Text Inputs

Package regexp implements regular expression search. The syntax of the regular expressions accepted is the same general syntax used by Perl, Python, and other languages. More precisely, it is the syntax accepted by RE2 and described at https://golang.org/s/re2syntax, except for \C. For an overview of the syntax, see the regexp/syntax package. The regexp implementation provided by this package is guaranteed to run in time linear in the size of the input. (This is a property not guaranteed by most open source implementations of regular expressions.) For more information about this property, see https://swtch.com/~rsc/regexp/regexp1.html or any book about automata theory. All characters are UTF-8-encoded code points. Following utf8.DecodeRune, each byte of an invalid UTF-8 sequence is treated as if it encoded utf8.RuneError (U+FFFD). There are 16 methods of Regexp that match a regular expression and identify the matched text. Their names are matched by this regular expression: If 'All' is present, the routine matches successive non-overlapping matches of the entire expression. Empty matches abutting a preceding match are ignored. The return value is a slice containing the successive return values of the corresponding non-'All' routine. These routines take an extra integer argument, n. If n >= 0, the function returns at most n matches/submatches; otherwise, it returns all of them. If 'String' is present, the argument is a string; otherwise it is a slice of bytes; return values are adjusted as appropriate. If 'Submatch' is present, the return value is a slice identifying the successive submatches of the expression. Submatches are matches of parenthesized subexpressions (also known as capturing groups) within the regular expression, numbered from left to right in order of opening parenthesis. Submatch 0 is the match of the entire expression, submatch 1 is the match of the first parenthesized subexpression, and so on. If 'Index' is present, matches and submatches are identified by byte index pairs within the input string: result[2*n:2*n+2] identifies the indexes of the nth submatch. The pair for n==0 identifies the match of the entire expression. If 'Index' is not present, the match is identified by the text of the match/submatch. If an index is negative or text is nil, it means that subexpression did not match any string in the input. For 'String' versions an empty string means either no match or an empty match. There is also a subset of the methods that can be applied to text read from an io.RuneReader: Regexp.MatchReader, Regexp.FindReaderIndex, Regexp.FindReaderSubmatchIndex. This set may grow. Note that regular expression matches may need to examine text beyond the text returned by a match, so the methods that match text from an io.RuneReader may read arbitrarily far into the input before returning. (There are a few other methods that do not match this pattern.)

Package ogdl is used to process OGDL, the Ordered Graph Data Language. OGDL is a textual format to write trees or graphs of text, where indentation and spaces define the structure. Here is an example: The languange is simple, either in its textual representation or its number of productions (the specification rules), allowing for compact implementations. OGDL character streams are normally formed by Unicode characters, and encoded as UTF-8 strings, but any encoding that is ASCII transparent is compatible with the specification. See the full spec at http://ogdl.org. To install this package just do: If we have a text file 'config.ogdl' containing: then, will print If the timeout parameter was not present, then the default value (60) will be assigned to 'to'. The default value is optional, but be aware that Int64() will return 0 in case that the parameter doesn't exist. The configuration file can be written in a conciser way: The package includes a template processor. It takes an arbitrary input stream with some variables in it, and produces an output stream with the variables resolved out of a Graph object which acts as context. For example (given the previous config file): string(b) is then: Some rules are followed:

Package tabwriter implements a write filter (tabwriter.Writer) that translates tabbed columns in input into properly aligned text. It is a drop-in replacement for the golang text/tabwriter package (https://golang.org/pkg/text/tabwriter), based on that package at https://github.com/golang/go/tree/cf2c2ea89d09d486bb018b1817c5874388038c3a with support for additional features. The package is using the Elastic Tabstops algorithm described at http://nickgravgaard.com/elastictabstops/index.html.

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: 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 json implements semantic processing of JSON as specified in RFC 8259. JSON is a simple data interchange format that can represent primitive data types such as booleans, strings, and numbers, in addition to structured data types such as objects and arrays. Marshal and Unmarshal encode and decode Go values to/from JSON text contained within a []byte. MarshalWrite and UnmarshalRead operate on JSON text by writing to or reading from an io.Writer or io.Reader. MarshalEncode and UnmarshalDecode operate on JSON text by encoding to or decoding from a jsontext.Encoder or jsontext.Decoder. Options may be passed to each of the marshal or unmarshal functions to configure the semantic behavior of marshaling and unmarshaling (i.e., alter how JSON data is understood as Go data and vice versa). jsontext.Options may also be passed to the marshal or unmarshal functions to configure the syntactic behavior of encoding or decoding. The data types of JSON are mapped to/from the data types of Go based on the closest logical equivalent between the two type systems. For example, a JSON boolean corresponds with a Go bool, a JSON string corresponds with a Go string, a JSON number corresponds with a Go int, uint or float, a JSON array corresponds with a Go slice or array, and a JSON object corresponds with a Go struct or map. See the documentation on Marshal and Unmarshal for a comprehensive list of how the JSON and Go type systems correspond. Arbitrary Go types can customize their JSON representation by implementing Marshaler, MarshalerTo, Unmarshaler, or UnmarshalerFrom. This provides authors of Go types with control over how their types are serialized as JSON. Alternatively, users can implement functions that match MarshalFunc, MarshalToFunc, UnmarshalFunc, or UnmarshalFromFunc to specify the JSON representation for arbitrary types. This provides callers of JSON functionality with control over how any arbitrary type is serialized as JSON. A Go struct is naturally represented as a JSON object, where each Go struct field corresponds with a JSON object member. When marshaling, all Go struct fields are recursively encoded in depth-first order as JSON object members except those that are ignored or omitted. When unmarshaling, JSON object members are recursively decoded into the corresponding Go struct fields. Object members that do not match any struct fields, also known as “unknown members”, are ignored by default or rejected if RejectUnknownMembers is specified. The representation of each struct field can be customized in the "json" struct field tag, where the tag is a comma separated list of options. As a special case, if the entire tag is `json:"-"`, then the field is ignored with regard to its JSON representation. Some options also have equivalent behavior controlled by a caller-specified Options. Field-specified options take precedence over caller-specified options. The first option is the JSON object name override for the Go struct field. If the name is not specified, then the Go struct field name is used as the JSON object name. JSON names containing commas or quotes, or names identical to "" or "-", can be specified using a single-quoted string literal, where the syntax is identical to the Go grammar for a double-quoted string literal, but instead uses single quotes as the delimiters. By default, unmarshaling uses case-sensitive matching to identify the Go struct field associated with a JSON object name. After the name, the following tag options are supported: omitzero: When marshaling, the "omitzero" option specifies that the struct field should be omitted if the field value is zero as determined by the "IsZero() bool" method if present, otherwise based on whether the field is the zero Go value. This option has no effect when unmarshaling. omitempty: When marshaling, the "omitempty" option specifies that the struct field should be omitted if the field value would have been encoded as a JSON null, empty string, empty object, or empty array. This option has no effect when unmarshaling. string: The "string" option specifies that StringifyNumbers be set when marshaling or unmarshaling a struct field value. This causes numeric types to be encoded as a JSON number within a JSON string, and to be decoded from a JSON string containing the JSON number without any surrounding whitespace. This extra level of encoding is often necessary since many JSON parsers cannot precisely represent 64-bit integers. case: When unmarshaling, the "case" option specifies how JSON object names are matched with the JSON name for Go struct fields. The option is a key-value pair specified as "case:value" where the value must either be 'ignore' or 'strict'. The 'ignore' value specifies that matching is case-insensitive where dashes and underscores are also ignored. If multiple fields match, the first declared field in breadth-first order takes precedence. The 'strict' value specifies that matching is case-sensitive. This takes precedence over the MatchCaseInsensitiveNames option. inline: The "inline" option specifies that the JSON representable content of this field type is to be promoted as if they were specified in the parent struct. It is the JSON equivalent of Go struct embedding. A Go embedded field is implicitly inlined unless an explicit JSON name is specified. The inlined field must be a Go struct (that does not implement any JSON methods), jsontext.Value, map[~string]T, or an unnamed pointer to such types. When marshaling, inlined fields from a pointer type are omitted if it is nil. Inlined fields of type jsontext.Value and map[~string]T are called “inlined fallbacks” as they can represent all possible JSON object members not directly handled by the parent struct. Only one inlined fallback field may be specified in a struct, while many non-fallback fields may be specified. This option must not be specified with any other option (including the JSON name). unknown: The "unknown" option is a specialized variant of the inlined fallback to indicate that this Go struct field contains any number of unknown JSON object members. The field type must be a jsontext.Value, map[~string]T, or an unnamed pointer to such types. If DiscardUnknownMembers is specified when marshaling, the contents of this field are ignored. If RejectUnknownMembers is specified when unmarshaling, any unknown object members are rejected regardless of whether an inlined fallback with the "unknown" option exists. This option must not be specified with any other option (including the JSON name). format: The "format" option specifies a format flag used to specialize the formatting of the field value. The option is a key-value pair specified as "format:value" where the value must be either a literal consisting of letters and numbers (e.g., "format:RFC3339") or a single-quoted string literal (e.g., "format:'2006-01-02'"). The interpretation of the format flag is determined by the struct field type. The "omitzero" and "omitempty" options are mostly semantically identical. The former is defined in terms of the Go type system, while the latter in terms of the JSON type system. Consequently they behave differently in some circumstances. For example, only a nil slice or map is omitted under "omitzero", while an empty slice or map is omitted under "omitempty" regardless of nilness. The "omitzero" option is useful for types with a well-defined zero value (e.g., net/netip.Addr) or have an IsZero method (e.g., time.Time.IsZero). Every Go struct corresponds to a list of JSON representable fields which is constructed by performing a breadth-first search over all struct fields (excluding unexported or ignored fields), where the search recursively descends into inlined structs. The set of non-inlined fields in a struct must have unique JSON names. If multiple fields all have the same JSON name, then the one at shallowest depth takes precedence and the other fields at deeper depths are excluded from the list of JSON representable fields. If multiple fields at the shallowest depth have the same JSON name, but exactly one is explicitly tagged with a JSON name, then that field takes precedence and all others are excluded from the list. This is analogous to Go visibility rules for struct field selection with embedded struct types. Marshaling or unmarshaling a non-empty struct without any JSON representable fields results in a SemanticError. Unexported fields must not have any `json` tags except for `json:"-"`. JSON is frequently used as a data interchange format to communicate between different systems, possibly implemented in different languages. For interoperability and security reasons, it is important that all implementations agree upon the semantic meaning of the data. For example, suppose we have two micro-services. The first service is responsible for authenticating a JSON request, while the second service is responsible for executing the request (having assumed that the prior service authenticated the request). If an attacker were able to maliciously craft a JSON request such that both services believe that the same request is from different users, it could bypass the authenticator with valid credentials for one user, but maliciously perform an action on behalf of a different user. According to RFC 8259, there unfortunately exist many JSON texts that are syntactically valid but semantically ambiguous. For example, the standard does not define how to interpret duplicate names within an object. The v1 encoding/json and encoding/json/v2 packages interpret some inputs in different ways. In particular: The standard specifies that JSON must be encoded using UTF-8. By default, v1 replaces invalid bytes of UTF-8 in JSON strings with the Unicode replacement character, while v2 rejects inputs with invalid UTF-8. To change the default, specify the jsontext.AllowInvalidUTF8 option. The replacement of invalid UTF-8 is a form of data corruption that alters the precise meaning of strings. The standard does not specify a particular behavior when duplicate names are encountered within a JSON object, which means that different implementations may behave differently. By default, v1 allows for the presence of duplicate names, while v2 rejects duplicate names. To change the default, specify the jsontext.AllowDuplicateNames option. If allowed, object members are processed in the order they are observed, meaning that later values will replace or be merged into prior values, depending on the Go value type. The standard defines a JSON object as an unordered collection of name/value pairs. While ordering can be observed through the underlying jsontext API, both v1 and v2 generally avoid exposing the ordering. No application should semantically depend on the order of object members. Allowing duplicate names is a vector through which ordering of members can accidentally be observed and depended upon. The standard suggests that JSON object names are typically compared based on equality of the sequence of Unicode code points, which implies that comparing names is often case-sensitive. When unmarshaling a JSON object into a Go struct, by default, v1 uses a (loose) case-insensitive match on the name, while v2 uses a (strict) case-sensitive match on the name. To change the default, specify the MatchCaseInsensitiveNames option. The use of case-insensitive matching provides another vector through which duplicate names can occur. Allowing case-insensitive matching means that v1 or v2 might interpret JSON objects differently from most other JSON implementations (which typically use a case-sensitive match). The standard does not specify a particular behavior when an unknown name in a JSON object is encountered. When unmarshaling a JSON object into a Go struct, by default both v1 and v2 ignore unknown names and their corresponding values. To change the default, specify the RejectUnknownMembers option. The standard suggests that implementations may use a float64 to represent a JSON number. Consequently, large JSON integers may lose precision when stored as a floating-point type. Both v1 and v2 correctly preserve precision when marshaling and unmarshaling a concrete integer type. However, even if v1 and v2 preserve precision for concrete types, other JSON implementations may not be able to preserve precision for outputs produced by v1 or v2. The `string` tag option can be used to specify that an integer type is to be quoted within a JSON string to avoid loss of precision. Furthermore, v1 and v2 may still lose precision when unmarshaling into an any interface value, where unmarshal uses a float64 by default to represent a JSON number. To change the default, specify the WithUnmarshalers option with a custom unmarshaler that pre-populates the interface value with a concrete Go type that can preserve precision. RFC 8785 specifies a canonical form for any JSON text, which explicitly defines specific behaviors that RFC 8259 leaves undefined. In theory, if a text can successfully jsontext.Value.Canonicalize without changing the semantic meaning of the data, then it provides a greater degree of confidence that the data is more secure and interoperable. The v2 API generally chooses more secure defaults than v1, but care should still be taken with large integers or unknown members. Unmarshal matches JSON object names with Go struct fields using a case-sensitive match, but can be configured to use a case-insensitive match with the "case:ignore" option. This permits unmarshaling from inputs that use naming conventions such as camelCase, snake_case, or kebab-case. By default, JSON object names for Go struct fields are derived from the Go field name, but may be specified in the `json` tag. Due to JSON's heritage in JavaScript, the most common naming convention used for JSON object names is camelCase. The "format" tag option can be used to alter the formatting of certain types. JSON objects can be inlined within a parent object similar to how Go structs can be embedded within a parent struct. The inlining rules are similar to those of Go embedding, but operates upon the JSON namespace. Go struct fields can be omitted from the output depending on either the input Go value or the output JSON encoding of the value. The "omitzero" option omits a field if it is the zero Go value or implements a "IsZero() bool" method that reports true. The "omitempty" option omits a field if it encodes as an empty JSON value, which we define as a JSON null or empty JSON string, object, or array. In many cases, the behavior of "omitzero" and "omitempty" are equivalent. If both provide the desired effect, then using "omitzero" is preferred. The exact order of JSON object can be preserved through the use of a specialized type that implements MarshalerTo and UnmarshalerFrom. Some Go types have a custom JSON representation where the implementation is delegated to some external package. Consequently, the "json" package will not know how to use that external implementation. For example, the google.golang.org/protobuf/encoding/protojson package implements JSON for all google.golang.org/protobuf/proto.Message types. WithMarshalers and WithUnmarshalers can be used to configure "json" and "protojson" to cooperate together. When implementing HTTP endpoints, it is common to be operating with an io.Reader and an io.Writer. The MarshalWrite and UnmarshalRead functions assist in operating on such input/output types. UnmarshalRead reads the entirety of the io.Reader to ensure that io.EOF is encountered without any unexpected bytes after the top-level JSON value. If a type implements encoding.TextMarshaler and/or encoding.TextUnmarshaler, then the MarshalText and UnmarshalText methods are used to encode/decode the value to/from a JSON string. Due to version skew, the set of JSON object members known at compile-time may differ from the set of members encountered at execution-time. As such, it may be useful to have finer grain handling of unknown members. This package supports preserving, rejecting, or discarding such members.

