Forms

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 sdk is the official AWS SDK for the Go programming language. The AWS SDK for Go provides APIs and utilities that developers can use to build Go applications that use AWS services, such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). The SDK removes the complexity of coding directly against a web service interface. It hides a lot of the lower-level plumbing, such as authentication, request retries, and error handling. The SDK also includes helpful utilities on top of the AWS APIs that add additional capabilities and functionality. For example, the Amazon S3 Download and Upload Manager will automatically split up large objects into multiple parts and transfer them concurrently. See the s3manager package documentation for more information. https://docs.aws.amazon.com/sdk-for-go/api/service/s3/s3manager/ Checkout the Getting Started Guide and API Reference Docs detailed the SDK's components and details on each AWS client the SDK supports. The Getting Started Guide provides examples and detailed description of how to get setup with the SDK. https://docs.aws.amazon.com/sdk-for-go/v1/developer-guide/welcome.html The API Reference Docs include a detailed breakdown of the SDK's components such as utilities and AWS clients. Use this as a reference of the Go types included with the SDK, such as AWS clients, API operations, and API parameters. https://docs.aws.amazon.com/sdk-for-go/api/ The SDK is composed of two main components, SDK core, and service clients. The SDK core packages are all available under the aws package at the root of the SDK. Each client for a supported AWS service is available within its own package under the service folder at the root of the SDK. aws - SDK core, provides common shared types such as Config, Logger, and utilities to make working with API parameters easier. awserr - Provides the error interface that the SDK will use for all errors that occur in the SDK's processing. This includes service API response errors as well. The Error type is made up of a code and message. Cast the SDK's returned error type to awserr.Error and call the Code method to compare returned error to specific error codes. See the package's documentation for additional values that can be extracted such as RequestId. credentials - Provides the types and built in credentials providers the SDK will use to retrieve AWS credentials to make API requests with. Nested under this folder are also additional credentials providers such as stscreds for assuming IAM roles, and ec2rolecreds for EC2 Instance roles. endpoints - Provides the AWS Regions and Endpoints metadata for the SDK. Use this to lookup AWS service endpoint information such as which services are in a region, and what regions a service is in. Constants are also provided for all region identifiers, e.g UsWest2RegionID for "us-west-2". session - Provides initial default configuration, and load configuration from external sources such as environment and shared credentials file. request - Provides the API request sending, and retry logic for the SDK. This package also includes utilities for defining your own request retryer, and configuring how the SDK processes the request. service - Clients for AWS services. All services supported by the SDK are available under this folder. The SDK includes the Go types and utilities you can use to make requests to AWS service APIs. Within the service folder at the root of the SDK you'll find a package for each AWS service the SDK supports. All service clients follows a common pattern of creation and usage. When creating a client for an AWS service you'll first need to have a Session value constructed. The Session provides shared configuration that can be shared between your service clients. When service clients are created you can pass in additional configuration via the aws.Config type to override configuration provided by in the Session to create service client instances with custom configuration. Once the service's client is created you can use it to make API requests the AWS service. These clients are safe to use concurrently. In the AWS SDK for Go, you can configure settings for service clients, such as the log level and maximum number of retries. Most settings are optional; however, for each service client, you must specify a region and your credentials. The SDK uses these values to send requests to the correct AWS region and sign requests with the correct credentials. You can specify these values as part of a session or as environment variables. See the SDK's configuration guide for more information. https://docs.aws.amazon.com/sdk-for-go/v1/developer-guide/configuring-sdk.html See the session package documentation for more information on how to use Session with the SDK. https://docs.aws.amazon.com/sdk-for-go/api/aws/session/ See the Config type in the aws package for more information on configuration options. https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config When using the SDK you'll generally need your AWS credentials to authenticate with AWS services. The SDK supports multiple methods of supporting these credentials. By default the SDK will source credentials automatically from its default credential chain. See the session package for more information on this chain, and how to configure it. The common items in the credential chain are the following: Environment Credentials - Set of environment variables that are useful when sub processes are created for specific roles. Shared Credentials file (~/.aws/credentials) - This file stores your credentials based on a profile name and is useful for local development. EC2 Instance Role Credentials - Use EC2 Instance Role to assign credentials to application running on an EC2 instance. This removes the need to manage credential files in production. Credentials can be configured in code as well by setting the Config's Credentials value to a custom provider or using one of the providers