etc). When creating archives or compressing files using a specific instance of the format's type, the name of the output file MUST match that of the format, to prevent confusion later on. If you absolutely need a different file extension, you may rename the file afterward. Values in this package are NOT safe for concurrent use. There is no performance benefit of reusing them, and since they may contain important state (especially while walking, reading, or writing), it is NOT recommended to reuse values from this package or change their configuration after they are in use.

Package latlong maps from a latitude and longitude to a timezone. It uses the data from http://efele.net/maps/tz/world/ compressed down to an internal form optimized for low memory overhead and fast lookups at the expense of perfect accuracy when close to borders. The data files are compiled in to this package and do not require explicit loading.

Package vfsgen takes an http.FileSystem (likely at `go generate` time) and generates Go code that statically implements the provided http.FileSystem. Features: - Efficient generated code without unneccessary overhead. - Uses gzip compression internally (selectively, only for files that compress well). - Enables direct access to internal gzip compressed bytes via an optional interface. - Outputs `gofmt`ed Go code. This code will generate an assets_vfsdata.go file with `var assets http.FileSystem = ...` that statically implements the contents of "assets" directory. vfsgen is great to use with go generate directives. This code can go in an assets_gen.go file, which can then be invoked via "//go:generate go run assets_gen.go". The input virtual filesystem can read directly from disk, or it can be more involved.

Package bitio provides an optimized bit-level Reader and Writer. You can use Reader.ReadBits() to read arbitrary number of bits from an io.Reader and return it as an uint64, and Writer.WriteBits() to write arbitrary number of bits of an uint64 value to an io.Writer. Both Reader and Writer also provide optimized methods for reading / writing 1 bit of information in the form of a bool value: Reader.ReadBool() and Writer.WriteBool(). These make this package ideal for compression algorithms that use Huffman coding for example, where decision whether to step left or right in the Huffman tree is the most frequent operation. Reader and Writer give a bit-level view of the underlying io.Reader and io.Writer, but they also provide a byte-level view (io.Reader and io.Writer) at the same time. This means you can also use the Reader.Read() and Writer.Write() methods to read and write slices of bytes. These will give you best performance if the underlying io.Reader and io.Writer are aligned to a byte boundary (else all the individual bytes are assembled from / spread to multiple bytes). You can ensure byte boundary alignment by calling the Align() method of Reader and Writer. As an extra, io.ByteReader and io.ByteWriter are also implemented. The more general highest-bits-first order is used. So for example if the input provides the bytes 0x8f and 0x55: Then ReadBits will return the following values: Writing the above values would result in the same sequence of bytes: All ReadXXX() and WriteXXX() methods return an error which you are expected to handle. For convenience, there are also matching TryReadXXX() and TryWriteXXX() methods which do not return an error. Instead they store the (first) error in the Reader.TryError / Writer.TryError field which you can inspect later. These TryXXX() methods are a no-op if a TryError has been encountered before, so it's safe to call multiple TryXXX() methods and defer the error checking. For example: This allows you to easily convert the result of individual ReadBits(), like this: And similarly: For performance reasons, Reader and Writer do not keep track of the number of read or written bits. If you happen to need the total number of processed bits, you may use the CountReader and CountWriter types which have identical API to that of Reader and Writer, but they also maintain the number of processed bits which you can query using the BitsCount field.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package lz4 implements compression using lz4.c and lz4hc.c Copyright (c) 2013 CloudFlare, Inc.