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: 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 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: 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 cgi implements the common gateway interface (CGI) for Caddy, a modern, full-featured, easy-to-use web server. This plugin lets you generate dynamic content on your website by means of command line scripts. To collect information about the inbound HTTP request, your script examines certain environment variables such as PATH_INFO and QUERY_STRING. Then, to return a dynamically generated web page to the client, your script simply writes content to standard output. In the case of POST requests, your script reads additional inbound content from standard input. The advantage of CGI is that you do not need to fuss with server startup and persistence, long term memory management, sockets, and crash recovery. Your script is called when a request matches one of the patterns that you specify in your Caddyfile. As soon as your script completes its response, it terminates. This simplicity makes CGI a perfect complement to the straightforward operation and configuration of Caddy. The benefits of Caddy, including HTTPS by default, basic access authentication, and lots of middleware options extend easily to your CGI scripts. CGI has some disadvantages. For one, Caddy needs to start a new process for each request. This can adversely impact performance and, if resources are shared between CGI applications, may require the use of some interprocess synchronization mechanism such as a file lock. Your server’s responsiveness could in some circumstances be affected, such as when your web server is hit with very high demand, when your script’s dependencies require a long startup, or when concurrently running scripts take a long time to respond. However, in many cases, such as using a pre-compiled CGI application like fossil or a Lua script, the impact will generally be insignificant. Another restriction of CGI is that scripts will be run with the same permissions as Caddy itself. This can sometimes be less than ideal, for example when your script needs to read or write files associated with a different owner. Serving dynamic content exposes your server to more potential threats than serving static pages. There are a number of considerations of which you should be aware when using CGI applications. CGI SCRIPTS SHOULD BE LOCATED OUTSIDE OF CADDY’S DOCUMENT ROOT. Otherwise, an inadvertent misconfiguration could result in Caddy delivering the script as an ordinary static resource. At best, this could merely confuse the site visitor. At worst, it could expose sensitive internal information that should not leave the server. MISTRUST THE CONTENTS OF PATH_INFO, QUERY_STRING AND STANDARD INPUT. Most of the environment variables available to your CGI program are inherently safe because they originate with Caddy and cannot be modified by external users. This is not the case with PATH_INFO, QUERY_STRING and, in the case of POST actions, the contents of standard input. Be sure to validate and sanitize all inbound content. If you use a CGI library or framework to process your scripts, make sure you understand its limitations. An error in a CGI application is generally handled within the application itself and reported in the headers it returns. Additionally, if the Caddy errors directive is enabled, any content the application writes to its standard error stream will be written to the error log. This can be useful to diagnose problems with the execution of the CGI application. Your CGI application can be executed directly or indirectly. In the direct case, the application can be a compiled native executable or it can be a shell script that contains as its first line a shebang that identifies the interpreter to which the file’s name should be passed. Caddy must have permission to execute the application. On Posix systems this will mean making sure the application’s ownership and permission bits are set appropriately; on Windows, this may involve properly setting up the filename extension association. In the indirect case, the name of the CGI script is passed to an interpreter such as lua, perl or python. The basic cgi directive lets you associate a single pattern with a particular script. The directive can be repeated any reasonable number of times. Here is the basic syntax: For example: When a request such as https://example.com/report or https://example.com/report/weekly arrives, the cgi middleware will detect the match and invoke the script named /usr/local/cgi-bin/report. The current working directory will be the same as Caddy itself. Here, it is assumed that the script is self-contained, for example a pre-compiled CGI application or a shell script. Here is an example of a standalone script, similar to one used in the cgi plugin’s test suite: The environment variables PATH_INFO and QUERY_STRING are populated and passed to the script automatically. There are a number of other standard CGI variables included that are described below. If you need to pass any special environment variables or allow any environment variables that are part of Caddy’s process to pass to your script, you will need to use the advanced directive syntax described below. The values used for the script name and its arguments are subject to placeholder replacement. In addition to the standard Caddy placeholders such as {method} and {host}, the following placeholder substitutions are made: - {.} is replaced with Caddy’s current working directory - {match} is replaced with the portion of the request that satisfies the match directive - {root} is replaced with Caddy’s specified root directory You can include glob wildcards in your matches. Basically, an asterisk represents a sequence of zero or more non-slash characters and a question mark represents a single non-slash character. These wildcards can be used multiple times in a match expression. See the documentation for path/Match in the Go standard library for more details about glob matching. Here is an example directive: In this case, the cgi middleware will match requests such as https://example.com/report/weekly.lua and https://example.com/report/report.lua/weekly but not https://example.com/report.lua. The use of the asterisk expands to any character sequence within a directory. For example, if the request is made, the following command is executed: Note that the portion of the request that follows the match is not included. That information is conveyed to the script by means of environment variables. In this example, the Lua interpreter is invoked directly from Caddy, so the Lua script does not need the shebang that would be needed in a standalone script. This method facilitates the use of CGI on the Windows platform. In order to specify custom environment variables, pass along one or more environment variables known to Caddy, or specify more than one match pattern for a given rule, you will need to use the advanced directive syntax. That looks like this: For example, With the advanced syntax, the exec subdirective must appear exactly once. The match subdirective must appear at least once. The env, pass_env, empty_env, and except subdirectives can appear any reasonable number of times. pass_all_env, dir may appear once. The dir subdirective specifies the CGI executable’s working directory. If it is not specified, Caddy’s current working directory is used. The except subdirective uses the same pattern matching logic that is used with the match subdirective except that the request must match a rule fully; no request path prefix matching is performed. Any request that matches a match pattern is then checked with the patterns in except, if any. If any matches are made with the except pattern, the request is rejected and passed along to subsequent handlers. This is a convenient way to have static file resources served properly rather than being confused as CGI applications. The empty_env subdirective is used to pass one or more empty environment variables. Some CGI scripts may expect the server to pass certain empty variables rather than leaving them unset. This subdirective allows you to deal with those situations. The values associated with environment variable keys are all subject to placeholder substitution, just as with the script name and arguments. If your CGI application runs properly at the command line but fails to run from Caddy it is possible that certain environment variables may be missing. For example, the ruby gem loader evidently requires the HOME environment variable to be set; you can do this with the subdirective pass_env HOME. Another class of problematic applications require the COMPUTERNAME variable. The pass_all_env subdirective instructs Caddy to pass each environment variable it knows about to the CGI excutable. This addresses a common frustration that is caused when an executable requires an environment variable and fails without a descriptive error message when the variable cannot be found. These applications often run fine from the command prompt but fail when invoked with CGI. The risk with this subdirective is that a lot of server information is shared with the CGI executable. Use this subdirective only with CGI applications that you trust not to leak this information. If you protect your CGI application with the Caddy JWT middleware, your program will have access to the token’s payload claims by means of environment variables. For example, the following token claims will be available with the following environment variables All values are conveyed as strings, so some conversion may be necessary in your program. No placeholder substitutions are made on these values. If you run into unexpected results with the CGI plugin, you are able to examine the environment in which your CGI application runs. To enter inspection mode, add the subdirective inspect to your CGI configuration block. This is a development option that should not be used in production. When in inspection mode, the plugin will respond to matching requests with a page that displays variables of interest. In particular, it will show the replacement value of {match} and the environment variables to which your CGI application has access. For example, consider this example CGI block: When you request a matching URL, for example, the Caddy server will deliver a text page similar to the following. The CGI application (in this case, wapptclsh) will not be called. This information can be used to diagnose problems with how a CGI application is called. To return to operation mode, remove or comment out the inspect subdirective. In this example, the Caddyfile looks like this: Note that a request for /show gets mapped to a script named /usr/local/cgi-bin/report/gen. There is no need for any element of the script name to match any element of the match pattern. The contents of /usr/local/cgi-bin/report/gen are: The purpose of this script is to show how request information gets communicated to a CGI script. Note that POST data must be read from standard input. In this particular case, posted data gets stored in the variable POST_DATA. Your script may use a different method to read POST content. Secondly, the SCRIPT_EXEC variable is not a CGI standard. It is provided by this middleware and contains the entire command line, including all arguments, with which the CGI script was executed. When a browser requests the response looks like When a client makes a POST request, such as with the following command the response looks the same except for the following lines: The fossil distributed software management tool is a native executable that supports interaction as a CGI application. In this example, /usr/bin/fossil is the executable and /home/quixote/projects.fossil is the fossil repository. To configure Caddy to serve it, use a cgi directive something like this in your Caddyfile: In your /usr/local/cgi-bin directory, make a file named projects with the following single line: The fossil documentation calls this a command file. When fossil is invoked after a request to /projects, it examines the relevant environment variables and responds as a CGI application. If you protect /projects with basic HTTP authentication, you may wish to enable the ALLOW REMOTE_USER AUTHENTICATION option when setting up fossil. This lets fossil dispense with its own authentication, assuming it has an account for the user. The agedu utility can be used to identify unused files that are taking up space on your storage media. Like fossil, it can be used in different modes including CGI. First, use it from the command line to generate an index of a directory, for example In your Caddyfile, include a directive that references the generated index: You will want to protect the /agedu resource with some sort of access control, for example HTTP Basic Authentication. This small example demonstrates how to write a CGI program in Go. The use of a bytes.Buffer makes it easy to report the content length in the CGI header. When this program is compiled and installed as /usr/local/bin/servertime, the following directive in your Caddy file will make it available: The cgit application provides an attractive and useful web interface to git repositories. Here is how to run it with Caddy. After compiling cgit, you can place the executable somewhere out of Caddy’s document root. In this example, it is located in /usr/local/cgi-bin. A sample configuration file is included in the project’s cgitrc.5.txt file. You can use it as a starting point for your configuration. The default location for this file is /etc/cgitrc but in this example the location /home/quixote/caddy/cgitrc. Note that changing the location of this file from its default will necessitate the inclusion of the environment variable CGIT_CONFIG in the Caddyfile cgi directive. When you edit the repository stanzas in this file, be sure each repo.path item refers to the .git directory within a working checkout. Here is an example stanza: Also, you will likely want to change cgit’s cache directory from its default in /var/cache (generally accessible only to root) to a location writeable by Caddy. In this example, cgitrc contains the line You may need to create the cgit subdirectory. There are some static cgit resources (namely, cgit.css, favicon.ico, and cgit.png) that will be accessed from Caddy’s document tree. For this example, these files are placed in a directory named cgit-resource. The following lines are part of the cgitrc file: Additionally, you will likely need to tweak the various file viewer filters such source-filter and about-filter based on your system. The following Caddyfile directive will allow you to access the cgit application at /cgit: Feeling reckless? You can run PHP in CGI mode. In general, FastCGI is the preferred method to run PHP if your application has many pages or a fair amount of database activity. But for small PHP programs that are seldom used, CGI can work fine. You’ll need the php-cgi interpreter for your platform. This may involve downloading the executable or downloading and then compiling the source code. For this example, assume the interpreter is installed as /usr/local/bin/php-cgi. Additionally, because of the way PHP operates in CGI mode, you will need an intermediate script. This one works in Posix environments: This script can be reused for multiple cgi directives. In this example, it is installed as /usr/local/cgi-bin/phpwrap. The argument following -c is your initialization file for PHP. In this example, it is named /home/quixote/.config/php/php-cgi.ini. Two PHP files will be used for this example. The first, /usr/local/cgi-bin/sample/min.php, looks like this: The second, /usr/local/cgi-bin/sample/action.php, follows: The following directive in your Caddyfile will make the application available at sample/min.php: This examples demonstrates printing a CGI rule

Package tcell provides a lower-level, portable API for building programs that interact with terminals or consoles. It works with both common (and many uncommon!) terminals or terminal emulators, and Windows console implementations. It provides support for up to 256 colors, text attributes, and box drawing elements. A database of terminals built from a real terminfo database is provided, along with code to generate new database entries. Tcell offers very rich support for mice, dependent upon the terminal of course. (Windows, XTerm, and iTerm 2 are known to work very well.) If the environment is not Unicode by default, such as an ISO8859 based locale or GB18030, Tcell can convert input and output, so that your terminal can operate in whatever locale is most convenient, while the application program can just assume "everything is UTF-8". Reasonable defaults are used for updating characters to something suitable for display. Unicode box drawing characters will be converted to use the alternate character set of your terminal, if native conversions are not available. If no ACS is available, then some ASCII fallbacks will be used. Note that support for non-UTF-8 locales (other than C) must be enabled by the application using RegisterEncoding() -- we don't have them all enabled by default to avoid bloating the application unneccessarily. (These days UTF-8 is good enough for almost everyone, and nobody should be using legacy locales anymore.) Also, actual glyphs for various code point will only be displayed if your terminal or emulator (or the font the emulator is using) supports them. A rich set of keycodes is supported, with support for up to 65 function keys, and various other special keys.

Package blackfriday is a markdown processor. It translates plain text with simple formatting rules into an AST, which can then be further processed to HTML (provided by Blackfriday itself) or other formats (provided by the community). The simplest way to invoke Blackfriday is to call the Run function. It will take a text input and produce a text output in HTML (or other format). A slightly more sophisticated way to use Blackfriday is to create a Markdown processor and to call Parse, which returns a syntax tree for the input document. You can leverage Blackfriday's parsing for content extraction from markdown documents. You can assign a custom renderer and set various options to the Markdown processor. If you're interested in calling Blackfriday from command line, see https://github.com/russross/blackfriday-tool. Blackfriday includes an algorithm for creating sanitized anchor names corresponding to a given input text. This algorithm is used to create anchors for headings when AutoHeadingIDs extension is enabled. The algorithm is specified below, so that other packages can create compatible anchor names and links to those anchors. The algorithm iterates over the input text, interpreted as UTF-8, one Unicode code point (rune) at a time. All runes that are letters (category L) or numbers (category N) are considered valid characters. They are mapped to lower case, and included in the output. All other runes are considered invalid characters. Invalid characters that precede the first valid character, as well as invalid character that follow the last valid character are dropped completely. All other sequences of invalid characters between two valid characters are replaced with a single dash character '-'. SanitizedAnchorName exposes this functionality, and can be used to create compatible links to the anchor names generated by blackfriday. This algorithm is also implemented in a small standalone package at github.com/shurcooL/sanitized_anchor_name. It can be useful for clients that want a small package and don't need full functionality of blackfriday.

Package null contains SQL types that consider zero input and null input as separate values, with convenient support for JSON and text marshaling. Types in this package will always encode to their null value if null. Use the zero subpackage if you want zero values and null to be treated the same.

Help editor to Input cjk language. Author fuhuizn@163.com Package gocui allows to create console user interfaces. Create a new GUI: Set GUI managers: Managers are in charge of GUI's layout and can be used to build widgets. On each iteration of the GUI's main loop, the Layout function of each configured manager is executed. Managers are used to set-up and update the application's main views, being possible to freely change them during execution. Also, it is important to mention that a main loop iteration is executed on each reported event (key-press, mouse event, window resize, etc). GUIs are composed by Views, you can think of it as buffers. Views implement the io.ReadWriter interface, so you can just write to them if you want to modify their content. The same is valid for reading. Create and initialize a view with absolute coordinates: Views can also be created using relative coordinates: Configure keybindings: gocui implements full mouse support that can be enabled with: Mouse events are handled like any other keybinding: IMPORTANT: Views can only be created, destroyed or updated in three ways: from the Layout function within managers, from keybinding callbacks or via *Gui.Update(). The reason for this is that it allows gocui to be concurrent-safe. So, if you want to update your GUI from a goroutine, you must use *Gui.Update(). For example: By default, gocui provides a basic edition mode. This mode can be extended and customized creating a new Editor and assigning it to *View.Editor: DefaultEditor can be taken as example to create your own custom Editor: Colored text: Views allow to add colored text using ANSI colors. For example: For more information, see the examples in folder "_examples/".

Package blackfriday is a Markdown processor. It translates plain text with simple formatting rules into HTML or LaTeX. Blackfriday includes an algorithm for creating sanitized anchor names corresponding to a given input text. This algorithm is used to create anchors for headings when EXTENSION_AUTO_HEADER_IDS is enabled. The algorithm is specified below, so that other packages can create compatible anchor names and links to those anchors. The algorithm iterates over the input text, interpreted as UTF-8, one Unicode code point (rune) at a time. All runes that are letters (category L) or numbers (category N) are considered valid characters. They are mapped to lower case, and included in the output. All other runes are considered invalid characters. Invalid characters that preceed the first valid character, as well as invalid character that follow the last valid character are dropped completely. All other sequences of invalid characters between two valid characters are replaced with a single dash character '-'. SanitizedAnchorName exposes this functionality, and can be used to create compatible links to the anchor names generated by blackfriday. This algorithm is also implemented in a small standalone package at github.com/shurcooL/sanitized_anchor_name. It can be useful for clients that want a small package and don't need full functionality of blackfriday.

Package tcell provides a lower-level, portable API for building programs that interact with terminals or consoles. It works with both common (and many uncommon!) terminals or terminal emulators, and Windows console implementations. It provides support for up to 256 colors, text attributes, and box drawing elements. A database of terminals built from a real terminfo database is provided, along with code to generate new database entries. Tcell offers very rich support for mice, dependent upon the terminal of course. (Windows, XTerm, and iTerm 2 are known to work very well.) If the environment is not Unicode by default, such as an ISO8859 based locale or GB18030, Tcell can convert input and output, so that your terminal can operate in whatever locale is most convenient, while the application program can just assume "everything is UTF-8". Reasonable defaults are used for updating characters to something suitable for display. Unicode box drawing characters will be converted to use the alternate character set of your terminal, if native conversions are not available. If no ACS is available, then some ASCII fallbacks will be used. Note that support for non-UTF-8 locales (other than C) must be enabled by the application using RegisterEncoding() -- we don't have them all enabled by default to avoid bloating the application unneccessarily. (These days UTF-8 is good enough for almost everyone, and nobody should be using legacy locales anymore.) Also, actual glyphs for various code point will only be displayed if your terminal or emulator (or the font the emulator is using) supports them. A rich set of keycodes is supported, with support for up to 65 function keys, and various other special keys.

Package tcell provides a lower-level, portable API for building programs that interact with terminals or consoles. It works with both common (and many uncommon!) terminals or terminal emulators, and Windows console implementations. It provides support for up to 256 colors, text attributes, and box drawing elements. A database of terminals built from a real terminfo database is provided, along with code to generate new database entries. Tcell offers very rich support for mice, dependent upon the terminal of course. (Windows, XTerm, and iTerm 2 are known to work very well.) If the environment is not Unicode by default, such as an ISO8859 based locale or GB18030, Tcell can convert input and output, so that your terminal can operate in whatever locale is most convenient, while the application program can just assume "everything is UTF-8". Reasonable defaults are used for updating characters to something suitable for display. Unicode box drawing characters will be converted to use the alternate character set of your terminal, if native conversions are not available. If no ACS is available, then some ASCII fallbacks will be used. Note that support for non-UTF-8 locales (other than C) must be enabled by the application using RegisterEncoding() -- we don't have them all enabled by default to avoid bloating the application unnecessarily. (These days UTF-8 is good enough for almost everyone, and nobody should be using legacy locales anymore.) Also, actual glyphs for various code point will only be displayed if your terminal or emulator (or the font the emulator is using) supports them. A rich set of key codes is supported, with support for up to 65 function keys, and various other special keys.

Package tcell provides a lower-level, portable API for building programs that interact with terminals or consoles. It works with both common (and many uncommon!) terminals or terminal emulators, and Windows console implementations. It provides support for up to 256 colors, text attributes, and box drawing elements. A database of terminals built from a real terminfo database is provided, along with code to generate new database entries. Tcell offers very rich support for mice, dependent upon the terminal of course. (Windows, XTerm, and iTerm 2 are known to work very well.) If the environment is not Unicode by default, such as an ISO8859 based locale or GB18030, Tcell can convert input and output, so that your terminal can operate in whatever locale is most convenient, while the application program can just assume "everything is UTF-8". Reasonable defaults are used for updating characters to something suitable for display. Unicode box drawing characters will be converted to use the alternate character set of your terminal, if native conversions are not available. If no ACS is available, then some ASCII fallbacks will be used. Note that support for non-UTF-8 locales (other than C) must be enabled by the application using RegisterEncoding() -- we don't have them all enabled by default to avoid bloating the application unneccessarily. (These days UTF-8 is good enough for almost everyone, and nobody should be using legacy locales anymore.) Also, actual glyphs for various code point will only be displayed if your terminal or emulator (or the font the emulator is using) supports them. A rich set of keycodes is supported, with support for up to 65 function keys, and various other special keys.