included with the SDK to bypass the default credential chain and use a custom one. This is helpful when you want to instruct the SDK to only use a specific set of credentials or providers. This example creates a credential provider for assuming an IAM role, "myRoleARN" and configures the S3 service client to use that role for API requests. See the credentials package documentation for more information on credential providers included with the SDK, and how to customize the SDK's usage of credentials. https://docs.aws.amazon.com/sdk-for-go/api/aws/credentials The SDK has support for the shared configuration file (~/.aws/config). This support can be enabled by setting the environment variable, "AWS_SDK_LOAD_CONFIG=1", or enabling the feature in code when creating a Session via the Option's SharedConfigState parameter. In addition to the credentials you'll need to specify the region the SDK will use to make AWS API requests to. In the SDK you can specify the region either with an environment variable, or directly in code when a Session or service client is created. The last value specified in code wins if the region is specified multiple ways. To set the region via the environment variable set the "AWS_REGION" to the region you want to the SDK to use. Using this method to set the region will allow you to run your application in multiple regions without needing additional code in the application to select the region. The endpoints package includes constants for all regions the SDK knows. The values are all suffixed with RegionID. These values are helpful, because they reduce the need to type the region string manually. To set the region on a Session use the aws package's Config struct parameter Region to the AWS region you want the service clients created from the session to use. This is helpful when you want to create multiple service clients, and all of the clients make API requests to the same region. See the endpoints package for the AWS Regions and Endpoints metadata. https://docs.aws.amazon.com/sdk-for-go/api/aws/endpoints/ In addition to setting the region when creating a Session you can also set the region on a per service client bases. This overrides the region of a Session. This is helpful when you want to create service clients in specific regions different from the Session's region. See the Config type in the aws package for more information and additional options such as setting the Endpoint, and other service client configuration options. https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config Once the client is created you can make an API request to the service. Each API method takes a input parameter, and returns the service response and an error. The SDK provides methods for making the API call in multiple ways. In this list we'll use the S3 ListObjects API as an example for the different ways of making API requests. ListObjects - Base API operation that will make the API request to the service. ListObjectsRequest - API methods suffixed with Request will construct the API request, but not send it. This is also helpful when you want to get a presigned URL for a request, and share the presigned URL instead of your application making the request directly. ListObjectsPages - Same as the base API operation, but uses a callback to automatically handle pagination of the API's response. ListObjectsWithContext - Same as base API operation, but adds support for the Context pattern. This is helpful for controlling the canceling of in flight requests. See the Go standard library context package for more information. This method also takes request package's Option functional options as the variadic argument for modifying how the request will be made, or extracting information from the raw HTTP response. ListObjectsPagesWithContext - same as ListObjectsPages, but adds support for the Context pattern. Similar to ListObjectsWithContext this method also takes the request package's Option function option types as the variadic argument. In addition to the API operations the SDK also includes several higher level methods that abstract checking for and waiting for an AWS resource to be in a desired state. In this list we'll use WaitUntilBucketExists to demonstrate the different forms of waiters. WaitUntilBucketExists. - Method to make API request to query an AWS service for a resource's state. Will return successfully when that state is accomplished. WaitUntilBucketExistsWithContext - Same as WaitUntilBucketExists, but adds support for the Context pattern. In addition these methods take request package's WaiterOptions to configure the waiter, and how underlying request will be made by the SDK. The API method will document which error codes the service might return for the operation. These errors will also be available as const strings prefixed with "ErrCode" in the service client's package. If there are no errors listed in the API's SDK documentation you'll need to consult the AWS service's API documentation for the errors that could be returned. Pagination helper methods are suffixed with "Pages", and provide the functionality needed to round trip API page requests. Pagination methods take a callback function that will be called for each page of the API's response. Waiter helper methods provide the functionality to wait for an AWS resource state. These methods abstract the logic needed to to check the state of an AWS resource, and wait until that resource is in a desired state. The waiter will block until the resource is in the state that is desired, an error occurs, or the waiter times out. If a resource times out the error code returned will be request.WaiterResourceNotReadyErrorCode. This example shows a complete working Go file which will upload a file to S3 and use the Context pattern to implement timeout logic that will cancel the request if it takes too long. This example highlights how to use sessions, create a service client, make a request, handle the error, and process the response.