Package datadog-api-client-go. This repository contains a Go API client for the Datadog API (https://docs.datadoghq.com/api/). • Go 1.22+ This repository contains per-major-version API client packages. Right now, Datadog has two API versions, v1, v2 and the common package. The client library for Datadog API v1 is located in the api/datadogV1 directory. Import it with The client library for Datadog API v2 is located in the api/datadogV2 directory. Import it with The datadog package for Datadog API is located in the api/datadog directory. Import it with Here's an example creating a user: Save it to example.go, then run go get github.com/DataDog/datadog-api-client-go/v2. Set the DD_CLIENT_API_KEY and DD_CLIENT_APP_KEY to your Datadog credentials, and then run go run example.go. This client includes access to Datadog API endpoints while they are in an unstable state and may undergo breaking changes. An extra configuration step is required to enable these endpoints: where <OperationName> is the name of the method used to interact with that endpoint. For example: GetLogsIndex, or UpdateLogsIndex When talking to a different server, like the eu instance, change the ContextServerVariables: If you want to disable GZIP compressed responses, set the compress flag on your configuration object: If you want to enable requests logging, set the debug flag on your configuration object: If you want to enable retry when getting status code 429 rate-limited or 5xx, set EnableRetry to true The default max retry is 3, you can change it with MaxRetries If you want to configure proxy, set env var HTTP_PROXY, and HTTPS_PROXY or set custom HTTPClient with proxy configured on configuration object: Several listing operations have a pagination method to help consume all the items available. For example, to retrieve all your incidents: Encoder/Decoder By default, datadog-api-client-go uses the Go standard library enconding/json (https://pkg.go.dev/encoding/json) to encode and decode data. As an alternative users can opt in to use goccy/go-json (https://github.com/goccy/go-json) by specifying the go build tag goccy_gojson. In comparison, there was a significant decrease in cpu time with goccy/go-json with an increase in memory overhead. For further benchmark information, see goccy/go-json benchmark (https://github.com/goccy/go-json#benchmarks) section. Developer documentation for API endpoints and models is available on Github pages (https://datadoghq.dev/datadog-api-client-go/pkg/github.com/DataDog/datadog-api-client-go/v2/). Released versions are available on pkg.go.dev (https://pkg.go.dev/github.com/DataDog/datadog-api-client-go/v2). As most of the code in this repository is generated, we will only accept PRs for files that are not modified by our code-generation machinery (changes to the generated files would get overwritten). We happily accept contributions to files that are not autogenerated, such as tests and development tooling. support@datadoghq.com