Package secretsmanager provides the client and types for making API requests to AWS Secrets Manager. AWS Secrets Manager is a web service that enables you to store, manage, and retrieve, secrets. This guide provides descriptions of the Secrets Manager API. For more information about using this service, see the AWS Secrets Manager User Guide (http://docs.aws.amazon.com/secretsmanager/latest/userguide/introduction.html). This version of the Secrets Manager API Reference documents the Secrets Manager API version 2017-10-17. As an alternative to using the API directly, you can use one of the AWS SDKs, which consist of libraries and sample code for various programming languages and platforms (such as Java, Ruby, .NET, iOS, and Android). The SDKs provide a convenient way to create programmatic access to AWS Secrets Manager. For example, the SDKs take care of cryptographically signing requests, managing errors, and retrying requests automatically. For more information about the AWS SDKs, including how to download and install them, see Tools for Amazon Web Services (http://aws.amazon.com/tools/). We recommend that you use the AWS SDKs to make programmatic API calls to Secrets Manager. However, you also can use the Secrets Manager HTTP Query API to make direct calls to the Secrets Manager web service. To learn more about the Secrets Manager HTTP Query API, see Making Query Requests (http://docs.aws.amazon.com/secretsmanager/latest/userguide/query-requests.html) in the AWS Secrets Manager User Guide. Secrets Manager supports GET and POST requests for all actions. That is, the API doesn't require you to use GET for some actions and POST for others. However, GET requests are subject to the limitation size of a URL. Therefore, for operations that require larger sizes, use a POST request. We welcome your feedback. Send your comments to awssecretsmanager-feedback@amazon.com (mailto:awssecretsmanager-feedback@amazon.com), or post your feedback and questions in the AWS Secrets Manager Discussion Forum (http://forums.aws.amazon.com/forum.jspa?forumID=296). For more information about the AWS Discussion Forums, see Forums Help (http://forums.aws.amazon.com/help.jspa). The JSON that AWS Secrets Manager expects as your request parameters and that the service returns as a response to HTTP query requests are single, long strings without line breaks or white space formatting. The JSON shown in the examples is formatted with both line breaks and white space to improve readability. When example input parameters would also result in long strings that extend beyond the screen, we insert line breaks to enhance readability. You should always submit the input as a single JSON text string. AWS Secrets Manager supports AWS CloudTrail, a service that records AWS API calls for your AWS account and delivers log files to an Amazon S3 bucket. By using information that's collected by AWS CloudTrail, you can determine which requests were successfully made to Secrets Manager, who made the request, when it was made, and so on. For more about AWS Secrets Manager and its support for AWS CloudTrail, see Logging AWS Secrets Manager Events with AWS CloudTrail (http://docs.aws.amazon.com/secretsmanager/latest/userguide/monitoring.html#monitoring_cloudtrail) in the AWS Secrets Manager User Guide. To learn more about CloudTrail, including how to turn it on and find your log files, see the AWS CloudTrail User Guide (http://docs.aws.amazon.com/awscloudtrail/latest/userguide/what_is_cloud_trail_top_level.html). See https://docs.aws.amazon.com/goto/WebAPI/secretsmanager-2017-10-17 for more information on this service. See secretsmanager package documentation for more information. https://docs.aws.amazon.com/sdk-for-go/api/service/secretsmanager/ To AWS Secrets Manager with the SDK use the New function to create a new service client. With that client you can make API requests to the service. These clients are safe to use concurrently. See the SDK's documentation for more information on how to use the SDK. https://docs.aws.amazon.com/sdk-for-go/api/ See aws.Config documentation for more information on configuring SDK clients. https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config See the AWS Secrets Manager client SecretsManager for more information on creating client for this service. https://docs.aws.amazon.com/sdk-for-go/api/service/secretsmanager/#New

Package segment is a library for performing Unicode Text Segmentation as described in Unicode Standard Annex #29 http://www.unicode.org/reports/tr29/ Currently only segmentation at Word Boundaries is supported. The functionality is exposed in two ways: 1. You can use a bufio.Scanner with the SplitWords implementation of SplitFunc. The SplitWords function will identify the appropriate word boundaries in the input text and the Scanner will return tokens at the appropriate place. 2. Sometimes you would also like information returned about the type of token. To do this we have introduce a new type named Segmenter. It works just like Scanner but additionally a token type is returned.

Package tcell provides a lower-level, portable API for building programs that interact with terminals or consoles. It works with both common (and many uncommon!) terminals or terminal emulators, and Windows console implementations. It provides support for up to 256 colors, text attributes, and box drawing elements. A database of terminals built from a real terminfo database is provided, along with code to generate new database entries. Tcell offers very rich support for mice, dependent upon the terminal of course. (Windows, XTerm, and iTerm 2 are known to work very well.) If the environment is not Unicode by default, such as an ISO8859 based locale or GB18030, Tcell can convert input and output, so that your terminal can operate in whatever locale is most convenient, while the application program can just assume "everything is UTF-8". Reasonable defaults are used for updating characters to something suitable for display. Unicode box drawing characters will be converted to use the alternate character set of your terminal, if native conversions are not available. If no ACS is available, then some ASCII fallbacks will be used. Note that support for non-UTF-8 locales (other than C) must be enabled by the application using RegisterEncoding() -- we don't have them all enabled by default to avoid bloating the application unneccessarily. (These days UTF-8 is good enough for almost everyone, and nobody should be using legacy locales anymore.) Also, actual glyphs for various code point will only be displayed if your terminal or emulator (or the font the emulator is using) supports them. A rich set of keycodes is supported, with support for up to 65 function keys, and various other special keys.

2fa is a two-factor authentication agent. Usage: “2fa -add name” adds a new key to the 2fa keychain with the given name. It prints a prompt to standard error and reads a two-factor key from standard input. Two-factor keys are short case-insensitive strings of letters A-Z and digits 2-7. By default the new key generates time-based (TOTP) authentication codes; the -hotp flag makes the new key generate counter-based (HOTP) codes instead. By default the new key generates 6-digit codes; the -7 and -8 flags select 7- and 8-digit codes instead. “2fa -list” lists the names of all the keys in the keychain. “2fa name” prints a two-factor authentication code from the key with the given name. If “-clip” is specified, 2fa also copies the code to the system clipboard. With no arguments, 2fa prints two-factor authentication codes from all known time-based keys. The default time-based authentication codes are derived from a hash of the key and the current time, so it is important that the system clock have at least one-minute accuracy. The keychain is stored unencrypted in the text file $HOME/.2fa. During GitHub 2FA setup, at the “Scan this barcode with your app” step, click the “enter this text code instead” link. A window pops up showing “your two-factor secret,” a short string of letters and digits. Add it to 2fa under the name github, typing the secret at the prompt: Then whenever GitHub prompts for a 2FA code, run 2fa to obtain one: Or to type less:

Package testscript provides support for defining filesystem-based tests by creating scripts in a directory. To invoke the tests, call testscript.Run. For example: A testscript directory holds test scripts *.txt run during 'go test'. Each script defines a subtest; the exact set of allowable commands in a script are defined by the parameters passed to the Run function. To run a specific script foo.txt where TestName is the name of the test that Run is called from. To define an executable command (or several) that can be run as part of the script, call RunMain with the functions that implement the command's functionality. The command functions will be called in a separate process, so are free to mutate global variables without polluting the top level test binary. In general script files should have short names: a few words, not whole sentences. The first word should be the general category of behavior being tested, often the name of a subcommand to be tested or a concept (vendor, pattern). Each script is a text archive (go doc github.com/rogpeppe/testscript//txtar). The script begins with an actual command script to run followed by the content of zero or more supporting files to create in the script's temporary file system before it starts executing. As an example: Each script runs in a fresh temporary work directory tree, available to scripts as $WORK. Scripts also have access to these other environment variables: The environment variable $exe (lowercase) is an empty string on most systems, ".exe" on Windows. The script's supporting files are unpacked relative to $WORK and then the script begins execution in that directory as well. Thus the example above runs in $WORK with $WORK/hello.txt containing the listed contents. The lines at the top of the script are a sequence of commands to be executed by a small script engine in the testscript package (not the system shell). The script stops and the overall test fails if any particular command fails. Each line is parsed into a sequence of space-separated command words, with environment variable expansion and # marking an end-of-line comment. Adding single quotes around text keeps spaces in that text from being treated as word separators and also disables environment variable expansion. Inside a single-quoted block of text, a repeated single quote indicates a literal single quote, as in: A line beginning with # is a comment and conventionally explains what is being done or tested at the start of a new phase in the script. A special form of environment variable syntax can be used to quote regexp metacharacters inside environment variables. The "@R" suffix is special, and indicates that the variable should be quoted. The command prefix ! indicates that the command on the rest of the line (typically go or a matching predicate) must fail, not succeed. Only certain commands support this prefix. They are indicated below by [!] in the synopsis. The command prefix [cond] indicates that the command on the rest of the line should only run when the condition is satisfied. The predefined conditions are: A condition can be negated: [!short] means to run the rest of the line when testing.Short() is false. Additional conditions can be added by passing a function to Params.Condition. The predefined commands are: - chmod mode file [!] exec program [args...] [&] Run the given executable program with the arguments. It must (or must not) succeed. Note that 'exec' does not terminate the script (unlike in Unix shells). If the last token is '&', the program executes in the background. The standard output and standard error of the previous command is cleared, but the output of the background process is buffered — and checking of its exit status is delayed — until the next call to 'wait', 'skip', or 'stop' or the end of the test. At the end of the test, any remaining background processes are terminated using os.Interrupt (if supported) or os.Kill. Standard input can be provided using the stdin command; this will be cleared after exec has been called. When TestScript runs a script and the script fails, by default TestScript shows the execution of the most recent phase of the script (since the last # comment) and only shows the # comments for earlier phases. For example, here is a multi-phase script with a bug in it (TODO: make this example less go-command specific): The bug is that the final phase installs p11 instead of p1. The test failure looks like: Note that the commands in earlier phases have been hidden, so that the relevant commands are more easily found, and the elapsed time for a completed phase is shown next to the phase heading. To see the entire execution, use "go test -v", which also adds an initial environment dump to the beginning of the log. Note also that in reported output, the actual name of the per-script temporary directory has been consistently replaced with the literal string $WORK. If Params.TestWork is true, it causes each test to log the name of its $WORK directory and other environment variable settings and also to leave that directory behind when it exits, for manual debugging of failing tests:

Package ql implements a pure Go embedded SQL database engine. QL is a member of the SQL family of languages. It is less complex and less powerful than SQL (whichever specification SQL is considered to be). 2017-01-10: Release v1.1.0 fixes some bugs and adds a configurable WAL headroom. 2016-07-29: Release v1.0.6 enables alternatively using = instead of == for equality operation. 2016-07-11: Release v1.0.5 undoes vendoring of lldb. QL now uses stable lldb (github.com/cznic/lldb). 2016-07-06: Release v1.0.4 fixes a panic when closing the WAL file. 2016-04-03: Release v1.0.3 fixes a data race. 2016-03-23: Release v1.0.2 vendors github.com/cznic/exp/lldb and github.com/camlistore/go4/lock. 2016-03-17: Release v1.0.1 adjusts for latest goyacc. Parser error messages are improved and changed, but their exact form is not considered a API change. 2016-03-05: The current version has been tagged v1.0.0. 2015-06-15: To improve compatibility with other SQL implementations, the count built-in aggregate function now accepts * as its argument. 2015-05-29: The execution planner was rewritten from scratch. It should use indices in all places where they were used before plus in some additional situations. It is possible to investigate the plan using the newly added EXPLAIN statement. The QL tool is handy for such analysis. If the planner would have used an index, but no such exists, the plan includes hints in form of copy/paste ready CREATE INDEX statements. The planner is still quite simple and a lot of work on it is yet ahead. You can help this process by filling an issue with a schema and query which fails to use an index or indices when it should, in your opinion. Bonus points for including output of `ql 'explain <query>'`. 2015-05-09: The grammar of the CREATE INDEX statement now accepts an expression list instead of a single expression, which was further limited to just a column name or the built-in id(). As a side effect, composite indices are now functional. However, the values in the expression-list style index are not yet used by other statements or the statement/query planner. The composite index is useful while having UNIQUE clause to check for semantically duplicate rows before they get added to the table or when such a row is mutated using the UPDATE statement and the expression-list style index tuple of the row is thus recomputed. 2015-05-02: The Schema field of table __Table now correctly reflects any column constraints and/or defaults. Also, the (*DB).Info method now has that information provided in new ColumInfo fields NotNull, Constraint and Default. 2015-04-20: Added support for {LEFT,RIGHT,FULL} [OUTER] JOIN. 2015-04-18: Column definitions can now have constraints and defaults. Details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. 2015-03-06: New built-in functions formatFloat and formatInt. Thanks urandom! (https://github.com/urandom) 2015-02-16: IN predicate now accepts a SELECT statement. See the updated "Predicates" section. 2015-01-17: Logical operators || and && have now alternative spellings: OR and AND (case insensitive). AND was a keyword before, but OR is a new one. This can possibly break existing queries. For the record, it's a good idea to not use any name appearing in, for example, [7] in your queries as the list of QL's keywords may expand for gaining better compatibility with existing SQL "standards". 2015-01-12: ACID guarantees were tightened at the cost of performance in some cases. The write collecting window mechanism, a formerly used implementation detail, was removed. Inserting rows one by one in a transaction is now slow. I mean very slow. Try to avoid inserting single rows in a transaction. Instead, whenever possible, perform batch updates of tens to, say thousands of rows in a single transaction. See also: http://www.sqlite.org/faq.html#q19, the discussed synchronization principles involved are the same as for QL, modulo minor details. Note: A side effect is that closing a DB before exiting an application, both for the Go API and through database/sql driver, is no more required, strictly speaking. Beware that exiting an application while there is an open (uncommitted) transaction in progress means losing the transaction data. However, the DB will not become corrupted because of not closing it. Nor that was the case before, but formerly failing to close a DB could have resulted in losing the data of the last transaction. 2014-09-21: id() now optionally accepts a single argument - a table name. 2014-09-01: Added the DB.Flush() method and the LIKE pattern matching predicate. 2014-08-08: The built in functions max and min now accept also time values. Thanks opennota! (https://github.com/opennota) 2014-06-05: RecordSet interface extended by new methods FirstRow and Rows. 2014-06-02: Indices on id() are now used by SELECT statements. 2014-05-07: Introduction of Marshal, Schema, Unmarshal. 2014-04-15: Added optional IF NOT EXISTS clause to CREATE INDEX and optional IF EXISTS clause to DROP INDEX. 2014-04-12: The column Unique in the virtual table __Index was renamed to IsUnique because the old name is a keyword. Unfortunately, this is a breaking change, sorry. 2014-04-11: Introduction of LIMIT, OFFSET. 2014-04-10: Introduction of query rewriting. 2014-04-07: Introduction of indices. QL imports zappy[8], a block-based compressor, which speeds up its performance by using a C version of the compression/decompression algorithms. If a CGO-free (pure Go) version of QL, or an app using QL, is required, please include 'purego' in the -tags option of go {build,get,install}. For example: If zappy was installed before installing QL, it might be necessary to rebuild zappy first (or rebuild QL with all its dependencies using the -a option): The syntax is specified using Extended Backus-Naur Form (EBNF) Lower-case production names are used to identify lexical tokens. Non-terminals are in CamelCase. Lexical tokens are enclosed in double quotes "" or back quotes “. The form a … b represents the set of characters from a through b as alternatives. The horizontal ellipsis … is also used elsewhere in the spec to informally denote various enumerations or code snippets that are not further specified. QL source code is Unicode text encoded in UTF-8. The text is not canonicalized, so a single accented code point is distinct from the same character constructed from combining an accent and a letter; those are treated as two code points. For simplicity, this document will use the unqualified term character to refer to a Unicode code point in the source text. Each code point is distinct; for instance, upper and lower case letters are different characters. Implementation restriction: For compatibility with other tools, the parser may disallow the NUL character (U+0000) in the statement. Implementation restriction: A byte order mark is disallowed anywhere in QL statements. The following terms are used to denote specific character classes The underscore character _ (U+005F) is considered a letter. Lexical elements are comments, tokens, identifiers, keywords, operators and delimiters, integer, floating-point, imaginary, rune and string literals and QL parameters. Line comments start with the character sequence // or -- and stop at the end of the line. A line comment acts like a space. General comments start with the character sequence /* and continue through the character sequence */. A general comment acts like a space. Comments do not nest. Tokens form the vocabulary of QL. There are four classes: identifiers, keywords, operators and delimiters, and literals. White space, formed from spaces (U+0020), horizontal tabs (U+0009), carriage returns (U+000D), and newlines (U+000A), is ignored except as it separates tokens that would otherwise combine into a single token. The formal grammar uses semicolons ";" as separators of QL statements. A single QL statement or the last QL statement in a list of statements can have an optional semicolon terminator. (Actually a separator from the following empty statement.) Identifiers name entities such as tables or record set columns. An identifier is a sequence of one or more letters and digits. The first character in an identifier must be a letter. For example No identifiers are predeclared, however note that no keyword can be used as an identifier. Identifiers starting with two underscores are used for meta data virtual tables names. For forward compatibility, users should generally avoid using any identifiers starting with two underscores. For example The following keywords are reserved and may not be used as identifiers. Keywords are not case sensitive. The following character sequences represent operators, delimiters, and other special tokens Operators consisting of more than one character are referred to by names in the rest of the documentation An integer literal is a sequence of digits representing an integer constant. An optional prefix sets a non-decimal base: 0 for octal, 0x or 0X for hexadecimal. In hexadecimal literals, letters a-f and A-F represent values 10 through 15. For example A floating-point literal is a decimal representation of a floating-point constant. It has an integer part, a decimal point, a fractional part, and an exponent part. The integer and fractional part comprise decimal digits; the exponent part is an e or E followed by an optionally signed decimal exponent. One of the integer part or the fractional part may be elided; one of the decimal point or the exponent may be elided. For example An imaginary literal is a decimal representation of the imaginary part of a complex constant. It consists of a floating-point literal or decimal integer followed by the lower-case letter i. For example A rune literal represents a rune constant, an integer value identifying a Unicode code point. A rune literal is expressed as one or more characters enclosed in single quotes. Within the quotes, any character may appear except single quote and newline. A single quoted character represents the Unicode value of the character itself, while multi-character sequences beginning with a backslash encode values in various formats. The simplest form represents the single character within the quotes; since QL statements are Unicode characters encoded in UTF-8, multiple UTF-8-encoded bytes may represent a single integer value. For instance, the literal 'a' holds a single byte representing a literal a, Unicode U+0061, value 0x61, while 'ä' holds two bytes (0xc3 0xa4) representing a literal a-dieresis, U+00E4, value 0xe4. Several backslash escapes allow arbitrary values to be encoded as ASCII text. There are four ways to represent the integer value as a numeric constant: \x followed by exactly two hexadecimal digits; \u followed by exactly four hexadecimal digits; \U followed by exactly eight hexadecimal digits, and a plain backslash \ followed by exactly three octal digits. In each case the value of the literal is the value represented by the digits in the corresponding base. Although these representations all result in an integer, they have different valid ranges. Octal escapes must represent a value between 0 and 255 inclusive. Hexadecimal escapes satisfy this condition by construction. The escapes \u and \U represent Unicode code points so within them some values are illegal, in particular those above 0x10FFFF and surrogate halves. After a backslash, certain single-character escapes represent special values All other sequences starting with a backslash are illegal inside rune literals. For example A string literal represents a string constant obtained from concatenating a sequence of characters. There are two forms: raw string literals and interpreted string literals. Raw string literals are character sequences between back quotes “. Within the quotes, any character is legal except back quote. The value of a raw string literal is the string composed of the uninterpreted (implicitly UTF-8-encoded) characters between the quotes; in particular, backslashes have no special meaning and the string may contain newlines. Carriage returns inside raw string literals are discarded from the raw string value. Interpreted string literals are character sequences between double quotes "". The text between the quotes, which may not contain newlines, forms the value of the literal, with backslash escapes interpreted as they are in rune literals (except that \' is illegal and \" is legal), with the same restrictions. The three-digit octal (\nnn) and two-digit hexadecimal (\xnn) escapes represent individual bytes of the resulting string; all other escapes represent the (possibly multi-byte) UTF-8 encoding of individual characters. Thus inside a string literal \377 and \xFF represent a single byte of value 0xFF=255, while ÿ, \u00FF, \U000000FF and \xc3\xbf represent the two bytes 0xc3 0xbf of the UTF-8 encoding of character U+00FF. For example These examples all represent the same string If the statement source represents a character as two code points, such as a combining form involving an accent and a letter, the result will be an error if placed in a rune literal (it is not a single code point), and will appear as two code points if placed in a string literal. Literals are assigned their values from the respective text representation at "compile" (parse) time. QL parameters provide the same functionality as literals, but their value is assigned at execution time from an expression list passed to DB.Run or DB.Execute. Using '?' or '$' is completely equivalent. For example Keywords 'false' and 'true' (not case sensitive) represent the two possible constant values of type bool (also not case sensitive). Keyword 'NULL' (not case sensitive) represents an untyped constant which is assignable to any type. NULL is distinct from any other value of any type. A type determines the set of values and operations specific to values of that type. A type is specified by a type name. Named instances of the boolean, numeric, and string types are keywords. The names are not case sensitive. Note: The blob type is exchanged between the back end and the API as []byte. On 32 bit platforms this limits the size which the implementation can handle to 2G. A boolean type represents the set of Boolean truth values denoted by the predeclared constants true and false. The predeclared boolean type is bool. A duration type represents the elapsed time between two instants as an int64 nanosecond count. The representation limits the largest representable duration to approximately 290 years. A numeric type represents sets of integer or floating-point values. The predeclared architecture-independent numeric types are The value of an n-bit integer is n bits wide and represented using two's complement arithmetic. Conversions are required when different numeric types are mixed in an expression or assignment. A string type represents the set of string values. A string value is a (possibly empty) sequence of bytes. The case insensitive keyword for the string type is 'string'. The length of a string (its size in bytes) can be discovered using the built-in function len. A time type represents an instant in time with nanosecond precision. Each time has associated with it a location, consulted when computing the presentation form of the time. The following functions are implicitly declared An expression specifies the computation of a value by applying operators and functions to operands. Operands denote the elementary values in an expression. An operand may be a literal, a (possibly qualified) identifier denoting a constant or a function or a table/record set column, or a parenthesized expression. A qualified identifier is an identifier qualified with a table/record set name prefix. For example Primary expression are the operands for unary and binary expressions. For example A primary expression of the form denotes the element of a string indexed by x. Its type is byte. The value x is called the index. The following rules apply - The index x must be of integer type except bigint or duration; it is in range if 0 <= x < len(s), otherwise it is out of range. - A constant index must be non-negative and representable by a value of type int. - A constant index must be in range if the string a is a literal. - If x is out of range at run time, a run-time error occurs. - s[x] is the byte at index x and the type of s[x] is byte. If s is NULL or x is NULL then the result is NULL. Otherwise s[x] is illegal. For a string, the primary expression constructs a substring. The indices low and high select which elements appear in the result. The result has indices starting at 0 and length equal to high - low. For convenience, any of the indices may be omitted. A missing low index defaults to zero; a missing high index defaults to the length of the sliced operand The indices low and high are in range if 0 <= low <= high <= len(a), otherwise they are out of range. A constant index must be non-negative and representable by a value of type int. If both indices are constant, they must satisfy low <= high. If the indices are out of range at run time, a run-time error occurs. Integer values of type bigint or duration cannot be used as indices. If s is NULL the result is NULL. If low or high is not omitted and is NULL then the result is NULL. Given an identifier f denoting a predeclared function, calls f with arguments a1, a2, … an. Arguments are evaluated before the function is called. The type of the expression is the result type of f. In a function call, the function value and arguments are evaluated in the usual order. After they are evaluated, the parameters of the call are passed by value to the function and the called function begins execution. The return value of the function is passed by value when the function returns. Calling an undefined function causes a compile-time error. Operators combine operands into expressions. Comparisons are discussed elsewhere. For other binary operators, the operand types must be identical unless the operation involves shifts or untyped constants. For operations involving constants only, see the section on constant expressions. Except for shift operations, if one operand is an untyped constant and the other operand is not, the constant is converted to the type of the other operand. The right operand in a shift expression must have unsigned integer type or be an untyped constant that can be converted to unsigned integer type. If the left operand of a non-constant shift expression is an untyped constant, the type of the constant is what it would be if the shift expression were replaced by its left operand alone. Expressions of the form yield a boolean value true if expr2, a regular expression, matches expr1 (see also [6]). Both expression must be of type string. If any one of the expressions is NULL the result is NULL. Predicates are special form expressions having a boolean result type. Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be comparable as defined in "Comparison operators". Another form of the IN predicate creates the expression list from a result of a SelectStmt. The SelectStmt must select only one column. The produced expression list is resource limited by the memory available to the process. NULL values produced by the SelectStmt are ignored, but if all records of the SelectStmt are NULL the predicate yields NULL. The select statement is evaluated only once. If the type of expr is not the same as the type of the field returned by the SelectStmt then the set operation yields false. The type of the column returned by the SelectStmt must be one of the simple (non blob-like) types: Expressions of the form are equivalent, including NULL handling, to The types of involved expressions must be ordered as defined in "Comparison operators". Expressions of the form yield a boolean value true if expr does not have a specific type (case A) or if expr has a specific type (case B). In other cases the result is a boolean value false. Unary operators have the highest precedence. There are five precedence levels for binary operators. Multiplication operators bind strongest, followed by addition operators, comparison operators, && (logical AND), and finally || (logical OR) Binary operators of the same precedence associate from left to right. For instance, x / y * z is the same as (x / y) * z. Note that the operator precedence is reflected explicitly by the grammar. Arithmetic operators apply to numeric values and yield a result of the same type as the first operand. The four standard arithmetic operators (+, -, *, /) apply to integer, rational, floating-point, and complex types; + also applies to strings; +,- also applies to times. All other arithmetic operators apply to integers only. sum integers, rationals, floats, complex values, strings difference integers, rationals, floats, complex values, times product integers, rationals, floats, complex values / quotient integers, rationals, floats, complex values % remainder integers & bitwise AND integers | bitwise OR integers ^ bitwise XOR integers &^ bit clear (AND NOT) integers << left shift integer << unsigned integer >> right shift integer >> unsigned integer Strings can be concatenated using the + operator String addition creates a new string by concatenating the operands. A value of type duration can be added to or subtracted from a value of type time. Times can subtracted from each other producing a value of type duration. For two integer values x and y, the integer quotient q = x / y and remainder r = x % y satisfy the following relationships with x / y truncated towards zero ("truncated division"). As an exception to this rule, if the dividend x is the most negative value for the int type of x, the quotient q = x / -1 is equal to x (and r = 0). If the divisor is a constant expression, it must not be zero. If the divisor is zero at run time, a run-time error occurs. If the dividend is non-negative and the divisor is a constant power of 2, the division may be replaced by a right shift, and computing the remainder may be replaced by a bitwise AND operation The shift operators shift the left operand by the shift count specified by the right operand. They implement arithmetic shifts if the left operand is a signed integer and logical shifts if it is an unsigned integer. There is no upper limit on the shift count. Shifts behave as if the left operand is shifted n times by 1 for a shift count of n. As a result, x << 1 is the same as x*2 and x >> 1 is the same as x/2 but truncated towards negative infinity. For integer operands, the unary operators +, -, and ^ are defined as follows For floating-point and complex numbers, +x is the same as x, while -x is the negation of x. The result of a floating-point or complex division by zero is not specified beyond the IEEE-754 standard; whether a run-time error occurs is implementation-specific. Whenever any operand of any arithmetic operation, unary or binary, is NULL, as well as in the case of the string concatenating operation, the result is NULL. For unsigned integer values, the operations +, -, *, and << are computed modulo 2n, where n is the bit width of the unsigned integer's type. Loosely speaking, these unsigned integer operations discard high bits upon overflow, and expressions may rely on “wrap around”. For signed integers with a finite bit width, the operations +, -, *, and << may legally overflow and the resulting value exists and is deterministically defined by the signed integer representation, the operation, and its operands. No exception is raised as a result of overflow. An evaluator may not optimize an expression under the assumption that overflow does not occur. For instance, it may not assume that x < x + 1 is always true. Integers of type bigint and rationals do not overflow but their handling is limited by the memory resources available to the program. Comparison operators compare two operands and yield a boolean value. In any comparison, the first operand must be of same type as is the second operand, or vice versa. The equality operators == and != apply to operands that are comparable. The ordering operators <, <=, >, and >= apply to operands that are ordered. These terms and the result of the comparisons are defined as follows - Boolean values are comparable. Two boolean values are equal if they are either both true or both false. - Complex values are comparable. Two complex values u and v are equal if both real(u) == real(v) and imag(u) == imag(v). - Integer values are comparable and ordered, in the usual way. Note that durations are integers. - Floating point values are comparable and ordered, as defined by the IEEE-754 standard. - Rational values are comparable and ordered, in the usual way. - String values are comparable and ordered, lexically byte-wise. - Time values are comparable and ordered. Whenever any operand of any comparison operation is NULL, the result is NULL. Note that slices are always of type string. Logical operators apply to boolean values and yield a boolean result. The right operand is evaluated conditionally. The truth tables for logical operations with NULL values Conversions are expressions of the form T(x) where T is a type and x is an expression that can be converted to type T. A constant value x can be converted to type T in any of these cases: - x is representable by a value of type T. - x is a floating-point constant, T is a floating-point type, and x is representable by a value of type T after rounding using IEEE 754 round-to-even rules. The constant T(x) is the rounded value. - x is an integer constant and T is a string type. The same rule as for non-constant x applies in this case. Converting a constant yields a typed constant as result. A non-constant value x can be converted to type T in any of these cases: - x has type T. - x's type and T are both integer or floating point types. - x's type and T are both complex types. - x is an integer, except bigint or duration, and T is a string type. Specific rules apply to (non-constant) conversions between numeric types or to and from a string type. These conversions may change the representation of x and incur a run-time cost. All other conversions only change the type but not the representation of x. A conversion of NULL to any type yields NULL. For the conversion of non-constant numeric values, the following rules apply 1. When converting between integer types, if the value is a signed integer, it is sign extended to implicit infinite precision; otherwise it is zero extended. It is then truncated to fit in the result type's size. For example, if v == uint16(0x10F0), then uint32(int8(v)) == 0xFFFFFFF0. The conversion always yields a valid value; there is no indication of overflow. 2. When converting a floating-point number to an integer, the fraction is discarded (truncation towards zero). 3. When converting an integer or floating-point number to a floating-point type, or a complex number to another complex type, the result value is rounded to the precision specified by the destination type. For instance, the value of a variable x of type float32 may be stored using additional precision beyond that of an IEEE-754 32-bit number, but float32(x) represents the result of rounding x's value to 32-bit precision. Similarly, x + 0.1 may use more than 32 bits of precision, but float32(x + 0.1) does not. In all non-constant conversions involving floating-point or complex values, if the result type cannot represent the value the conversion succeeds but the result value is implementation-dependent. 1. Converting a signed or unsigned integer value to a string type yields a string containing the UTF-8 representation of the integer. Values outside the range of valid Unicode code points are converted to "\uFFFD". 2. Converting a blob to a string type yields a string whose successive bytes are the elements of the blob. 3. Converting a value of a string type to a blob yields a blob whose successive elements are the bytes of the string. 4. Converting a value of a bigint type to a string yields a string containing the decimal decimal representation of the integer. 5. Converting a value of a string type to a bigint yields a bigint value containing the integer represented by the string value. A prefix of “0x” or “0X” selects base 16; the “0” prefix selects base 8, and a “0b” or “0B” prefix selects base 2. Otherwise the value is interpreted in base 10. An error occurs if the string value is not in any valid format. 6. Converting a value of a rational type to a string yields a string containing the decimal decimal representation of the rational in the form "a/b" (even if b == 1). 7. Converting a value of a string type to a bigrat yields a bigrat value containing the rational represented by the string value. The string can be given as a fraction "a/b" or as a floating-point number optionally followed by an exponent. An error occurs if the string value is not in any valid format. 8. Converting a value of a duration type to a string returns a string representing the duration in the form "72h3m0.5s". Leading zero units are omitted. As a special case, durations less than one second format using a smaller unit (milli-, micro-, or nanoseconds) to ensure that the leading digit is non-zero. The zero duration formats as 0, with no unit. 9. Converting a string value to a duration yields a duration represented by the string. A duration string is a possibly signed sequence of decimal numbers, each with optional fraction and a unit suffix, such as "300ms", "-1.5h" or "2h45m". Valid time units are "ns", "us" (or "µs"), "ms", "s", "m", "h". 10. Converting a time value to a string returns the time formatted using the format string When evaluating the operands of an expression or of function calls, operations are evaluated in lexical left-to-right order. For example, in the evaluation of the function calls and evaluation of c happen in the order h(), i(), j(), c. Floating-point operations within a single expression are evaluated according to the associativity of the operators. Explicit parentheses affect the evaluation by overriding the default associativity. In the expression x + (y + z) the addition y + z is performed before adding x. Statements control execution. The empty statement does nothing. Alter table statements modify existing tables. With the ADD clause it adds a new column to the table. The column must not exist. With the DROP clause it removes an existing column from a table. The column must exist and it must be not the only (last) column of the table. IOW, there cannot be a table with no columns. For example When adding a column to a table with existing data, the constraint clause of the ColumnDef cannot be used. Adding a constrained column to an empty table is fine. Begin transactions statements introduce a new transaction level. Every transaction level must be eventually balanced by exactly one of COMMIT or ROLLBACK statements. Note that when a transaction is roll-backed because of a statement failure then no explicit balancing of the respective BEGIN TRANSACTION is statement is required nor permitted. Failure to properly balance any opened transaction level may cause dead locks and/or lose of data updated in the uppermost opened but never properly closed transaction level. For example A database cannot be updated (mutated) outside of a transaction. Statements requiring a transaction A database is effectively read only outside of a transaction. Statements not requiring a transaction The commit statement closes the innermost transaction nesting level. If that's the outermost level then the updates to the DB made by the transaction are atomically made persistent. For example Create index statements create new indices. Index is a named projection of ordered values of a table column to the respective records. As a special case the id() of the record can be indexed. Index name must not be the same as any of the existing tables and it also cannot be the same as of any column name of the table the index is on. For example Now certain SELECT statements may use the indices to speed up joins and/or to speed up record set filtering when the WHERE clause is used; or the indices might be used to improve the performance when the ORDER BY clause is present. The UNIQUE modifier requires the indexed values tuple to be index-wise unique or have all values NULL. The optional IF NOT EXISTS clause makes the statement a no operation if the index already exists. A simple index consists of only one expression which must be either a column name or the built-in id(). A more complex and more general index is one that consists of more than one expression or its single expression does not qualify as a simple index. In this case the type of all expressions in the list must be one of the non blob-like types. Note: Blob-like types are blob, bigint, bigrat, time and duration. Create table statements create new tables. A column definition declares the column name and type. Table names and column names are case sensitive. Neither a table or an index of the same name may exist in the DB. For example The optional IF NOT EXISTS clause makes the statement a no operation if the table already exists. The optional constraint clause has two forms. The first one is found in many SQL dialects. This form prevents the data in column DepartmentName to be NULL. The second form allows an arbitrary boolean expression to be used to validate the column. If the value of the expression is true then the validation succeeded. If the value of the expression is false or NULL then the validation fails. If the value of the expression is not of type bool an error occurs. The optional DEFAULT clause is an expression which, if present, is substituted instead of a NULL value when the colum is assigned a value. Note that the constraint and/or default expressions may refer to other columns by name: When a table row is inserted by the INSERT INTO statement or when a table row is updated by the UPDATE statement, the order of operations is as follows: 1. The new values of the affected columns are set and the values of all the row columns become the named values which can be referred to in default expressions evaluated in step 2. 2. If any row column value is NULL and the DEFAULT clause is present in the column's definition, the default expression is evaluated and its value is set as the respective column value. 3. The values, potentially updated, of row columns become the named values which can be referred to in constraint expressions evaluated during step 4. 4. All row columns which definition has the constraint clause present will have that constraint checked. If any constraint violation is detected, the overall operation fails and no changes to the table are made. Delete from statements remove rows from a table, which must exist. For example If the WHERE clause is not present then all rows are removed and the statement is equivalent to the TRUNCATE TABLE statement. Drop index statements remove indices from the DB. The index must exist. For example The optional IF EXISTS clause makes the statement a no operation if the index does not exist. Drop table statements remove tables from the DB. The table must exist. For example The optional IF EXISTS clause makes the statement a no operation if the table does not exist. Insert into statements insert new rows into tables. New rows come from literal data, if using the VALUES clause, or are a result of select statement. In the later case the select statement is fully evaluated before the insertion of any rows is performed, allowing to insert values calculated from the same table rows are to be inserted into. If the ColumnNameList part is omitted then the number of values inserted in the row must be the same as are columns in the table. If the ColumnNameList part is present then the number of values per row must be same as the same number of column names. All other columns of the record are set to NULL. The type of the value assigned to a column must be the same as is the column's type or the value must be NULL. For example If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. Explain statement produces a recordset consisting of lines of text which describe the execution plan of a statement, if any. For example, the QL tool treats the explain statement specially and outputs the joined lines: The explanation may aid in uderstanding how a statement/query would be executed and if indices are used as expected - or which indices may possibly improve the statement performance. The create index statements above were directly copy/pasted in the terminal from the suggestions provided by the filter recordset pipeline part returned by the explain statement. If the statement has nothing special in its plan, the result is the original statement. To get an explanation of the select statement of the IN predicate, use the EXPLAIN statement with that particular select statement. The rollback statement closes the innermost transaction nesting level discarding any updates to the DB made by it. If that's the outermost level then the effects on the DB are as if the transaction never happened. For example The (temporary) record set from the last statement is returned and can be processed by the client. In this case the rollback is the same as 'DROP TABLE tmp;' but it can be a more complex operation. Select from statements produce recordsets. The optional DISTINCT modifier ensures all rows in the result recordset are unique. Either all of the resulting fields are returned ('*') or only those named in FieldList. RecordSetList is a list of table names or parenthesized select statements, optionally (re)named using the AS clause. The result can be filtered using a WhereClause and orderd by the OrderBy clause. For example If Recordset is a nested, parenthesized SelectStmt then it must be given a name using the AS clause if its field are to be accessible in expressions. A field is an named expression. Identifiers, not used as a type in conversion or a function name in the Call clause, denote names of (other) fields, values of which should be used in the expression. The expression can be named using the AS clause. If the AS clause is not present and the expression consists solely of a field name, then that field name is used as the name of the resulting field. Otherwise the field is unnamed. For example The SELECT statement can optionally enumerate the desired/resulting fields in a list. No two identical field names can appear in the list. When more than one record set is used in the FROM clause record set list, the result record set field names are rewritten to be qualified using the record set names. If a particular record set doesn't have a name, its respective fields became unnamed. The optional JOIN clause, for example is mostly equal to except that the rows from a which, when they appear in the cross join, never made expr to evaluate to true, are combined with a virtual row from b, containing all nulls, and added to the result set. For the RIGHT JOIN variant the discussed rules are used for rows from b not satisfying expr == true and the virtual, all-null row "comes" from a. The FULL JOIN adds the respective rows which would be otherwise provided by the separate executions of the LEFT JOIN and RIGHT JOIN variants. For more thorough OUTER JOIN discussion please see the Wikipedia article at [10]. Resultins rows of a SELECT statement can be optionally ordered by the ORDER BY clause. Collating proceeds by considering the expressions in the expression list left to right until a collating order is determined. Any possibly remaining expressions are not evaluated. All of the expression values must yield an ordered type or NULL. Ordered types are defined in "Comparison operators". Collating of elements having a NULL value is different compared to what the comparison operators yield in expression evaluation (NULL result instead of a boolean value). Below, T denotes a non NULL value of any QL type. NULL collates before any non NULL value (is considered smaller than T). Two NULLs have no collating order (are considered equal). The WHERE clause restricts records considered by some statements, like SELECT FROM, DELETE FROM, or UPDATE. It is an error if the expression evaluates to a non null value of non bool type. The GROUP BY clause is used to project rows having common values into a smaller set of rows. For example Using the GROUP BY without any aggregate functions in the selected fields is in certain cases equal to using the DISTINCT modifier. The last two examples above produce the same resultsets. The optional OFFSET clause allows to ignore first N records. For example The above will produce only rows 11, 12, ... of the record set, if they exist. The value of the expression must a non negative integer, but not bigint or duration. The optional LIMIT clause allows to ignore all but first N records. For example The above will return at most the first 10 records of the record set. The value of the expression must a non negative integer, but not bigint or duration. The LIMIT and OFFSET clauses can be combined. For example Considering table t has, say 10 records, the above will produce only records 4 - 8. After returning record #8, no more result rows/records are computed. 1. The FROM clause is evaluated, producing a Cartesian product of its source record sets (tables or nested SELECT statements). 2. If present, the JOIN cluase is evaluated on the result set of the previous evaluation and the recordset specified by the JOIN clause. (... JOIN Recordset ON ...) 3. If present, the WHERE clause is evaluated on the result set of the previous evaluation. 4. If present, the GROUP BY clause is evaluated on the result set of the previous evaluation(s). 5. The SELECT field expressions are evaluated on the result set of the previous evaluation(s). 6. If present, the DISTINCT modifier is evaluated on the result set of the previous evaluation(s). 7. If present, the ORDER BY clause is evaluated on the result set of the previous evaluation(s). 8. If present, the OFFSET clause is evaluated on the result set of the previous evaluation(s). The offset expression is evaluated once for the first record produced by the previous evaluations. 9. If present, the LIMIT clause is evaluated on the result set of the previous evaluation(s). The limit expression is evaluated once for the first record produced by the previous evaluations. Truncate table statements remove all records from a table. The table must exist. For example Update statements change values of fields in rows of a table. For example Note: The SET clause is optional. If any of the columns of the table were defined using the optional constraints clause or the optional defaults clause then those are processed on a per row basis. The details are discussed in the "Constraints and defaults" chapter below the CREATE TABLE statement documentation. To allow to query for DB meta data, there exist specially named tables, some of them being virtual. Note: Virtual system tables may have fake table-wise unique but meaningless and unstable record IDs. Do not apply the built-in id() to any system table. The table __Table lists all tables in the DB. The schema is The Schema column returns the statement to (re)create table Name. This table is virtual. The table __Colum lists all columns of all tables in the DB. The schema is The Ordinal column defines the 1-based index of the column in the record. This table is virtual. The table __Colum2 lists all columns of all tables in the DB which have the constraint NOT NULL or which have a constraint expression defined or which have a default expression defined. The schema is It's possible to obtain a consolidated recordset for all properties of all DB columns using The Name column is the column name in TableName. The table __Index lists all indices in the DB. The schema is The IsUnique columns reflects if the index was created using the optional UNIQUE clause. This table is virtual. Built-in functions are predeclared. The built-in aggregate function avg returns the average of values of an expression. Avg ignores NULL values, but returns NULL if all values of a column are NULL or if avg is applied to an empty record set. The column values must be of a numeric type. The built-in function contains returns true if substr is within s. If any argument to contains is NULL the result is NULL. The built-in aggregate function count returns how many times an expression has a non NULL values or the number of rows in a record set. Note: count() returns 0 for an empty record set. For example Date returns the time corresponding to in the appropriate zone for that time in the given location. The month, day, hour, min, sec, and nsec values may be outside their usual ranges and will be normalized during the conversion. For example, October 32 converts to November 1. A daylight savings time transition skips or repeats times. For example, in the United States, March 13, 2011 2:15am never occurred, while November 6, 2011 1:15am occurred twice. In such cases, the choice of time zone, and therefore the time, is not well-defined. Date returns a time that is correct in one of the two zones involved in the transition, but it does not guarantee which. A location maps time instants to the zone in use at that time. Typically, the location represents the collection of time offsets in use in a geographical area, such as "CEST" and "CET" for central Europe. "local" represents the system's local time zone. "UTC" represents Universal Coordinated Time (UTC). The month specifies a month of the year (January = 1, ...). If any argument to date is NULL the result is NULL. The built-in function day returns the day of the month specified by t. If the argument to day is NULL the result is NULL. The built-in function formatTime returns a textual representation of the time value formatted according to layout, which defines the format by showing how the reference time, would be displayed if it were the value; it serves as an example of the desired output. The same display rules will then be applied to the time value. If any argument to formatTime is NULL the result is NULL. NOTE: The string value of the time zone, like "CET" or "ACDT", is dependent on the time zone of the machine the function is run on. For example, if the t value is in "CET", but the machine is in "ACDT", instead of "CET" the result is "+0100". This is the same what Go (time.Time).String() returns and in fact formatTime directly calls t.String(). returns on a machine in the CET time zone, but may return on a machine in the ACDT zone. The time value is in both cases the same so its ordering and comparing is correct. Only the display value can differ. The built-in functions formatFloat and formatInt format numbers to strings using go's number format functions in the `strconv` package. For all three functions, only the first argument is mandatory. The default values of the rest are shown in the examples. If the first argument is NULL, the result is NULL. returns returns returns Unlike the `strconv` equivalent, the formatInt function handles all integer types, both signed and unsigned. The built-in function hasPrefix tests whether the string s begins with prefix. If any argument to hasPrefix is NULL the result is NULL. The built-in function hasSuffix tests whether the string s ends with suffix. If any argument to hasSuffix is NULL the result is NULL. The built-in function hour returns the hour within the day specified by t, in the range [0, 23]. If the argument to hour is NULL the result is NULL. The built-in function hours returns the duration as a floating point number of hours. If the argument to hours is NULL the result is NULL. The built-in function id takes zero or one arguments. If no argument is provided, id() returns a table-unique automatically assigned numeric identifier of type int. Ids of deleted records are not reused unless the DB becomes completely empty (has no tables). For example If id() without arguments is called for a row which is not a table record then the result value is NULL. For example If id() has one argument it must be a table name of a table in a cross join. For example The built-in function len takes a string argument and returns the lentgh of the string in bytes. The expression len(s) is constant if s is a string constant. If the argument to len is NULL the result is NULL. The built-in aggregate function max returns the largest value of an expression in a record set. Max ignores NULL values, but returns NULL if all values of a column are NULL or if max is applied to an empty record set. The expression values must be of an ordered type. For example The built-in aggregate function min returns the smallest value of an expression in a record set. Min ignores NULL values, but returns NULL if all values of a column are NULL or if min is applied to an empty record set. For example The column values must be of an ordered type. The built-in function minute returns the minute offset within the hour specified by t, in the range [0, 59]. If the argument to minute is NULL the result is NULL. The built-in function minutes returns the duration as a floating point number of minutes. If the argument to minutes is NULL the result is NULL. The built-in function month returns the month of the year specified by t (January = 1, ...). If the argument to month is NULL the result is NULL. The built-in function nanosecond returns the nanosecond offset within the second specified by t, in the range [0, 999999999]. If the argument to nanosecond is NULL the result is NULL. The built-in function nanoseconds returns the duration as an integer nanosecond count. If the argument to nanoseconds is NULL the result is NULL. The built-in function now returns the current local time. The built-in function parseTime parses a formatted string and returns the time value it represents. The layout defines the format by showing how the reference time, would be interpreted if it were the value; it serves as an example of the input format. The same interpretation will then be made to the input string. Elements omitted from the value are assumed to be zero or, when zero is impossible, one, so parsing "3:04pm" returns the time corresponding to Jan 1, year 0, 15:04:00 UTC (note that because the year is 0, this time is before the zero Time). Years must be in the range 0000..9999. The day of the week is checked for syntax but it is otherwise ignored. In the absence of a time zone indicator, parseTime returns a time in UTC. When parsing a time with a zone offset like -0700, if the offset corresponds to a time zone used by the current location, then parseTime uses that location and zone in the returned time. Otherwise it records the time as being in a fabricated location with time fixed at the given zone offset. When parsing a time with a zone abbreviation like MST, if the zone abbreviation has a defined offset in the current location, then that offset is used. The zone abbreviation "UTC" is recognized as UTC regardless of location. If the zone abbreviation is unknown, Parse records the time as being in a fabricated location with the given zone abbreviation and a zero offset. This choice means that such a time can be parses and reformatted with the same layout losslessly, but the exact instant used in the representation will differ by the actual zone offset. To avoid such problems, prefer time layouts that use a numeric zone offset. If any argument to parseTime is NULL the result is NULL. The built-in function second returns the second offset within the minute specified by t, in the range [0, 59]. If the argument to second is NULL the result is NULL. The built-in function seconds returns the duration as a floating point number of seconds. If the argument to seconds is NULL the result is NULL. The built-in function since returns the time elapsed since t. It is shorthand for now()-t. If the argument to since is NULL the result is NULL. The built-in aggregate function sum returns the sum of values of an expression for all rows of a record set. Sum ignores NULL values, but returns NULL if all values of a column are NULL or if sum is applied to an empty record set. The column values must be of a numeric type. The built-in function timeIn returns t with the location information set to loc. For discussion of the loc argument please see date(). If any argument to timeIn is NULL the result is NULL. The built-in function weekday returns the day of the week specified by t. Sunday == 0, Monday == 1, ... If the argument to weekday is NULL the result is NULL. The built-in function year returns the year in which t occurs. If the argument to year is NULL the result is NULL. The built-in function yearDay returns the day of the year specified by t, in the range [1,365] for non-leap years, and [1,366] in leap years. If the argument to yearDay is NULL the result is NULL. Three functions assemble and disassemble complex numbers. The built-in function complex constructs a complex value from a floating-point real and imaginary part, while real and imag extract the real and imaginary parts of a complex value. The type of the arguments and return value correspond. For complex, the two arguments must be of the same floating-point type and the return type is the complex type with the corresponding floating-point constituents: complex64 for float32, complex128 for float64. The real and imag functions together form the inverse, so for a complex value z, z == complex(real(z), imag(z)). If the operands of these functions are all constants, the return value is a constant. If any argument to any of complex, real, imag functions is NULL the result is NULL. For the numeric types, the following sizes are guaranteed Portions of this specification page are modifications based on work[2] created and shared by Google[3] and used according to terms described in the Creative Commons 3.0 Attribution License[4]. This specification is licensed under the Creative Commons Attribution 3.0 License, and code is licensed under a BSD license[5]. Links from the above documentation This section is not part of the specification. WARNING: The implementation of indices is new and it surely needs more time to become mature. Indices are used currently used only by the WHERE clause. The following expression patterns of 'WHERE expression' are recognized and trigger index use. The relOp is one of the relation operators <, <=, ==, >=, >. For the equality operator both operands must be of comparable types. For all other operators both operands must be of ordered types. The constant expression is a compile time constant expression. Some constant folding is still a TODO. Parameter is a QL parameter ($1 etc.). Consider tables t and u, both with an indexed field f. The WHERE expression doesn't comply with the above simple detected cases. However, such query is now automatically rewritten to which will use both of the indices. The impact of using the indices can be substantial (cf. BenchmarkCrossJoin*) if the resulting rows have low "selectivity", ie. only few rows from both tables are selected by the respective WHERE filtering. Note: Existing QL DBs can be used and indices can be added to them. However, once any indices are present in the DB, the old QL versions cannot work with such DB anymore. Running a benchmark with -v (-test.v) outputs information about the scale used to report records/s and a brief description of the benchmark. For example Running the full suite of benchmarks takes a lot of time. Use the -timeout flag to avoid them being killed after the default time limit (10 minutes).