Package cron implements a cron spec parser and job runner. To download the specific tagged release, run: Import it in your program as: It requires Go 1.11 or later due to usage of Go Modules. Callers may register Funcs to be invoked on a given schedule. Cron will run them in their own goroutines. A cron expression represents a set of times, using 5 space-separated fields. Month and Day-of-week field values are case insensitive. "SUN", "Sun", and "sun" are equally accepted. The specific interpretation of the format is based on the Cron Wikipedia page: https://en.wikipedia.org/wiki/Cron Alternative Cron expression formats support other fields like seconds. You can implement that by creating a custom Parser as follows. Since adding Seconds is the most common modification to the standard cron spec, cron provides a builtin function to do that, which is equivalent to the custom parser you saw earlier, except that its seconds field is REQUIRED: That emulates Quartz, the most popular alternative Cron schedule format: http://www.quartz-scheduler.org/documentation/quartz-2.x/tutorials/crontrigger.html Asterisk ( * ) The asterisk indicates that the cron expression will match for all values of the field; e.g., using an asterisk in the 5th field (month) would indicate every month. Slash ( / ) Slashes are used to describe increments of ranges. For example 3-59/15 in the 1st field (minutes) would indicate the 3rd minute of the hour and every 15 minutes thereafter. The form "*\/..." is equivalent to the form "first-last/...", that is, an increment over the largest possible range of the field. The form "N/..." is accepted as meaning "N-MAX/...", that is, starting at N, use the increment until the end of that specific range. It does not wrap around. Comma ( , ) Commas are used to separate items of a list. For example, using "MON,WED,FRI" in the 5th field (day of week) would mean Mondays, Wednesdays and Fridays. Hyphen ( - ) Hyphens are used to define ranges. For example, 9-17 would indicate every hour between 9am and 5pm inclusive. Question mark ( ? ) Question mark may be used instead of '*' for leaving either day-of-month or day-of-week blank. You may use one of several pre-defined schedules in place of a cron expression. You may also schedule a job to execute at fixed intervals, starting at the time it's added or cron is run. This is supported by formatting the cron spec like this: where "duration" is a string accepted by time.ParseDuration (http://golang.org/pkg/time/#ParseDuration). For example, "@every 1h30m10s" would indicate a schedule that activates after 1 hour, 30 minutes, 10 seconds, and then every interval after that. Note: The interval does not take the job runtime into account. For example, if a job takes 3 minutes to run, and it is scheduled to run every 5 minutes, it will have only 2 minutes of idle time between each run. By default, all interpretation and scheduling is done in the machine's local time zone (time.Local). You can specify a different time zone on construction: Individual cron schedules may also override the time zone they are to be interpreted in by providing an additional space-separated field at the beginning of the cron spec, of the form "CRON_TZ=Asia/Tokyo". For example: The prefix "TZ=(TIME ZONE)" is also supported for legacy compatibility. Be aware that jobs scheduled during daylight-savings leap-ahead transitions will not be run! A Cron runner may be configured with a chain of job wrappers to add cross-cutting functionality to all submitted jobs. For example, they may be used to achieve the following effects: Install wrappers for all jobs added to a cron using the `cron.WithChain` option: Install wrappers for individual jobs by explicitly wrapping them: Since the Cron service runs concurrently with the calling code, some amount of care must be taken to ensure proper synchronization. All cron methods are designed to be correctly synchronized as long as the caller ensures that invocations have a clear happens-before ordering between them. Cron defines a Logger interface that is a subset of the one defined in github.com/go-logr/logr. It has two logging levels (Info and Error), and parameters are key/value pairs. This makes it possible for cron logging to plug into structured logging systems. An adapter, [Verbose]PrintfLogger, is provided to wrap the standard library *log.Logger. For additional insight into Cron operations, verbose logging may be activated which will record job runs, scheduling decisions, and added or removed jobs. Activate it with a one-off logger as follows: Cron entries are stored in an array, sorted by their next activation time. Cron sleeps until the next job is due to be run. Upon waking:

Package cron implements a cron spec parser and job runner. Callers may register Funcs to be invoked on a given schedule. Cron will run them in their own goroutines. A cron expression represents a set of times, using 6 space-separated fields. Note: Month and Day-of-week field values are case insensitive. "SUN", "Sun", and "sun" are equally accepted. Asterisk ( * ) The asterisk indicates that the cron expression will match for all values of the field; e.g., using an asterisk in the 5th field (month) would indicate every month. Slash ( / ) Slashes are used to describe increments of ranges. For example 3-59/15 in the 1st field (minutes) would indicate the 3rd minute of the hour and every 15 minutes thereafter. The form "*\/..." is equivalent to the form "first-last/...", that is, an increment over the largest possible range of the field. The form "N/..." is accepted as meaning "N-MAX/...", that is, starting at N, use the increment until the end of that specific range. It does not wrap around. Comma ( , ) Commas are used to separate items of a list. For example, using "MON,WED,FRI" in the 5th field (day of week) would mean Mondays, Wednesdays and Fridays. Hyphen ( - ) Hyphens are used to define ranges. For example, 9-17 would indicate every hour between 9am and 5pm inclusive. Question mark ( ? ) Question mark may be used instead of '*' for leaving either day-of-month or day-of-week blank. You may use one of several pre-defined schedules in place of a cron expression. You may also schedule a job to execute at fixed intervals, starting at the time it's added or cron is run. This is supported by formatting the cron spec like this: where "duration" is a string accepted by time.ParseDuration (http://golang.org/pkg/time/#ParseDuration). For example, "@every 1h30m10s" would indicate a schedule that activates after 1 hour, 30 minutes, 10 seconds, and then every interval after that. Note: The interval does not take the job runtime into account. For example, if a job takes 3 minutes to run, and it is scheduled to run every 5 minutes, it will have only 2 minutes of idle time between each run. All interpretation and scheduling is done in the machine's local time zone (as provided by the Go time package (http://www.golang.org/pkg/time). Be aware that jobs scheduled during daylight-savings leap-ahead transitions will not be run! Since the Cron service runs concurrently with the calling code, some amount of care must be taken to ensure proper synchronization. All cron methods are designed to be correctly synchronized as long as the caller ensures that invocations have a clear happens-before ordering between them. Cron entries are stored in an array, sorted by their next activation time. Cron sleeps until the next job is due to be run. Upon waking:

Package dns implements a full featured interface to the Domain Name System. Both server- and client-side programming is supported. The package allows complete control over what is sent out to the DNS. The API follows the less-is-more principle, by presenting a small, clean interface. It supports (asynchronous) querying/replying, incoming/outgoing zone transfers, TSIG, EDNS0, dynamic updates, notifies and DNSSEC validation/signing. Note that domain names MUST be fully qualified before sending them, unqualified names in a message will result in a packing failure. Resource records are native types. They are not stored in wire format. Basic usage pattern for creating a new resource record: Or directly from a string: Or when the default origin (.) and TTL (3600) and class (IN) suit you: Or even: In the DNS messages are exchanged, these messages contain resource records (sets). Use pattern for creating a message: Or when not certain if the domain name is fully qualified: The message m is now a message with the question section set to ask the MX records for the miek.nl. zone. The following is slightly more verbose, but more flexible: After creating a message it can be sent. Basic use pattern for synchronous querying the DNS at a server configured on 127.0.0.1 and port 53: Suppressing multiple outstanding queries (with the same question, type and class) is as easy as setting: More advanced options are available using a net.Dialer and the corresponding API. For example it is possible to set a timeout, or to specify a source IP address and port to use for the connection: If these "advanced" features are not needed, a simple UDP query can be sent, with: When this functions returns you will get DNS message. A DNS message consists out of four sections. The question section: in.Question, the answer section: in.Answer, the authority section: in.Ns and the additional section: in.Extra. Each of these sections (except the Question section) contain a []RR. Basic use pattern for accessing the rdata of a TXT RR as the first RR in the Answer section: Both domain names and TXT character strings are converted to presentation form both when unpacked and when converted to strings. For TXT character strings, tabs, carriage returns and line feeds will be converted to \t, \r and \n respectively. Back slashes and quotations marks will be escaped. Bytes below 32 and above 127 will be converted to \DDD form. For domain names, in addition to the above rules brackets, periods, spaces, semicolons and the at symbol are escaped. DNSSEC (DNS Security Extension) adds a layer of security to the DNS. It uses public key cryptography to sign resource records. The public keys are stored in DNSKEY records and the signatures in RRSIG records. Requesting DNSSEC information for a zone is done by adding the DO (DNSSEC OK) bit to a request. Signature generation, signature verification and key generation are all supported. Dynamic updates reuses the DNS message format, but renames three of the sections. Question is Zone, Answer is Prerequisite, Authority is Update, only the Additional is not renamed. See RFC 2136 for the gory details. You can set a rather complex set of rules for the existence of absence of certain resource records or names in a zone to specify if resource records should be added or removed. The table from RFC 2136 supplemented with the Go DNS function shows which functions exist to specify the prerequisites. The prerequisite section can also be left empty. If you have decided on the prerequisites you can tell what RRs should be added or deleted. The next table shows the options you have and what functions to call. An TSIG or transaction signature adds a HMAC TSIG record to each message sent. The supported algorithms include: HmacSHA1, HmacSHA256 and HmacSHA512. Basic use pattern when querying with a TSIG name "axfr." (note that these key names must be fully qualified - as they are domain names) and the base64 secret "so6ZGir4GPAqINNh9U5c3A==": If an incoming message contains a TSIG record it MUST be the last record in the additional section (RFC2845 3.2). This means that you should make the call to SetTsig last, right before executing the query. If you make any changes to the RRset after calling SetTsig() the signature will be incorrect. When requesting an zone transfer (almost all TSIG usage is when requesting zone transfers), with TSIG, this is the basic use pattern. In this example we request an AXFR for miek.nl. with TSIG key named "axfr." and secret "so6ZGir4GPAqINNh9U5c3A==" and using the server 176.58.119.54: You can now read the records from the transfer as they come in. Each envelope is checked with TSIG. If something is not correct an error is returned. A custom TSIG implementation can be used. This requires additional code to perform any session establishment and signature generation/verification. The client must be configured with an implementation of the TsigProvider interface: Basic use pattern validating and replying to a message that has TSIG set. RFC 6895 sets aside a range of type codes for private use. This range is 65,280 - 65,534 (0xFF00 - 0xFFFE). When experimenting with new Resource Records these can be used, before requesting an official type code from IANA. See https://miek.nl/2014/september/21/idn-and-private-rr-in-go-dns/ for more information. EDNS0 is an extension mechanism for the DNS defined in RFC 2671 and updated by RFC 6891. It defines a new RR type, the OPT RR, which is then completely abused. Basic use pattern for creating an (empty) OPT RR: The rdata of an OPT RR consists out of a slice of EDNS0 (RFC 6891) interfaces. Currently only a few have been standardized: EDNS0_NSID (RFC 5001) and EDNS0_SUBNET (RFC 7871). Note that these options may be combined in an OPT RR. Basic use pattern for a server to check if (and which) options are set: SIG(0) From RFC 2931: It works like TSIG, except that SIG(0) uses public key cryptography, instead of the shared secret approach in TSIG. Supported algorithms: ECDSAP256SHA256, ECDSAP384SHA384, RSASHA1, RSASHA256 and RSASHA512. Signing subsequent messages in multi-message sessions is not implemented.