Package lilliput resizes and encodes images from compressed images

Package fpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates go-pdf/fpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. go-pdf/fpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the go-pdf/fpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the go-pdf/fpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.SummaryCompare() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package restful , a lean package for creating REST-style WebServices without magic. A WebService has a collection of Route objects that dispatch incoming Http Requests to a function calls. Typically, a WebService has a root path (e.g. /users) and defines common MIME types for its routes. WebServices must be added to a container (see below) in order to handler Http requests from a server. A Route is defined by a HTTP method, an URL path and (optionally) the MIME types it consumes (Content-Type) and produces (Accept). This package has the logic to find the best matching Route and if found, call its Function. The (*Request, *Response) arguments provide functions for reading information from the request and writing information back to the response. See the example https://github.com/emicklei/go-restful/blob/master/examples/restful-user-resource.go with a full implementation. A Route parameter can be specified using the format "uri/{var[:regexp]}" or the special version "uri/{var:*}" for matching the tail of the path. For example, /persons/{name:[A-Z][A-Z]} can be used to restrict values for the parameter "name" to only contain capital alphabetic characters. Regular expressions must use the standard Go syntax as described in the regexp package. (https://code.google.com/p/re2/wiki/Syntax) This feature requires the use of a CurlyRouter. A Container holds a collection of WebServices, Filters and a http.ServeMux for multiplexing http requests. Using the statements "restful.Add(...) and restful.Filter(...)" will register WebServices and Filters to the Default Container. The Default container of go-restful uses the http.DefaultServeMux. You can create your own Container and create a new http.Server for that particular container. A filter dynamically intercepts requests and responses to transform or use the information contained in the requests or responses. You can use filters to perform generic logging, measurement, authentication, redirect, set response headers etc. In the restful package there are three hooks into the request,response flow where filters can be added. Each filter must define a FilterFunction: Use the following statement to pass the request,response pair to the next filter or RouteFunction These are processed before any registered WebService. These are processed before any Route of a WebService. These are processed before calling the function associated with the Route. See the example https://github.com/emicklei/go-restful/blob/master/examples/restful-filters.go with full implementations. Two encodings are supported: gzip and deflate. To enable this for all responses: If a Http request includes the Accept-Encoding header then the response content will be compressed using the specified encoding. Alternatively, you can create a Filter that performs the encoding and install it per WebService or Route. See the example https://github.com/emicklei/go-restful/blob/master/examples/restful-encoding-filter.go By installing a pre-defined container filter, your Webservice(s) can respond to the OPTIONS Http request. By installing the filter of a CrossOriginResourceSharing (CORS), your WebService(s) can handle CORS requests. Unexpected things happen. If a request cannot be processed because of a failure, your service needs to tell via the response what happened and why. For this reason HTTP status codes exist and it is important to use the correct code in every exceptional situation. If path or query parameters are not valid (content or type) then use http.StatusBadRequest. Despite a valid URI, the resource requested may not be available If the application logic could not process the request (or write the response) then use http.StatusInternalServerError. The request has a valid URL but the method (GET,PUT,POST,...) is not allowed. The request does not have or has an unknown Accept Header set for this operation. The request does not have or has an unknown Content-Type Header set for this operation. In addition to setting the correct (error) Http status code, you can choose to write a ServiceError message on the response. This package has several options that affect the performance of your service. It is important to understand them and how you can change it. DoNotRecover controls whether panics will be caught to return HTTP 500. If set to false, the container will recover from panics. Default value is true If content encoding is enabled then the default strategy for getting new gzip/zlib writers and readers is to use a sync.Pool. Because writers are expensive structures, performance is even more improved when using a preloaded cache. You can also inject your own implementation. This package has the means to produce detail logging of the complete Http request matching process and filter invocation. Enabling this feature requires you to set an implementation of restful.StdLogger (e.g. log.Logger) instance such as: The restful.SetLogger() method allows you to override the logger used by the package. By default restful uses the standard library `log` package and logs to stdout. Different logging packages are supported as long as they conform to `StdLogger` interface defined in the `log` sub-package, writing an adapter for your preferred package is simple. (c) 2012-2015, http://ernestmicklei.com. MIT License

Package tsz implement time-series compression http://www.vldb.org/pvldb/vol8/p1816-teller.pdf