Package awk implements AWK-style processing of input streams. The awk package can be considered a shallow EDSL (embedded domain-specific language) for Go that facilitates text processing. It aims to implement the core semantics provided by AWK, a pattern scanning and processing language defined as part of the POSIX 1003.1 standard (http://pubs.opengroup.org/onlinepubs/9699919799/utilities/awk.html) and therefore part of all standard Linux/Unix distributions. AWK's forte is simple transformations of tabular data. For example, the following is a complete AWK program that reads an entire file from the standard input device, splits each file into whitespace-separated columns, and outputs all lines in which the fifth column is an odd number: Here's a typical Go analogue of that one-line AWK program: The goal of the awk package is to emulate AWK's simplicity while simultaneously taking advantage of Go's speed, safety, and flexibility. With the awk package, the preceding code reduces to the following: While not a one-liner like the original AWK program, the above is conceptually close to it. The AppendStmt method defines a script in terms of patterns and actions exactly as in the AWK program. The Run method then runs the script on an input stream, which can be any io.Reader. For those programmers unfamiliar with AWK, an AWK program consists of a sequence of pattern/action pairs. Each pattern that matches a given line causes the corresponding action to be performed. AWK programs tend to be terse because AWK implicitly reads the input file, splits it into records (default: newline-terminated lines), and splits each record into fields (default: whitespace-separated columns), saving the programmer from having to express such operations explicitly. Furthermore, AWK provides a default pattern, which matches every record, and a default action, which outputs a record unmodified. The awk package attempts to mimic those semantics in Go. Basic usage consists of three steps: 1. Script allocation (awk.NewScript) 2. Script definition (Script.AppendStmt) 3. Script execution (Script.Run) In Step 2, AppendStmt is called once for each pattern/action pair that is to be appended to the script. The same script can be applied to multiple input streams by re-executing Step 3. Actions to be executed on every run of Step 3 can be supplied by assigning the script's Begin and End fields. The Begin action is typically used to initialize script state by calling methods such as SetRS and SetFS and assigning user-defined data to the script's State field (what would be global variables in AWK). The End action is typically used to store or report final results. To mimic AWK's dynamic type system. the awk package provides the Value and ValueArray types. Value represents a scalar that can be coerced without error to a string, an int, or a float64. ValueArray represents a—possibly multidimensional—associative array of Values. Both patterns and actions can access the current record's fields via the script's F method, which takes a 1-based index and returns the corresponding field as a Value. An index of 0 returns the entire record as a Value. The following AWK features and GNU AWK extensions are currently supported by the awk package: • the basic pattern/action structure of an AWK script, including BEGIN and END rules and range patterns • control over record separation (RS), including regular expressions and null strings (implying blank lines as separators) • control over field separation (FS), including regular expressions and null strings (implying single-character fields) • fixed-width fields (FIELDWIDTHS) • fields defined by a regular expression (FPAT) • control over case-sensitive vs. case-insensitive comparisons (IGNORECASE) • control over the number conversion format (CONVFMT) • automatic enumeration of records (NR) and fields (NR) • "weak typing" • multidimensional associative arrays • premature termination of record processing (next) and script processing (exit) • explicit record reading (getline) from either the current stream or a specified stream • maintenance of regular-expression status variables (RT, RSTART, and RLENGTH) For more information about AWK and its features, see the awk(1) manual page on any Linux/Unix system (available online from, e.g., http://linux.die.net/man/1/awk) or read the book, "The AWK Programming Language" by Aho, Kernighan, and Weinberger. A number of examples ported from the POSIX 1003.1 standard document (http://pubs.opengroup.org/onlinepubs/9699919799/utilities/awk.html) are presented below.