btcd is a full-node bitcoin implementation written in Go. The default options are sane for most users. This means btcd will work 'out of the box' for most users. However, there are also a wide variety of flags that can be used to control it. The following section provides a usage overview which enumerates the flags. An interesting point to note is that the long form of all of these options (except -C) can be specified in a configuration file that is automatically parsed when btcd starts up. By default, the configuration file is located at ~/.btcd/btcd.conf on POSIX-style operating systems and %LOCALAPPDATA%\btcd\btcd.conf on Windows. The -C (--configfile) flag, as shown below, can be used to override this location. Usage: Application Options: Help Options:

Package storage provides an easy way to work with Google Cloud Storage. Google Cloud Storage stores data in named objects, which are grouped into buckets. More information about Google Cloud Storage is available at https://cloud.google.com/storage/docs. See https://pkg.go.dev/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. To start working with this package, create a Client: The client will use your default application credentials. Clients should be reused instead of created as needed. The methods of Client are safe for concurrent use by multiple goroutines. You may configure the client by passing in options from the google.golang.org/api/option package. You may also use options defined in this package, such as WithJSONReads. If you only wish to access public data, you can create an unauthenticated client with To use an emulator with this library, you can set the STORAGE_EMULATOR_HOST environment variable to the address at which your emulator is running. This will send requests to that address instead of to Cloud Storage. You can then create and use a client as usual: Please note that there is no official emulator for Cloud Storage. A Google Cloud Storage bucket is a collection of objects. To work with a bucket, make a bucket handle: A handle is a reference to a bucket. You can have a handle even if the bucket doesn't exist yet. To create a bucket in Google Cloud Storage, call BucketHandle.Create: Note that although buckets are associated with projects, bucket names are global across all projects. Each bucket has associated metadata, represented in this package by BucketAttrs. The third argument to BucketHandle.Create allows you to set the initial BucketAttrs of a bucket. To retrieve a bucket's attributes, use BucketHandle.Attrs: An object holds arbitrary data as a sequence of bytes, like a file. You refer to objects using a handle, just as with buckets, but unlike buckets you don't explicitly create an object. Instead, the first time you write to an object it will be created. You can use the standard Go io.Reader and io.Writer interfaces to read and write object data: Objects also have attributes, which you can fetch with ObjectHandle.Attrs: Listing objects in a bucket is done with the BucketHandle.Objects method: Objects are listed lexicographically by name. To filter objects lexicographically, [Query.StartOffset] and/or [Query.EndOffset] can be used: If only a subset of object attributes is needed when listing, specifying this subset using Query.SetAttrSelection may speed up the listing process: Both objects and buckets have ACLs (Access Control Lists). An ACL is a list of ACLRules, each of which specifies the role of a user, group or project. ACLs are suitable for fine-grained control, but you may prefer using IAM to control access at the project level (see Cloud Storage IAM docs. To list the ACLs of a bucket or object, obtain an ACLHandle and call ACLHandle.List: You can also set and delete ACLs. Every object has a generation and a metageneration. The generation changes whenever the content changes, and the metageneration changes whenever the metadata changes. Conditions let you check these values before an operation; the operation only executes if the conditions match. You can use conditions to prevent race conditions in read-modify-write operations. For example, say you've read an object's metadata into objAttrs. Now you want to write to that object, but only if its contents haven't changed since you read it. Here is how to express that: You can obtain a URL that lets anyone read or write an object for a limited time. Signing a URL requires credentials authorized to sign a URL. To use the same authentication that was used when instantiating the Storage client, use BucketHandle.SignedURL. You can also sign a URL without creating a client. See the documentation of SignedURL for details. A type of signed request that allows uploads through HTML forms directly to Cloud Storage with temporary permission. Conditions can be applied to restrict how the HTML form is used and exercised by a user. For more information, please see the XML POST Object docs as well as the documentation of BucketHandle.GenerateSignedPostPolicyV4. If the