Package compression implements various compression mechanisms

Package bindata converts any file into manageable Go source code. Useful for embedding binary data into a go program. The file data is optionally gzip compressed before being converted to a raw byte slice. The following paragraphs cover some of the customization options which can be specified in the Config struct, which must be passed into the Translate() call. When used with the `Debug` option, the generated code does not actually include the asset data. Instead, it generates function stubs which load the data from the original file on disk. The asset API remains identical between debug and release builds, so your code will not have to change. This is useful during development when you expect the assets to change often. The host application using these assets uses the same API in both cases and will not have to care where the actual data comes from. An example is a Go webserver with some embedded, static web content like HTML, JS and CSS files. While developing it, you do not want to rebuild the whole server and restart it every time you make a change to a bit of javascript. You just want to build and launch the server once. Then just press refresh in the browser to see those changes. Embedding the assets with the `debug` flag allows you to do just that. When you are finished developing and ready for deployment, just re-invoke `go-bindata` without the `-debug` flag. It will now embed the latest version of the assets. The `NoMemCopy` option will alter the way the output file is generated. It will employ a hack that allows us to read the file data directly from the compiled program's `.rodata` section. This ensures that when we call call our generated function, we omit unnecessary memcopies. The downside of this, is that it requires dependencies on the `reflect` and `unsafe` packages. These may be restricted on platforms like AppEngine and thus prevent you from using this mode. Another disadvantage is that the byte slice we create, is strictly read-only. For most use-cases this is not a problem, but if you ever try to alter the returned byte slice, a runtime panic is thrown. Use this mode only on target platforms where memory constraints are an issue. The default behaviour is to use the old code generation method. This prevents the two previously mentioned issues, but will employ at least one extra memcopy and thus increase memory requirements. For instance, consider the following two examples: This would be the default mode, using an extra memcopy but gives a safe implementation without dependencies on `reflect` and `unsafe`: Here is the same functionality, but uses the `.rodata` hack. The byte slice returned from this example can not be written to without generating a runtime error. The NoCompress option indicates that the supplied assets are *not* GZIP compressed before being turned into Go code. The data should still be accessed through a function call, so nothing changes in the API. This feature is useful if you do not care for compression, or the supplied resource is already compressed. Doing it again would not add any value and may even increase the size of the data. The default behaviour of the program is to use compression. The keys used in the `_bindata` map are the same as the input file name passed to `go-bindata`. This includes the path. In most cases, this is not desirable, as it puts potentially sensitive information in your code base. For this purpose, the tool supplies another command line flag `-prefix`. This accepts a [regular expression](https://github.com/google/re2/wiki/Syntax) string, which will be used to match a portion of the map keys and function names that should be stripped out. For example, running without the `-prefix` flag, we get: Running with the `-prefix` flag, we get: With the optional Tags field, you can specify any go build tags that must be fulfilled for the output file to be included in a build. This is useful when including binary data in multiple formats, where the desired format is specified at build time with the appropriate tags. The tags are appended to a `// +build` line in the beginning of the output file and must follow the build tags syntax specified by the go tool. When you want to embed big files or plenty of files, then the generated output is really big (maybe over 3Mo). Even if the generated file shouldn't be read, you probably need use analysis tool or an editor which can become slower with a such file. Generating big files can be avoided with `-split` command line option. In that case, the given output is a directory path, the tool will generate one source file per file to embed, and it will generate a common file nammed `common.go` which contains commons parts like API.

Package sparse provides implementations of selected sparse matrix formats. Matrices and linear algebra are used extensively in scientific computing and machine learning applications. Large datasets are analysed comprising vectors of numerical features that represent some object. The nature of feature encoding schemes, especially those like "one hot", tends to lead to vectors with mostly zero values for many of the features. In text mining applications, where features are typically terms from a vocabulary, it is not uncommon for 99% of the elements within these vectors to contain zero values. Sparse matrix formats take advantage of this fact to optimise memory usage and processing performance by only storing and processing non-zero values. Sparse matrix formats can broadly be divided into 3 main categories: 1. Creational - Sparse matrix formats suited to construction and building of matrices. Matrix formats in this category include DOK (Dictionary Of Keys) and COO (COOrdinate aka triplet). 2. Operational - Sparse matrix formats suited to arithmetic operations e.g. multiplication. Matrix formats in this category include CSR (Compressed Sparse Row aka CRS - Compressed Row Storage) and CSC (Compressed Sparse Column aka CCS - Compressed Column Storage) 3. Specialised - Specialised matrix formats suiting specific sparsity patterns. Matrix formats in this category include DIA (DIAgonal) for efficiently storing and manipulating symmetric diagonal matrices. A common practice is to construct sparse matrices using a creational format e.g. DOK or COO and then convert them to an operational format e.g. CSR for arithmetic operations. All sparse matrix implementations in this package implement the Matrix interface defined within the gonum/mat package and so may be used interchangeably with matrix types defined within the package e.g. mat.Dense, mat.VecDense, etc.