Command pigeon generates parsers in Go from a PEG grammar. From Wikipedia [0]: Its features and syntax are inspired by the PEG.js project [1], while the implementation is loosely based on [2]. Formal presentation of the PEG theory by Bryan Ford is also an important reference [3]. An introductory blog post can be found at [4]. The pigeon tool must be called with PEG input as defined by the accepted PEG syntax below. The grammar may be provided by a file or read from stdin. The generated parser is written to stdout by default. The following options can be specified: The tool makes no attempt to format the code, nor to detect the required imports. It is recommended to use goimports to properly generate the output code: The goimports tool can be installed with: If the code blocks in the grammar (see below, section "Code block") are golint- and go vet-compliant, then the resulting generated code will also be golint- and go vet-compliant. The generated code doesn't use any third-party dependency unless code blocks in the grammar require such a dependency. The accepted syntax for the grammar is formally defined in the grammar/pigeon.peg file, using the PEG syntax. What follows is an informal description of this syntax. Identifiers, whitespace, comments and literals follow the same notation as the Go language, as defined in the language specification (http://golang.org/ref/spec#Source_code_representation): The grammar must be Unicode text encoded in UTF-8. New lines are identified by the \n character (U+000A). Space (U+0020), horizontal tabs (U+0009) and carriage returns (U+000D) are considered whitespace and are ignored except to separate tokens. A PEG grammar consists of a set of rules. A rule is an identifier followed by a rule definition operator and an expression. An optional display name - a string literal used in error messages instead of the rule identifier - can be specified after the rule identifier. E.g.: The rule definition operator can be any one of those: A rule is defined by an expression. The following sections describe the various expression types. Expressions can be grouped by using parentheses, and a rule can be referenced by its identifier in place of an expression. The choice expression is a list of expressions that will be tested in the order they are defined. The first one that matches will be used. Expressions are separated by the forward slash character "/". E.g.: Because the first match is used, it is important to think about the order of expressions. For example, in this rule, "<=" would never be used because the "<" expression comes first: The sequence expression is a list of expressions that must all match in that same order for the sequence expression to be considered a match. Expressions are separated by whitespace. E.g.: A labeled expression consists of an identifier followed by a colon ":" and an expression. A labeled expression introduces a variable named with the label that can be referenced in the code blocks in the same scope. The variable will have the value of the expression that follows the colon. E.g.: The variable is typed as an empty interface, and the underlying type depends on the following: For terminals (character and string literals, character classes and the any matcher), the value is []byte. E.g.: For predicates (& and !), the value is always nil. E.g.: For a sequence, the value is a slice of empty interfaces, one for each expression value in the sequence. The underlying types of each value in the slice follow the same rules described here, recursively. E.g.: For a repetition (+ and *), the value is a slice of empty interfaces, one for each repetition. The underlying types of each value in the slice follow the same rules described here, recursively. E.g.: For a choice expression, the value is that of the matching choice. E.g.: For the optional expression (?), the value is nil or the value of the expression. E.g.: Of course, the type of the value can be anything once an action code block is used. E.g.: An expression prefixed with the ampersand "&" is the "and" predicate expression: it is considered a match if the following expression is a match, but it does not consume any input. An expression prefixed with the exclamation point "!" is the "not" predicate expression: it is considered a match if the following expression is not a match, but it does not consume any input. E.g.: The expression following the & and ! operators can be a code block. In that case, the code block must return a bool and an error. The operator's semantic is the same, & is a match if the code block returns true, ! is a match if the code block returns false. The code block has access to any labeled value defined in its scope. E.g.: An expression followed by "*", "?" or "+" is a match if the expression occurs zero or more times ("*"), zero or one time "?" or one or more times ("+") respectively. The match is greedy, it will match as many times as possible. E.g. A literal matcher tries to match the input against a single character or a string literal. The literal may be a single-quoted single character, a double-quoted string or a backtick-quoted raw string. The same rules as in Go apply regarding the allowed characters and escapes. The literal may be followed by a lowercase "i" (outside the ending quote) to indicate that the match is case-insensitive. E.g.: A character class matcher tries to match the input against a class of characters inside square brackets "[...]". Inside the brackets, characters represent themselves and the same escapes as in string literals are available, except that the single- and double-quote escape is not valid, instead the closing square bracket "]" must be escaped to be used. Character ranges can be specified using the "[a-z]" notation. Unicode classes can be specified using the "[\pL]" notation, where L is a single-letter Unicode class of characters, or using the "[\p{Class}]" notation where Class is a valid Unicode class (e.g. "Latin"). As for string literals, a lowercase "i" may follow the matcher (outside the ending square bracket) to indicate that the match is case-insensitive. A "^" as first character inside the square brackets indicates that the match is inverted (it is a match if the input does not match the character class matcher). E.g.: The any matcher is represented by the dot ".". It matches any character except the end of file, thus the "!." expression is used to indicate "match the end of file". E.g.: Code blocks can be added to generate custom Go code. There are three kinds of code blocks: the initializer, the action and the predicate. All code blocks appear inside curly braces "{...}". The initializer must appear first in the grammar, before any rule. It is copied as-is (minus the wrapping curly braces) at the top of the generated parser. It may contain function declarations, types, variables, etc. just like any Go file. Every symbol declared here will be available to all other code blocks. Although the initializer is optional in a valid grammar, it is usually required to generate a valid Go source code file (for the package clause). E.g.: Action code blocks are code blocks declared after an expression in a rule. Those code blocks are turned into a method on the "*current" type in the generated source code. The method receives any labeled expression's value as argument (as interface{}) and must return two values, the first being the value of the expression (an interface{}), and the second an error. If a non-nil error is returned, it is added to the list of errors that the parser will return. E.g.: Predicate code blocks are code blocks declared immediately after the and "&" or the not "!" operators. Like action code blocks, predicate code blocks are turned into a method on the "*current" type in the generated source code. The method receives any labeled expression's value as argument (as interface{}) and must return two values, the first being a bool and the second an error. If a non-nil error is returned, it is added to the list of errors that the parser will return. E.g.: The current type is a struct that provides two useful fields that can be accessed in action and predicate code blocks: "pos" and "text". The "pos" field indicates the current position of the parser in the source input. It is itself a struct with three fields: "line", "col" and "offset". Line is a 1-based line number, col is a 1-based column number that counts runes from the start of the line, and offset is a 0-based byte offset. The "text" field is the slice of bytes of the current match. It is empty in a predicate code block. The parser generated by pigeon exports a few symbols so that it can be used as a package with public functions to parse input text. The exported API is: See the godoc page of the generated parser for the test/predicates grammar for an example documentation page of the exported API: http://godoc.org/github.com/mna/pigeon/test/predicates. Like the grammar used to generate the parser, the input text must be UTF-8-encoded Unicode. The start rule of the parser is the first rule in the PEG grammar used to generate the parser. A call to any of the Parse* functions returns the value generated by executing the grammar on the provided input text, and an optional error. Typically, the grammar should generate some kind of abstract syntax tree (AST), but for simple grammars it may evaluate the result immediately, such as in the examples/calculator example. There are no constraints imposed on the author of the grammar, it can return whatever is needed. When the parser returns a non-nil error, the error is always of type errList, which is defined as a slice of errors ([]error). Each error in the list is of type *parserError. This is a struct that has an "Inner" field that can be used to access the original error. So if a code block returns some well-known error like: The original error can be accessed this way: By defaut the parser will continue after an error is returned and will cumulate all errors found during parsing. If the grammar reaches a point where it shouldn't continue, a panic statement can be used to terminate parsing. The panic will be caught at the top-level of the Parse* call and will be converted into a *parserError like any error, and an errList will still be returned to the caller. The divide by zero error in the examples/calculator grammar leverages this feature (no special code is needed to handle division by zero, if it happens, the runtime panics and it is recovered and returned as a parsing error). Providing good error reporting in a parser is not a trivial task. Part of it is provided by the pigeon tool, by offering features such as filename, position and rule name in the error message, but an important part of good error reporting needs to be done by the grammar author. For example, many programming languages use double-quotes for string literals. Usually, if the opening quote is found, the closing quote is expected, and if none is found, there won't be any other rule that will match, there's no need to backtrack and try other choices, an error should be added to the list and the match should be consumed. In order to do this, the grammar can look something like this: This is just one example, but it illustrates the idea that error reporting needs to be thought out when designing the grammar. Generated parsers have user-provided code mixed with pigeon code in the same package, so there is no package boundary in the resulting code to prevent access to unexported symbols. What is meant to be implementation details in pigeon is also available to user code - which doesn't mean it should be used. For this reason, it is important to precisely define what is intended to be the supported API of pigeon, the parts that will be stable in future versions. The "stability" of the API attempts to make a similar guarantee as the Go 1 compatibility [5]. The following lists what part of the current pigeon code falls under that guarantee (features may be added in the future): The pigeon command-line flags and arguments: those will not be removed and will maintain the same semantics. The explicitly exported API generated by pigeon. See [6] for the documentation of this API on a generated parser. The PEG syntax, as documented above. The code blocks (except the initializer) will always be generated as methods on the *current type, and this type is guaranteed to have the fields pos (type position) and text (type []byte). There are no guarantees on other fields and methods of this type. The position type will always have the fields line, col and offset, all defined as int. There are no guarantees on other fields and methods of this type. The type of the error value returned by the Parse* functions, when not nil, will always be errList defined as a []error. There are no guarantees on methods of this type, other than the fact it implements the error interface. Individual errors in the errList will always be of type *parserError, and this type is guaranteed to have an Inner field that contains the original error value. There are no guarantees on other fields and methods of this type. References:

Command mox is a modern, secure, full-featured, open source mail server for low-maintenance self-hosted email. Mox is started with the "serve" subcommand, but mox also has many other subcommands. Many of those commands talk to a running mox instance, through the ctl file in the data directory. Specify the configuration file (that holds the path to the data directory) through the -config flag or MOXCONF environment variable. Commands that don't talk to a running mox instance are often for testing/debugging email functionality. For example for parsing an email message, or looking up SPF/DKIM/DMARC records. Below is the usage information as printed by the command when started without any parameters. Followed by the help and usage information for each command. Start mox, serving SMTP/IMAP/HTTPS. Incoming email is accepted over SMTP. Email can be retrieved by users using IMAP. HTTP listeners are started for the admin/account web interfaces, and for automated TLS configuration. Missing essential TLS certificates are immediately requested, other TLS certificates are requested on demand. Only implemented on unix systems, not Windows. Quickstart generates configuration files and prints instructions to quickly set up a mox instance. Quickstart writes configuration files, prints initial admin and account passwords, DNS records you should create. If you run it on Linux it writes a systemd service file and prints commands to enable and start mox as service. All output is written to quickstart.log for later reference. The user or uid is optional, defaults to "mox", and is the user or uid/gid mox will run as after initialization. Quickstart assumes mox will run on the machine you run quickstart on and uses its host name and public IPs. On many systems the hostname is not a fully qualified domain name, but only the first dns "label", e.g. "mail" in case of "mail.example.org". If so, quickstart does a reverse DNS lookup to find the hostname, and as fallback uses the label plus the domain of the email address you specified. Use flag -hostname to explicitly specify the hostname mox will run on. Mox is by far easiest to operate if you let it listen on port 443 (HTTPS) and 80 (HTTP). TLS will be fully automatic with ACME with Let's Encrypt. You can run mox along with an existing webserver, but because of MTA-STS and autoconfig, you'll need to forward HTTPS traffic for two domains to mox. Run "mox quickstart -existing-webserver ..." to generate configuration files and instructions for configuring mox along with an existing webserver. But please first consider configuring mox on port 443. It can itself serve domains with HTTP/HTTPS, including with automatic TLS with ACME, is easily configured through both configuration files and admin web interface, and can act as a reverse proxy (and static file server for that matter), so you can forward traffic to your existing backend applications. Look for "WebHandlers:" in the output of "mox config describe-domains" and see the output of "mox config example webhandlers". Shut mox down, giving connections maximum 3 seconds to stop before closing them. While shutting down, new IMAP and SMTP connections will get a status response indicating temporary unavailability. Existing connections will get a 3 second period to finish their transaction and shut down. Under normal circumstances, only IMAP has long-living connections, with the IDLE command to get notified of new mail deliveries. Set new password an account. The password is read from stdin. Secrets derived from the password, but not the password itself, are stored in the account database. The stored secrets are for authentication with: scram-sha-256, scram-sha-1, cram-md5, plain text (bcrypt hash). The parameter is an account name, as configured under Accounts in domains.conf and as present in the data/accounts/ directory, not a configured email address for an account. Set a new admin password, for the web interface. The password is read from stdin. Its bcrypt hash is stored in a file named "adminpasswd" in the configuration directory. Print the log levels, or set a new default log level, or a level for the given package. By default, a single log level applies to all logging in mox. But for each "pkg", an overriding log level can be configured. Examples of packages: smtpserver, smtpclient, queue, imapserver, spf, dkim, dmarc, junk, message, etc. Specify a pkg and an empty level to clear the configured level for a package. Valid labels: error, info, debug, trace, traceauth, tracedata. List hold rules for the delivery queue. Messages submitted to the queue that match a hold rule will be marked as on hold and not scheduled for delivery. Add hold rule for the delivery queue. Add a hold rule to mark matching newly submitted messages as on hold. Set the matching rules with the flags. Don't specify any flags to match all submitted messages. Remove hold rule for the delivery queue. Remove a hold rule by its id. List matching messages in the delivery queue. Prints the message with its ID, last and next delivery attempts, last error. Mark matching messages on hold. Messages that are on hold are not delivered until marked as off hold again, or otherwise handled by the admin. Mark matching messages off hold. Once off hold, messages can be delivered according to their current next delivery attempt. See the "queue schedule" command. Change next delivery attempt for matching messages. The next delivery attempt is adjusted by the duration parameter. If the -now flag is set, the new delivery attempt is set to the duration added to the current time, instead of added to the current scheduled time. Schedule immediate delivery with "mox queue schedule -now 0". Set transport for matching messages. By default, the routing rules determine how a message is delivered. The default and common case is direct delivery with SMTP. Messages can get a previously configured transport assigned to use for delivery, e.g. using submission to another mail server or with connections over a SOCKS proxy. Set TLS requirements for delivery of matching messages. Value "yes" is handled as if the RequireTLS extension was specified during submission. Value "no" is handled as if the message has a header "TLS-Required: No". This header is not added by the queue. If messages without this header are relayed through other mail servers they will apply their own default TLS policy. Value "default" is the default behaviour, currently for unverified opportunistic TLS. Fail delivery of matching messages, delivering DSNs. Failing a message is handled similar to how delivery is given up after all delivery attempts failed. The DSN (delivery status notification) message contains a line saying the message was canceled by the admin. Remove matching messages from the queue. Dangerous operation, this completely removes the message. If you want to store the message, use "queue dump" before removing. Dump a message from the queue. The message is printed to stdout and is in standard internet mail format. List matching messages in the retired queue. Prints messages with their ID and results. Print a message from the retired queue. Prints a JSON representation of the information from the retired queue. Print addresses in suppression list. Add address to suppression list for account. Remove address from suppression list for account. Check if address is present in suppression list, for any or specific account. List matching webhooks in the queue. Prints list of webhooks, their IDs and basic information. Change next delivery attempt for matching webhooks. The next delivery attempt is adjusted by the duration parameter. If the -now flag is set, the new delivery attempt is set to the duration added to the current time, instead of added to the current scheduled time. Schedule immediate delivery with "mox queue schedule -now 0". Fail delivery of matching webhooks. Print details of a webhook from the queue. The webhook is printed to stdout as JSON. List matching webhooks in the retired queue. Prints list of retired webhooks, their IDs and basic information. Print details of a webhook from the retired queue. The retired webhook is printed to stdout as JSON. Import a maildir into an account. The mbox/maildir archive is accessed and imported by the running mox process, so it must have access to the archive files. The default suggested systemd service file isolates mox from most of the file system, with only the "data/" directory accessible, so you may want to put the mbox/maildir archive files in a directory like "data/import/" to make it available to mox. By default, messages will train the junk filter based on their flags and, if "automatic junk flags" configuration is set, based on mailbox naming. If the destination mailbox is the Sent mailbox, the recipients of the messages are added to the message metadata, causing later incoming messages from these recipients to be accepted, unless other reputation signals prevent that. Users can also import mailboxes/messages through the account web page by uploading a zip or tgz file with mbox and/or maildirs. Messages are imported even if already present. Importing messages twice will result in duplicate messages. Mailbox flags, like "seen", "answered", will be imported. An optional dovecot-keywords file can specify additional flags, like Forwarded/Junk/NotJunk. Import an mbox into an account. Using mbox is not recommended, maildir is a better defined format. The mbox/maildir archive is accessed and imported by the running mox process, so it must have access to the archive files. The default suggested systemd service file isolates mox from most of the file system, with only the "data/" directory accessible, so you may want to put the mbox/maildir archive files in a directory like "data/import/" to make it available to mox. By default, messages will train the junk filter based on their flags and, if "automatic junk flags" configuration is set, based on mailbox naming. If the destination mailbox is the Sent mailbox, the recipients of the messages are added to the message metadata, causing later incoming messages from these recipients to be accepted, unless other reputation signals prevent that. Users can also import mailboxes/messages through the account web page by uploading a zip or tgz file with mbox and/or maildirs. Messages are imported even if already present. Importing messages twice will result in duplicate messages. Export one or all mailboxes from an account in maildir format. Export bypasses a running mox instance. It opens the account mailbox/message database file directly. This may block if a running mox instance also has the database open, e.g. for IMAP connections. To export from a running instance, use the accounts web page or webmail. Export messages from one or all mailboxes in an account in mbox format. Using mbox is not recommended. Maildir is a better format. Export bypasses a running mox instance. It opens the account mailbox/message database file directly. This may block if a running mox instance also has the database open, e.g. for IMAP connections. To export from a running instance, use the accounts web page or webmail. For mbox export, "mboxrd" is used where message lines starting with the magic "From " string are escaped by prepending a >. All ">*From " are escaped, otherwise reconstructing the original could lose a ">". Start a local SMTP/IMAP server that accepts all messages, useful when testing/developing software that sends email. Localserve starts mox with a configuration suitable for local email-related software development/testing. It listens for SMTP/Submission(s), IMAP(s) and HTTP(s), on the regular port numbers + 1000. Data is stored in the system user's configuration directory under "mox-localserve", e.g. $HOME/.config/mox-localserve/ on linux, but can be overridden with the -dir flag. If the directory does not yet exist, it is automatically initialized with configuration files, an account with email address mox@localhost and password moxmoxmox, and a newly generated self-signed TLS certificate. Incoming messages are delivered as normal, falling back to accepting and delivering to the mox account for unknown addresses. Submitted messages are added to the queue, which delivers by ignoring the destination servers, always connecting to itself instead. Recipient addresses with the following localpart suffixes are handled specially: - "temperror": fail with a temporary error code - "permerror": fail with a permanent error code - [45][0-9][0-9]: fail with the specific error code - "timeout": no response (for an hour) If the localpart begins with "mailfrom" or "rcptto", the error is returned during those commands instead of during "data". Prints help about matching commands. If multiple commands match, they are listed along with the first line of their help text. If a single command matches, its usage and full help text is printed. Creates a backup of the config and data directory. Backup copies the config directory to <destdir>/config, and creates <destdir>/data with a consistent snapshot of the databases and message files and copies other files from the data directory. Empty directories are not copied. The backup can then be stored elsewhere for long-term storage, or used to fall back to should an upgrade fail. Simply copying files in the data directory while mox is running can result in unusable database files. Message files never change (they are read-only, though can be removed) and are hard-linked so they don't consume additional space. If hardlinking fails, for example when the backup destination directory is on a different file system, a regular copy is made. Using a destination directory like "data/tmp/backup" increases the odds hardlinking succeeds: the default systemd service file specifically mounts the data directory, causing attempts to hardlink outside it to fail with an error about cross-device linking. All files in the data directory that aren't recognized (i.e. other than known database files, message files, an acme directory, the "tmp" directory, etc), are stored, but with a warning. Remove files in the destination directory before doing another backup. The backup command will not overwrite files, but print and return errors. Exit code 0 indicates the backup was successful. A clean successful backup does not print any output, but may print warnings. Use the -verbose flag for details, including timing. To restore a backup, first shut down mox, move away the old data directory and move an earlier backed up directory in its place, run "mox verifydata <datadir>", possibly with the "-fix" option, and restart mox. After the restore, you may also want to run "mox bumpuidvalidity" for each account for which messages in a mailbox changed, to force IMAP clients to synchronize mailbox state. Before upgrading, to check if the upgrade will likely succeed, first make a backup, then use the new mox binary to run "mox verifydata <backupdir>/data". This can change the backup files (e.g. upgrade database files, move away unrecognized message files), so you should make a new backup before actually upgrading. Verify the contents of a data directory, typically of a backup. Verifydata checks all database files to see if they are valid BoltDB/bstore databases. It checks that all messages in the database have a corresponding on-disk message file and there are no unrecognized files. If option -fix is specified, unrecognized message files are moved away. This may be needed after a restore, because messages enqueued or delivered in the future may get those message sequence numbers assigned and writing the message file would fail. Consistency of message/mailbox UID, UIDNEXT and UIDVALIDITY is verified as well. Because verifydata opens the database files, schema upgrades may automatically be applied. This can happen if you use a new mox release. It is useful to run "mox verifydata" with a new binary before attempting an upgrade, but only on a copy of the database files, as made with "mox backup". Before upgrading, make a new backup again since "mox verifydata" may have upgraded the database files, possibly making them potentially no longer readable by the previous version. Print licenses of mox source code and dependencies. Parses and validates the configuration files. If valid, the command exits with status 0. If not valid, all errors encountered are printed. Check the DNS records with the configuration for the domain, and print any errors/warnings. Prints annotated DNS records as zone file that should be created for the domain. The zone file can be imported into existing DNS software. You should review the DNS records, especially if your domain previously/currently has email configured. Prints an annotated empty configuration for use as domains.conf. The domains configuration file contains the domains and their configuration, and accounts and their configuration. This includes the configured email addresses. The mox admin web interface, and the mox command line interface, can make changes to this file. Mox automatically reloads this file when it changes. Like the static configuration, the example domains.conf printed by this command needs modifications to make it valid. Prints an annotated empty configuration for use as mox.conf. The static configuration file cannot be reloaded while mox is running. Mox has to be restarted for changes to the static configuration file to take effect. This configuration file needs modifications to make it valid. For example, it may contain unfinished list items. List all accounts. Each account is printed on a line, with optional additional tab-separated information, such as "(disabled)". Add an account with an email address and reload the configuration. Email can be delivered to this address/account. A password has to be configured explicitly, see the setaccountpassword command. Remove an account and reload the configuration. Email addresses for this account will also be removed, and incoming email for these addresses will be rejected. All data for the account will be removed. Disable login for an account, showing message to users when they try to login. Incoming email will still be accepted for the account, and queued email from the account will still be delivered. No new login sessions are possible. Message must be non-empty, ascii-only without control characters including newline, and maximum 256 characters because it is used in SMTP/IMAP. Enable login again for an account. Login attempts by the user no long result in an error message. Adds an address to an account and reloads the configuration. If address starts with a @ (i.e. a missing localpart), this is a catchall address for the domain. Remove an address and reload the configuration. Incoming email for this address will be rejected after removing an address. Adds a new domain to the configuration and reloads the configuration. The account is used for the postmaster mailboxes the domain, including as DMARC and TLS reporting. Localpart is the "username" at the domain for this account. If must be set if and only if account does not yet exist. The domain can be created in disabled mode, preventing automatically requesting TLS certificates with ACME, and rejecting incoming/outgoing messages involving the domain, but allowing further configuration of the domain. Remove a domain from the configuration and reload the configuration. This is a dangerous operation. Incoming email delivery for this domain will be rejected. Disable a domain and reload the configuration. This is a dangerous operation. Incoming/outgoing messages involving this domain will be rejected. Enable a domain and reload the configuration. Incoming/outgoing messages involving this domain will be accepted again. List TLS public keys for TLS client certificate authentication. If account is absent, the TLS public keys for all accounts are listed. Get a TLS public key for a fingerprint. Prints the type, name, account and address for the key, and the certificate in PEM format. Add a TLS public key to the account of the given address. The public key is read from the certificate. The optional name is a human-readable descriptive name of the key. If absent, the CommonName from the certificate is used. Remove TLS public key for fingerprint. Generate an ed25519 private key and minimal certificate for use a TLS public key and write to files starting with stem. The private key is written to $stem.$timestamp.ed25519privatekey.pkcs8.pem. The certificate is written to $stem.$timestamp.certificate.pem. The private key and certificate are also written to $stem.$timestamp.ed25519privatekey-certificate.pem. The certificate can be added to an account with "mox config account tlspubkey add". The combined file can be used with "mox sendmail". The private key is also written to standard error in raw-url-base64-encoded form, also for use with "mox sendmail". The fingerprint is written to standard error too, for reference. Show aliases (lists) for domain. Print settings and members of alias (list). Add new alias (list) with one or more addresses and public posting enabled. An alias is used for delivering incoming email to multiple recipients. If you want to add an address to an account, don't use an alias, just add the address to the account. Update alias (list) configuration. Remove alias (list). Add addresses to alias (list). Remove addresses from alias (list). Describe configuration for mox when invoked as sendmail. Prints a systemd unit service file for mox. This is the same file as generated using quickstart. If the systemd service file has changed with a newer version of mox, use this command to generate an up to date version. Ensure host private keys exist for TLS listeners with ACME. In mox.conf, each listener can have TLS configured. Long-lived private key files can be specified, which will be used when requesting ACME certificates. Configuring these private keys makes it feasible to publish DANE TLSA records for the corresponding public keys in DNS, protected with DNSSEC, allowing TLS certificate verification without depending on a list of Certificate Authorities (CAs). Previous versions of mox did not pre-generate private keys for use with ACME certificates, but would generate private keys on-demand. By explicitly configuring private keys, they will not change automatedly with new certificates, and the DNS TLSA records stay valid. This command looks for listeners in mox.conf with TLS with ACME configured. For each missing host private key (of type rsa-2048 and ecdsa-p256) a key is written to config/hostkeys/. If a certificate exists in the ACME "cache", its private key is copied. Otherwise a new private key is generated. Snippets for manually updating/editing mox.conf are printed. After running this command, and updating mox.conf, run "mox config dnsrecords" for a domain and create the TLSA DNS records it suggests to enable DANE. List available config examples, or print a specific example. Initiate a preauthenticated IMAP connection on file descriptor 0. For use with tools that can do IMAP over tunneled connections, e.g. with SSH during migrations. TLS is not possible on the connection, and authentication does not require TLS. Check if a newer version of mox is available. A single DNS TXT lookup to _updates.xmox.nl tells if a new version is available. If so, a changelog is fetched from https://updates.xmox.nl, and the individual entries verified with a builtin public key. The changelog is printed. Turn an ID from a Received header into a cid, for looking up in logs. A cid is essentially a connection counter initialized when mox starts. Each log line contains a cid. Received headers added by mox contain a unique ID that can be decrypted to a cid by admin of a mox instance only. Print the configuration for email clients for a domain. Sending email is typically not done on the SMTP port 25, but on submission ports 465 (with TLS) and 587 (without initial TLS, but usually added to the connection with STARTTLS). For IMAP, the port with TLS is 993 and without is 143. Without TLS/STARTTLS, passwords are sent in clear text, which should only be configured over otherwise secured connections, like a VPN. Dial the address using TLS with certificate verification using DANE. Data is copied between connection and stdin/stdout until either side closes the connection. Connect to MX server for domain using STARTTLS verified with DANE. If no destination host is specified, regular delivery logic is used to find the hosts to attempt delivery too. This involves following CNAMEs for the domain, looking up MX records, and possibly falling back to the domain name itself as host. If a destination host is specified, that is the only candidate host considered for dialing. With a list of destinations gathered, each is dialed until a successful SMTP session verified with DANE has been initialized, including EHLO and STARTTLS commands. Once connected, data is copied between connection and stdin/stdout, until either side closes the connection. This command follows the same logic as delivery attempts made from the queue, sharing most of its code. Print TLSA record for given certificate/key and parameters. Valid values: - usage: pkix-ta (0), pkix-ee (1), dane-ta (2), dane-ee (3) - selector: cert (0), spki (1) - matchtype: full (0), sha2-256 (1), sha2-512 (2) Common DANE TLSA record parameters are: dane-ee spki sha2-256, or 3 1 1, followed by a sha2-256 hash of the DER-encoded "SPKI" (subject public key info) from the certificate. An example DNS zone file entry: The first usable information from the pem file is used to compose the TLSA record. In case of selector "cert", a certificate is required. Otherwise the "subject public key info" (spki) of the first certificate or public or private key (pkcs#8, pkcs#1 or ec private key) is used. Lookup DNS name of given type. Lookup always prints whether the response was DNSSEC-protected. Examples: mox dns lookup ptr 1.1.1.1 mox dns lookup mx xmox.nl mox dns lookup txt _dmarc.xmox.nl. mox dns lookup tlsa _25._tcp.xmox.nl Generate a new ed25519 key for use with DKIM. Ed25519 keys are much smaller than RSA keys of comparable cryptographic strength. This is convenient because of maximum DNS message sizes. At the time of writing, not many mail servers appear to support ed25519 DKIM keys though, so it is recommended to sign messages with both RSA and ed25519 keys. Generate a new 2048 bit RSA private key for use with DKIM. The generated file is in PEM format, and has a comment it is generated for use with DKIM, by mox. Lookup and print the DKIM record for the selector at the domain. Print a DKIM DNS TXT record with the public key derived from the private key read from stdin. The DNS should be configured as a TXT record at $selector._domainkey.$domain. Verify the DKIM signatures in a message and print the results. The message is parsed, and the DKIM-Signature headers are validated. Validation of older messages may fail because the DNS records have been removed or changed by now, or because the signature header may have specified an expiration time that was passed. Sign a message, adding DKIM-Signature headers based on the domain in the From header. The message is parsed, the domain looked up in the configuration files, and DKIM-Signature headers generated. The message is printed with the DKIM-Signature headers prepended. Lookup dmarc policy for domain, a DNS TXT record at _dmarc.<domain>, validate and print it. Parse a DMARC report from an email message, and print its extracted details. DMARC reports are periodically mailed, if requested in the DMARC DNS record of a domain. Reports are sent by mail servers that received messages with our domain in a From header. This may or may not be legatimate email. DMARC reports contain summaries of evaluations of DMARC and DKIM/SPF, which can help understand email deliverability problems. Parse an email message and evaluate it against the DMARC policy of the domain in the From-header. mailfromaddress and helodomain are used for SPF validation. If both are empty, SPF validation is skipped. mailfromaddress should be the address used as MAIL FROM in the SMTP session. For DSN messages, that address may be empty. The helo domain was specified at the beginning of the SMTP transaction that delivered the message. These values can be found in message headers. For each reporting address in the domain's DMARC record, check if it has opted into receiving reports (if needed). A DMARC record can request reports about DMARC evaluations to be sent to an email/http address. If the organizational domains of that of the DMARC record and that of the report destination address do not match, the destination address must opt-in to receiving DMARC reports by creating a DMARC record at <dmarcdomain>._report._dmarc.<reportdestdomain>. Test if IP is in the DNS blocklist of the zone, e.g. bl.spamcop.net. If the IP is in the blocklist, an explanation is printed. This is typically a URL with more information. Check the health of the DNS blocklist represented by zone, e.g. bl.spamcop.net. The health of a DNS blocklist can be checked by querying for 127.0.0.1 and 127.0.0.2. The second must and the first must not be present. Lookup the MTASTS record and policy for the domain. MTA-STS is a mechanism for a domain to specify if it requires TLS connections for delivering email. If a domain has a valid MTA-STS DNS TXT record at _mta-sts.<domain> it signals it implements MTA-STS. A policy can then be fetched at https://mta-sts.<domain>/.well-known/mta-sts.txt. The policy specifies the mode (enforce, testing, none), which MX servers support TLS and should be used, and how long the policy can be cached. Lookup the age of domain in RDAP based on latest registration. RDAP is the registration data access protocol. Registries run RDAP services for their top level domains, providing information such as the registration date of domains. This command looks up the "age" of a domain by looking at the most recent "registration", "reregistration" or "reinstantiation" event. Email messages from recently registered domains are often treated with suspicion, and some mail systems are more likely to classify them as junk. On each invocation, a bootstrap file with a list of registries (of top-level domains) is retrieved, without caching. Do not run this command too often with automation. Recreate and retrain the junk filter for the account or all accounts. Useful after having made changes to the junk filter configuration, or if the implementation has changed. Sendmail is a drop-in replacement for /usr/sbin/sendmail to deliver emails sent by unix processes like cron. If invoked as "sendmail", it will act as sendmail for sending messages. Its intention is to let processes like cron send emails. Messages are submitted to an actual mail server over SMTP. The destination mail server and credentials are configured in /etc/moxsubmit.conf, see mox config describe-sendmail. The From message header is rewritten to the configured address. When the addressee appears to be a local user, because without @, the message is sent to the configured default address. If submitting an email fails, it is added to a directory moxsubmit.failures in the user's home directory. Most flags are ignored to fake compatibility with other sendmail implementations. A single recipient or the -t flag with a To-header is required. With the -t flag, Cc and Bcc headers are not handled specially, so Bcc is not removed and the addresses do not receive the email. /etc/moxsubmit.conf should be group-readable and not readable by others and this binary should be setgid that group: Check the status of IP for the policy published in DNS for the domain. IPs may be allowed to send for a domain, or disallowed, and several shades in between. If not allowed, an explanation may be provided by the policy. If so, the explanation is printed. The SPF mechanism that matched (if any) is also printed. Lookup the SPF record for the domain and print it. Parse the record as SPF record. If valid, nothing is printed. Lookup the TLSRPT record for the domain. A TLSRPT record typically contains an email address where reports about TLS connectivity should be sent. Mail servers attempting delivery to our domain should attempt to use TLS. TLSRPT lets them report how many connection successfully used TLS, and how what kind of errors occurred otherwise. Parse and print the TLSRPT in the message. The report is printed in formatted JSON. Prints this mox version. Lists available methods, prints request/response parameters for method, or calls a method with a request read from standard input. List available examples, or print a specific example. Change the IMAP UID validity of the mailbox, causing IMAP clients to refetch messages. This can be useful after manually repairing metadata about the account/mailbox. Opens account database file directly. Ensure mox does not have the account open, or is not running. Reassign UIDs in one mailbox or all mailboxes in an account and bump UID validity, causing IMAP clients to refetch messages. Opens account database file directly. Ensure mox does not have the account open, or is not running. Fix inconsistent UIDVALIDITY and UIDNEXT in messages/mailboxes/account. The next UID to use for a message in a mailbox should always be higher than any existing message UID in the mailbox. If it is not, the mailbox UIDNEXT is updated. Each mailbox has a UIDVALIDITY sequence number, which should always be lower than the per-account next UIDVALIDITY to use. If it is not, the account next UIDVALIDITY is updated. Opens account database file directly. Ensure mox does not have the account open, or is not running. Ensure message sizes in the database matching the sum of the message prefix length and on-disk file size. Messages with an inconsistent size are also parsed again. If an inconsistency is found, you should probably also run "mox bumpuidvalidity" on the mailboxes or entire account to force IMAP clients to refetch messages. Parse all messages in the account or all accounts again. Can be useful after upgrading mox with improved message parsing. Messages are parsed in batches, so other access to the mailboxes/messages are not blocked while reparsing all messages. Ensure messages in the database have a pre-parsed MIME form in the database. Recalculate message counts for all mailboxes in the account, and total message size for quota. When a message is added to/removed from a mailbox, or when message flags change, the total, unread, unseen and deleted messages are accounted, the total size of the mailbox, and the total message size for the account. In case of a bug in this accounting, the numbers could become incorrect. This command will find, fix and print them. Parse message, print JSON representation. Reassign message threads. For all accounts, or optionally only the specified account. Threading for all messages in an account is first reset, and new base subject and normalized message-id saved with the message. Then all messages are evaluated and matched against their parents/ancestors. Messages are matched based on the References header, with a fall-back to an In-Reply-To header, and if neither is present/valid, based only on base subject. A References header typically points to multiple previous messages in a hierarchy. From oldest ancestor to most recent parent. An In-Reply-To header would have only a message-id of the parent message. A message is only linked to a parent/ancestor if their base subject is the same. This ensures unrelated replies, with a new subject, are placed in their own thread. The base subject is lower cased, has whitespace collapsed to a single space, and some components removed: leading "Re:", "Fwd:", "Fw:", or bracketed tag (that mailing lists often add, e.g. "[listname]"), trailing "(fwd)", or enclosing "[fwd: ...]". Messages are linked to all their ancestors. If an intermediate parent/ancestor message is deleted in the future, the message can still be linked to the earlier ancestors. If the direct parent already wasn't available while matching, this is stored as the message having a "missing link" to its stored ancestors.