Package grpchan provides an abstraction for a gRPC transport, called a Channel. The channel is more general than the concrete *grpc.ClientConn and *grpc.Server types provided by gRPC. It allows gRPC over alternate substrates and includes sub-packages that provide two such alternatives: in-process and HTTP 1.1. The key type in this package is an alternate implementation of grpc.ServiceRegistrar interface that allows you to accumulate service registrations, for use with an implementation other than *grpc.Server. This repo also includes a deprecated protoc plugin. This is no longer needed now that the standard protoc-gen-go-grpc plugin generates code that uses interfaces: grpc.ClientConnInterface and grpc.ServiceRegistrar. In older versions, the generated code only supported concrete types (*grpc.ClientConn and *grpc.Server) so this repo's protoc plugin would generate alternate code that used interfaces (and thus supported other concrete implementations). Continued use of the plugin is only to continue supporting code that uses the functions generated by it. To use the protoc plugin, you need to first build it and make sure its location is in your PATH. When you invoke protoc, include a --grpchan_out parameter that indicates the same output directory as used for your --go_out parameter. Alongside the *.pb.go files generated, the grpchan plugin will also create *.pb.grpchan.go files. In older versions of the Go plugin (when emitting gRPC code), a server registration function for each RPC service defined in the proto source files was generated that looked like so: The grpchan plugin produces a similarly named method that accepts the ServiceRegistry interface: A new transport can then be implemented by just implementing two interfaces: grpc.ClientConnInterface for the client side and grpchan.ServiceRegistry for the server side. The alternate method also works just fine with *grpc.Server as it implements the ServiceRegistry interface. NOTE: If your have code relying on New<ServiceName>ChannelClient methods that earlier versions of this package produced, they can still be generated by passing a "legacy_stubs" option to the plugin. Example: The client-side implementation of a transport is done with just the two methods in grpc.ClientConnInterface: one for unary RPCs and the other for streaming RPCs. Note that when a unary interceptor is invoked for an RPC on a channel that is *not* a *grpc.ClientConn, the parameter of that type will be nil. Not all client call options will make sense for all transports. This repo chooses to ignore call options that do not apply (as opposed to failing the RPC or panicking). However, several call options are likely important to support: those for accessing header and trailer metadata. The peer, per-RPC credentials, and message size limits are other options that are reasonably straight-forward to apply to other transports. But the other options (dealing with on-the-wire encoding, compression, etc) may not be applicable. The server-side implementation of a transport must be able to invoke method and stream handlers for a given service implementation. This is done by implementing the grpc.ServiceRegistrar interface. When a service is registered, a service description is provided that includes access to method and stream handlers. When the transport receives requests for RPC operations, it in turn invokes these handlers. For streaming operations, it must also supply a grpc.ServerStream implementation, for exchanging messages on the stream. Note that the server stream's context will need a custom implementation of the grpc.ServerTransportStream in it, too. Sadly, this interface is just different enough from grpc.ServerStream that they cannot be implemented by the same type. This is particularly necessary for unary calls since this is how a unary handler indicates what headers and trailers to send back to the client.

Package readahead provides readers which enable concurrent read from seekable or compressed files. It's useful when reading from a network file system (like Google Cloud Storage).

Package rpm implements the rpm package file format. For more information about the rpm file format, see: http://ftp.rpm.org/max-rpm/s1-rpm-file-format-rpm-file-format.html Packages are composed of two headers: the Signature header and the "Header" header. Each contains key-value pairs called tags. Tags map an integer key to a value whose data type will be one of the TagType types. Tag values can be decoded with the appropriate Tag method for the data type. Many known tags are available as Package methods. For example, RPMTAG_NAME and RPMTAG_BUILDTIME are available as Package.Name and Package.BuildTime respectively. Tags can be retrieved and decoded from the Signature or Header headers directly using Header.GetTag and their tag identifier. Header.GetTag and all Tag methods will return a zero value if the header or the tag do not exist, or if the tag has a different data type. You may enumerate all tags in a header with Header.Tags: In the rpm ecosystem, package versions are compared using EVR; epoch, version, release. Versions may be compared using the Compare function. Packages may be be sorted using the PackageSlice type which implements sort.Interface. Packages are sorted lexically by name ascending and then by version descending. Version is evaluated first by epoch, then by version string, then by release. The Sort function is provided for your convenience. Packages may be validated using MD5Check or GPGCheck. See the example for each function. The payload of an rpm package is typically archived in cpio format and compressed with xz. To decompress and unarchive an rpm payload, the reader that read the rpm package headers will be positioned at the beginning of the payload and can be reused with the appropriate Go packages for the rpm payload format. You can check the archive format with Package.PayloadFormat and the compression algorithm with Package.PayloadCompression. For the cpio archive format, the following package is recommended: https://github.com/cavaliergopher/cpio For xz compression, the following package is recommended: https://github.com/ulikunitz/xz See README.md for a working example of extracting files from a cpio/xz rpm package using these packages. See cmd/rpmdump and cmd/rpminfo for example programs that emulate tools from the rpm ecosystem.

bindata converts any file into managable Go source code. Useful for embedding binary data into a go program. The file data is optionally gzip compressed before being converted to a raw byte slice. The following paragraphs cover some of the customization options which can be specified in the Config struct, which must be passed into the Translate() call. When used with the `Debug` option, the generated code does not actually include the asset data. Instead, it generates function stubs which load the data from the original file on disk. The asset API remains identical between debug and release builds, so your code will not have to change. This is useful during development when you expect the assets to change often. The host application using these assets uses the same API in both cases and will not have to care where the actual data comes from. An example is a Go webserver with some embedded, static web content like HTML, JS and CSS files. While developing it, you do not want to rebuild the whole server and restart it every time you make a change to a bit of javascript. You just want to build and launch the server once. Then just press refresh in the browser to see those changes. Embedding the assets with the `debug` flag allows you to do just that. When you are finished developing and ready for deployment, just re-invoke `go-bindata` without the `-debug` flag. It will now embed the latest version of the assets. The `NoMemCopy` option will alter the way the output file is generated. It will employ a hack that allows us to read the file data directly from the compiled program's `.rodata` section. This ensures that when we call call our generated function, we omit unnecessary memcopies. The downside of this, is that it requires dependencies on the `reflect` and `unsafe` packages. These may be restricted on platforms like AppEngine and thus prevent you from using this mode. Another disadvantage is that the byte slice we create, is strictly read-only. For most use-cases this is not a problem, but if you ever try to alter the returned byte slice, a runtime panic is thrown. Use this mode only on target platforms where memory constraints are an issue. The default behaviour is to use the old code generation method. This prevents the two previously mentioned issues, but will employ at least one extra memcopy and thus increase memory requirements. For instance, consider the following two examples: This would be the default mode, using an extra memcopy but gives a safe implementation without dependencies on `reflect` and `unsafe`: Here is the same functionality, but uses the `.rodata` hack. The byte slice returned from this example can not be written to without generating a runtime error. The NoCompress option indicates that the supplied assets are *not* GZIP compressed before being turned into Go code. The data should still be accessed through a function call, so nothing changes in the API. This feature is useful if you do not care for compression, or the supplied resource is already compressed. Doing it again would not add any value and may even increase the size of the data. The default behaviour of the program is to use compression. The keys used in the `_bindata` map are the same as the input file name passed to `go-bindata`. This includes the path. In most cases, this is not desireable, as it puts potentially sensitive information in your code base. For this purpose, the tool supplies another command line flag `-prefix`. This accepts a portion of a path name, which should be stripped off from the map keys and function names. For example, running without the `-prefix` flag, we get: Running with the `-prefix` flag, we get: With the optional Tags field, you can specify any go build tags that must be fulfilled for the output file to be included in a build. This is useful when including binary data in multiple formats, where the desired format is specified at build time with the appropriate tags. The tags are appended to a `// +build` line in the beginning of the output file and must follow the build tags syntax specified by the go tool.

Package fs implements virtual file system access for compressed files.