Package tabwriter implements a write filter (tabwriter.Writer) that translates tabbed columns in input into properly aligned text. The package is using the Elastic Tabstops algorithm described at http://nickgravgaard.com/elastictabstops/index.html. The text/tabwriter package is frozen and is not accepting new features.

Package w3pilot provides a Go client for the W3Pilot browser automation platform. W3Pilot is a browser automation platform built for AI agents that uses the WebDriver BiDi protocol for bidirectional communication with the browser. Launch a browser and navigate to a page: Find elements using CSS selectors and interact with them: Type text into input fields: Capture screenshots as PNG data: Launch in headless mode for CI/server environments: Or with explicit options: This client requires Chrome or Chromium. If Chrome is not found on your system, it will automatically download Chrome for Testing from Google's official API. You can also specify a custom Chrome path via the CHROME_PATH environment variable or the ExecutablePath option in LaunchOptions. Package w3pilot provides a Go client for browser automation using the WebDriver BiDi protocol. It launches Chrome with BiDi support and communicates over WebSocket.

Package foxhound is a high-performance Go web scraping framework with native anti-detection built on Camoufox, a Firefox fork designed to evade bot fingerprinting. Foxhound is a scraping framework for Go — it handles the full lifecycle of web data extraction: fetching pages (with or without a real browser), navigating JavaScript-heavy sites, solving CAPTCHAs, rotating identities and proxies, extracting structured data, and exporting results. Think of it as Scrapy for Go, but with first-class browser automation and anti-detection built in from day one. Modern websites deploy increasingly sophisticated bot detection: TLS fingerprinting, JavaScript challenges (Cloudflare, DataDome, PerimeterX), canvas/WebGL fingerprint checks, and behavioral analysis. Traditional HTTP-only scrapers fail silently against these defenses. Headless Chrome is widely fingerprinted. Foxhound solves this by combining two fetching strategies behind a single API: The smart router starts with the fast static client and automatically escalates to the full browser when it detects blocks (403, 429, 503, CAPTCHA pages). This means you get HTTP-client speed on easy targets and browser-level evasion on hard ones, without changing your code. Foxhound is organized around five core concepts: Hunt is the top-level campaign orchestrator. It owns the queue, spawns Walker goroutines, collects stats, and coordinates shutdown. You configure a Hunt with seed URLs, a Processor (your extraction logic), middleware, pipelines, and writers. Trail is a fluent navigation path builder. It chains browser actions — Navigate, Click, Fill, Wait, Scroll, InfiniteScroll, Evaluate (custom JS), and CaptureXHR — into a reusable sequence that gets compiled into Jobs. Trails describe what a human would do on the page. Walker is a goroutine that acts as a virtual user. Each Walker pops Jobs from the queue, fetches pages through the middleware chain, runs your Processor, writes extracted Items through the pipeline, and enqueues discovered follow-up Jobs. A Hunt runs multiple Walkers concurrently. Job is the unit of work: a URL plus fetch mode, priority, browser steps, metadata, and optional session routing. Jobs flow through the queue and are consumed by Walkers. Session is a stateful client that wraps a fetcher, cookie jar, identity profile, and proxy into a reusable unit. Use it standalone for ad-hoc scraping, or register multiple Sessions with a Hunt via Hunt.AddSession to route different Jobs through different identities and proxies. Every request flows through a middleware chain before reaching the fetcher: The static fetcher (fetch.NewStealth) uses Go's HTTP client with precise header ordering and TLS fingerprints matched to the identity profile. The browser fetcher (fetch.NewCamoufox) launches a real Camoufox browser instance via the Juggler protocol (Firefox's native remote protocol, less targeted by anti-bot than CDP). The smart fetcher (fetch.NewSmart) wraps both and auto-escalates based on response signals and Bayesian domain risk scoring. Every request uses a complete, internally consistent identity profile: user agent, TLS fingerprint, header order, OS, hardware specs, screen dimensions, locale, timezone, and geolocation all match. Randomness without consistency is the number one cause of bot detection — a Windows UA with a macOS font list, or a US locale with a Tokyo timezone, triggers instant blocks. Foxhound ships 60 embedded device profiles. The identity package generates profiles with functional options: When using Camoufox, the identity is serialized to a JSON config that sets navigator properties, WebGL vendor/renderer, canvas noise, OS-specific fonts, screen dimensions, and timezone at the C++ level inside the browser — not via JavaScript injection that anti-bot scripts can detect. Foxhound models human behavior using statistical distributions observed from real user sessions: Three built-in profiles ("careful", "moderate", "aggressive") control the overall pacing. Configure via BehaviorConfig or Hunt options. The NopeCHA browser extension is automatically downloaded from GitHub and loaded into Camoufox on first launch. It solves reCAPTCHA, hCAPTCHA, and Cloudflare Turnstile challenges without API keys. The extension is cached at ~/.cache/foxhound/extensions/nopecha/ and updated automatically. The design philosophy: the goal is to never trigger a CAPTCHA. If one appears, earlier layers (identity, timing, proxy rotation) failed. NopeCHA is the safety net, not the primary strategy. Disable with extension_path: "none" in config or WithExtensionPath("none"). Foxhound provides 13 middleware layers that wrap the fetcher: Middleware is composable: each layer wraps a Fetcher and returns a Fetcher, so you can stack them in any order or add custom middleware. Websites frequently change their DOM structure — class names rotate, IDs are randomized, layouts shift. Foxhound's adaptive selector system survives these rewrites by building element signatures (tag, position, text patterns, ancestor structure) alongside CSS selectors. When a selector stops matching, the system falls back to similarity matching against saved signatures. Enable with Hunt.WithAdaptive and use via Response.Adaptive, Response.CSSAdaptive, Response.CSSAdaptiveAll, or Trail.Adaptive. Signatures can be stored in JSON files or SQLite. A Hunt is the standard way to scrape at scale. Define a Processor, configure middleware and writers, add seed URLs, and run: Trails describe multi-step browser interactions for JS-heavy pages. This example searches Google Maps and scrolls through results: Session is the lightweight alternative to Hunt for quick, stateful fetches. Cookies persist across calls, and the identity stays consistent: Response provides built-in CSS and XPath querying without importing the parse package: Response.Follow extracts links from the page and generates follow-up Jobs: Capture background API calls that JavaScript makes after page load. This is essential for SPAs where data loads via XHR/fetch, not in the initial HTML: The captured responses are available in Response.CapturedXHR as a slice of maps with keys: request_url, request_method, status, headers, body. For sites behind Cloudflare's JavaScript challenge, Foxhound can detect and wait for the challenge to complete: Route different jobs through different identities and proxies within a single Hunt: Cache responses on disk for zero-network iteration during development: The foxhound module is organized into focused sub-packages: [engine] — Hunt, Trail, Walker, scheduler, retry logic, stats collection, and ItemList for thread-safe item accumulation with CSV/JSON/JSONL export. [fetch] — Stealth HTTP client (TLS fingerprinting + header ordering), Camoufox browser automation (Juggler protocol), Smart router (auto-escalation), XHR capture, page pool management, domain risk scoring, and SOCKS5 auth relay. [identity] — Profile generation with 60 embedded device profiles. Produces consistent identity bundles (UA, TLS, headers, OS, hardware, screen, locale, geo) and Camoufox fingerprint configs. [behavior] — Human behavior simulation: timing (Weibull/Gamma distributions), mouse (Bezier curves), scroll patterns, keyboard input, navigation profiles, and session fatigue modeling. [middleware] — 13 composable middleware layers: rate limiting, dedup, retry, autothrottle, cookies, referer, redirect, depth, delta-fetch, circuit breaker, metrics, blocked detection, and robots.txt. [parse] — Content extraction: CSS (goquery), JSON (dot-path), XPath (subset), regex, structured schema, Markdown/text conversion, metadata (JSON-LD, OpenGraph, NextData, NuxtData), contact deobfuscation, sitemap/feed parsing, adaptive selectors, HTML table extraction, JS preload detection, directory listings, pagination detection, and auto-detection with Readability-style scoring. [pipeline] — Item processing stages: validation, cleaning, deduplication, field transformation (regex, rename, type coercion), and chain composition. pipeline/export — Output writers: JSON, JSONL, CSV, XML, SQLite, PostgreSQL, Markdown, Text, and Webhook. [proxy] — Proxy pool management with geo-aware selection, health checking, cooldown tracking, and provider adapters (BrightData, Oxylabs, Smartproxy). [queue] — Job queue implementations: in-memory (heap-based priority queue), Redis (sorted sets), and SQLite (persistent). [cache] — Response caching: in-memory (LRU + TTL), file-based (SHA256 keys), Redis, and SQLite. [captcha] — CAPTCHA detection (Cloudflare, reCAPTCHA, hCAPTCHA, GeeTest) and solving via NopeCHA, CapSolver, 2Captcha, and Turnstile. [monitor] — Observability: atomic stat counters, Prometheus metrics (isolated registry), and webhook-based alerting rules. cmd/foxhound — CLI tool: init, run, check, proxy-test, shell, browser-shell, resume, curl2fox, and preview commands.

Package null contains SQL types that consider zero input and null input as separate values, with convenient support for JSON and text marshaling. Types in this package will always encode to their null value if null. Use the zero subpackage if you want zero values and null to be treated the same.

Package dotmatrix encodes images in a "dot matrix" pattern using braille unicode characters. Images are first converted to monochrome, then each 2x4 pixel block is coded to an 8-dot braille character. In this fashion, an image's entire pixel set can be mapped, one-by-one, to either a "filled" or "unfilled" braille dot. The resulting braille symbols are arranged as lines of text to form a representation of the original image. The encoded image is lossy in the sense that color information is reduced to monochrome with diffusion, but otherwise the resulting text-based image is pixel perfect. In other words, if a pure monochrome image is used as input, there will be no loss of information. https://en.wikipedia.org/wiki/Braille_Patterns⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀

┌──────────────────────────────────────────────────────────────────────┐ │ ai_suggest.go — Parse & Apply AI Pin Suggestions │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ chat_view.go — Custom Chat View with Selectable Text │ │ │ │ Replaces the default ChatPanel.Layout() with a version that uses │ │ read-only giowidget.Editor for each message, enabling text │ │ selection and copy-to-clipboard. │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ export.go — Pin Configuration Export │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ layout.go — Main Layout, Navigation & Theme Switching │ │ │ │ Demonstrates: │ │ • ui.VStack / ui.HStack — vertical and horizontal stacking │ │ • ui.AppBar — top application bar with action buttons │ │ • ui.Expanded — fills remaining space in a stack │ │ • ui.Scroll — vertical scroll wrapper │ │ • ui.Style(view).Padding() — modifier chaining │ │ • ui.ViewFunc — bridging a lower-level Gio widget into a View │ │ • Theme switching via ThemeRefValue.Set() │ │ • Page routing with a plain Go switch statement │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ Pingo — RPi Pico / Pico 2 Pin Selector │ │ A demo application showcasing the ImmyGo UI framework. │ │ │ │ This project is structured as a learning guide for building │ │ desktop apps with ImmyGo. Each file covers a specific concept: │ │ │ │ main.go → App entry point, ui.Run, theme, options │ │ state.go → Reactive state, AI engine, persistent widgets │ │ layout.go → Main layout: AppBar, SideNav, page routing │ │ page_pinout.go → Pinout + pin selector + AI assist │ │ page_mypins.go → Selected pins summary, conflict detection │ │ page_settings.go → AI provider & app settings │ │ svg.go → Embedding & rasterising SVG assets │ │ pindata/ → Domain model (no UI dependency) │ └──────────────────────────────────────────────────────────────────────┘ Requires Gio system deps on Linux: ┌──────────────────────────────────────────────────────────────────────┐ │ page_mypins.go — Selected Pins Summary Page │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ page_pinout.go — Interactive Pinout & Pin Selector (CubeMX-style) │ │ │ │ The pinout page is the primary pin selection interface: │ │ 1. Select a peripheral category (SPI, I2C, UART, etc.) │ │ 2. Pick a specific function (e.g., SPI0 RX) │ │ 3. Click an eligible pin on the diagram to assign it │ │ 4. Click an assigned pin to deassign it │ │ │ │ Eligible pins highlight in cyan, assigned pins show their │ │ function in the peripheral's category color. │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ page_settings.go — AI & App Settings Page │ │ │ │ Non-secret settings (provider, model, host, temperature, tokens) │ │ are persisted to ~/.config/pingo/settings.json. │ │ API keys are NEVER written to disk — use the ANTHROPIC_API_KEY │ │ environment variable or enter the key in the masked input │ │ (held in memory only for the current session). │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ state.go — Reactive State Management │ │ │ │ ImmyGo provides State[T], a generic thread-safe reactive value. │ │ When you call state.Set(v), the UI automatically re-renders on │ │ the next frame. Use state.Get() in your build function to read. │ │ │ │ Key rules: │ │ • State is goroutine-safe (uses sync.RWMutex internally). │ │ • Calling Set() bumps an internal version counter that ImmyGo │ │ uses to detect changes. │ │ • Update(fn) applies a transformation atomically. │ │ │ │ For stateful Gio widgets (SideNav, Toggle, Clickable, Editor), │ │ you MUST store the widget in a package-level var so it persists │ │ across frames. Creating a new widget every frame destroys the │ │ click/press state and breaks interactivity. │ └──────────────────────────────────────────────────────────────────────┘ ┌──────────────────────────────────────────────────────────────────────┐ │ svg.go — Embedding & Rendering SVG Assets │ │ │ │ Demonstrates: │ │ • Go 1.16+ embed directive for bundling assets into the binary │ │ • Using oksvg + rasterx to rasterise SVG → image.NRGBA │ │ • Displaying raster images via ui.Image(img).Size(w, h) │ │ │ │ ImmyGo's ui.Image takes any image.Image and renders it via Gio's │ │ GPU pipeline. Since Gio doesn't have native SVG support, we │ │ rasterise the SVG once at startup and cache the result. │ │ │ │ The Pico board SVG comes from: │ │ https://github.com/tinygo-org/playground/tree/main/parts │ └──────────────────────────────────────────────────────────────────────┘

Package vibium provides a Go client for the Vibium browser automation platform. Vibium is a browser automation platform built for AI agents that uses the WebDriver BiDi protocol for bidirectional communication with the browser. Launch a browser and navigate to a page: Find elements using CSS selectors and interact with them: Type text into input fields: Capture screenshots as PNG data: Launch in headless mode for CI/server environments: Or with explicit options: This client requires the Vibium clicker binary to be available. Install it via: Or set the VIBIUM_CLICKER_PATH environment variable to point to the binary. Package vibium provides a Go client for browser automation via the Vibium platform. It communicates with the Vibium clicker binary over WebSocket using the WebDriver BiDi protocol.

Package commandpalette provides a fuzzy-search command palette overlay for the Bubble Tea framework. The palette renders as a self-contained bordered box: a text input at the top, a live-filtered list of actions below, and a keyboard hint footer. Actions are matched by label and optional keywords using fuzzy search. The caller is responsible for opening/closing the palette and handling esc and ctrl+c before forwarding key messages to Update. Typical usage: In Update:

Package testastic provides expressive testing utilities for Go. Testastic offers structured comparison for JSON, YAML, HTML, and plain text documents with support for template-based matchers, alongside general-purpose assertions for values, errors, strings, and collections. Compare API responses or rendered documents against expected files with flexible matching: Input types by assertion: Expected files support template matchers for dynamic values: Available built-in matchers: Configure comparison behavior with options: Additional options are available for HTML comparison: When API responses change, update expected files automatically: General-purpose assertions for common test scenarios: Contains, NotContains, HasPrefix, NotHasPrefix, HasSuffix, NotHasSuffix, and Matches accept string, []byte, or fmt.Stringer inputs. For asynchronous operations, retry until a condition is met or timeout is reached. The condition is checked immediately, then at regular intervals (default 100ms). Configure polling with WithInterval and WithMessage: Register custom matchers for domain-specific validation: Then use in expected files: "id": "{{customID}}"

Package websocket implements the WebSocket protocol defined in RFC 6455. This file contains the implementation of WebSocket compression using the DEFLATE algorithm as specified in RFC 7692. 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 websocket implements the WebSocket protocol defined in RFC 6455. Package websocket implements the WebSocket protocol defined in RFC 6455. This file contains proxy-related functionality for WebSocket connections.

Package willow is a retained-mode 2D game framework for Ebitengine. Ebitengine is immediate-mode: every frame you issue draw commands from scratch, and nothing persists. Willow adds a retained-mode layer on top - you build a persistent scene graph of nodes, and Willow traverses it each frame to produce draw commands for Ebitengine. Willow provides the scene graph, transform hierarchy, sprite batching, input handling, camera viewports, text rendering, particle systems, and more that every non-trivial 2D game needs. Full documentation, tutorials, and examples are available at: https://phanxgames.github.io/willow/ The simplest way to get started is Run, which creates a window and game loop for you: For full control, implement ebiten.Game yourself and call [Scene.Update] and [Scene.Draw] directly: Every visual element is a Node. Nodes form a tree rooted at [Scene.Root]. Children inherit their parent's transform and alpha. Create nodes with typed constructors: NewContainer, NewSprite, NewText, NewParticleEmitter, NewMesh, NewPolygon, and others. For solid-color rectangles, use NewSprite with a zero-value TextureRegion and set color and size: For quick tree searches, use [Node.FindChild] (direct children) or [Node.FindDescendant] (recursive depth-first). Both support % wildcards: For repeated lookups or tag-based grouping, use NodeIndex: Willow includes cameras with follow/scroll-to/zoom, two text systems (SDF-based DistanceFieldFont for smooth TTF/OTF scaling with outlines, glows, and shadows; pixel-perfect PixelFont for bitmap spritesheet fonts with integer-only scaling), CPU-simulated particles, mesh/polygon/rope geometry, Kage shader filters, texture caching, masking, blend modes, lighting layers, and tweens (via gween). All 45 gween easing functions are re-exported as EaseLinear, EaseOutCubic, EaseOutBounce, etc. for autocomplete discoverability without an extra import. See the full docs for guides on each feature: https://phanxgames.github.io/willow/

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: 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.