Package mph is a Go implementation of the compress, hash and displace (CHD) minimal perfect hash algorithm. See http://cmph.sourceforge.net/papers/esa09.pdf for details. To create and serialize a hash table: To read from the hash table: MMAP is also indirectly supported, by deserializing from a byte slice and slicing the keys and values. See https://github.com/alecthomas/mph for source.

Package capn is a capnproto library for go see http://kentonv.github.io/capnproto/ capnpc-go provides the compiler backend for capnp after installing to $PATH capnp files can be compiled with capnpc-go requires two annotations for all types. This is the package and import found in go.capnp. Package is needed to know what package to place at the head of the generated file and what go name to use when referring to the type from another package. Import should be the fully qualified import path and is used to generate import statement from other packages and to detect when two types are in the same package. Typically these are added as file annotations. For example: In capnproto, the unit of communication is a message. A message consists of one or more of segments to allow easier allocation, but ideally and typically you just make one segment per message. Logically, a message organized in a tree of objects, with the root always being a struct (as opposed to a list or primitive). Here is an example of writing a new message. We use the demo schema aircraft.capnp from the aircraftlib directory. You may wish to read the schema before reading this example. << Example moved to its own file: See the file, write_test.go >> In summary, when you make a new message, you should first make new segment, and then create the root struct in that segment. Then add your non-child (contained) objects. This is because, as the spec says: All objects are values with pointer semantics that point into the data in a message or segment. Messages can be read/written from a stream uncompressed or using the capnproto compression. In this library a *Segment is taken to refer to both a specific segment as well as the containing message. This is to reduce the number of types generic code needs to deal with and allows objects to be created in the same segment as their outer object (thus reducing the number of far pointers). Most getters/setters in the library don't return an error. Instead a get that fails due to an invalid pointer, out of bounds, etc will return the default value. A invalid set will be noop'ed. If you really need to know whether a set succeeds then errors are provided by the lower level Object methods. Since go doesn't have any templating, lists are created for the basic types and one level of named types. The list of basic types (e.g. List(UInt8), List(Text), etc) are all provided in this library. Lists of user named types are created with the user types (e.g. user struct Foo will create a Foo_List type). capnp schemas that use deeper lists (e.g. List(List(UInt8))) will use PointerList and the user will have to use the Object.ToList* functions to cast to the correct type. For adding documentation comments to the generated code, there's the doc annotation. This annotation adds the comment to a struct, enum or field so that godoc will pick it up. For Example: capnpc-go will generate the following for structs: For each group a typedef is created with a different method set for just the groups fields: That way the following may be used to access a field in a group: Note that Group accessors just cast the type and so have no overhead Named unions are treated as a group with an inner unnamed union. Unnamed unions generate an enum Type_Which and a corresponding Which() function: Which() should be checked before using the getters, and the default case must always be handled. Setters for single values will set the union discriminator as well as set the value. For voids in unions, there is a void setter that just sets the discriminator. For example: For groups in unions, there is a group setter that just sets the discriminator. This must be called before the group getter can be used to set values. For example: capnpc-go generates enum values in all caps. For example in the capnp file: In the generated capnp.go file: In addition an enum.String() function is generated that will convert the constants to a string for debugging or logging purposes. By default, the enum name is used as the tag value, but the tags can be customized with a $Go.tag or $Go.notag annotation. For example: In the generated go file:

Package cae implements PHP-like Compression and Archive Extensions.

Package basex provides fast base encoding / decoding of any given alphabet using bitcoin style leading zero compression. It is a GO port of https://github.com/cryptocoinjs/base-x

Package xz supports the compression and decompression of xz files. It supports version 1.0.4 of the specification without the non-LZMA2 filters. See http://tukaani.org/xz/xz-file-format-1.0.4.txt

Package archive contains traversal utilities for ZIP and tar archives with gzip, bzip2, xz, and LZ4 compression.

Package metrics contains the serializer compression component for metrics