GoogleAccessID and PrivateKey option fields are not provided, they will be automatically detected by BucketHandle.SignedURL and BucketHandle.GenerateSignedPostPolicyV4 if any of the following are true: Detecting GoogleAccessID may not be possible if you are authenticated using a token source or using option.WithHTTPClient. In this case, you can provide a service account email for GoogleAccessID and the client will attempt to sign the URL or Post Policy using that service account. To generate the signature, you must have: Errors returned by this client are often of the type googleapi.Error. These errors can be introspected for more information by using errors.As with the richer googleapi.Error type. For example: Methods in this package may retry calls that fail with transient errors. Retrying continues indefinitely unless the controlling context is canceled, the client is closed, or a non-transient error is received. To stop retries from continuing, use context timeouts or cancellation. The retry strategy in this library follows best practices for Cloud Storage. By default, operations are retried only if they are idempotent, and exponential backoff with jitter is employed. In addition, errors are only retried if they are defined as transient by the service. See the Cloud Storage retry docs for more information. Users can configure non-default retry behavior for a single library call (using BucketHandle.Retryer and ObjectHandle.Retryer) or for all calls made by a client (using Client.SetRetry). For example: You can add custom headers to any API call made by this package by using callctx.SetHeaders on the context which is passed to the method. For example, to add a custom audit logging header: This package includes support for the Cloud Storage gRPC API. The implementation uses gRPC rather than the Default JSON & XML APIs to make requests to Cloud Storage. The Go Storage gRPC client is generally available. The Notifications, Serivce Account HMAC and GetServiceAccount RPCs are not supported through the gRPC client. To create a client which will use gRPC, use the alternate constructor: Using the gRPC API inside GCP with a bucket in the same region can allow for Direct Connectivity (enabling requests to skip some proxy steps and reducing response latency). A warning is emmitted if gRPC is not used within GCP to warn that Direct Connectivity could not be initialized. Direct Connectivity is not required to access the gRPC API. Dependencies for the gRPC API may slightly increase the size of binaries for applications depending on this package. If you are not using gRPC, you can use the build tag `disable_grpc_modules` to opt out of these dependencies and reduce the binary size. The gRPC client emits metrics by default and will export the gRPC telemetry discussed in gRFC/66 and gRFC/78 to Google Cloud Monitoring. The metrics are accessible through Cloud Monitoring API and you incur no additional cost for publishing the metrics. Google Cloud Support can use this information to more quickly diagnose problems related to GCS and gRPC. Sending this data does not incur any billing charges, and requires minimal CPU (a single RPC every minute) or memory (a few KiB to batch the telemetry). To access the metrics you can view them through Cloud Monitoring metric explorer with the prefix `storage.googleapis.com/client`. Metrics are emitted every minute. You can disable metrics using the following example when creating a new gRPC client using WithDisabledClientMetrics. The metrics exporter uses Cloud Monitoring API which determines project ID and credentials doing the following: * Project ID is determined using OTel Resource Detector for the environment otherwise it falls back to the project provided by google.FindCredentials. * Credentials are determined using Application Default Credentials. The principal must have `roles/monitoring.metricWriter` role granted. If not a logged warning will be emitted. Subsequent are silenced to prevent noisy logs. Certain control plane and long-running operations for Cloud Storage (including Folder and Managed Folder operations) are supported via the autogenerated Storage Control client, which is available as a subpackage in this module. See package docs at cloud.google.com/go/storage/control/apiv2 or reference the Storage Control API docs.

Package trace provides an implementation of the tracing part of the OpenTelemetry API. To participate in distributed traces a Span needs to be created for the operation being performed as part of a traced workflow. In its simplest form: A Tracer is unique to the instrumentation and is used to create Spans. Instrumentation should be designed to accept a TracerProvider from which it can create its own unique Tracer. Alternatively, the registered global TracerProvider from the go.opentelemetry.io/otel package can be used as a default. This package does not conform to the standard Go versioning policy; all of its interfaces may have methods added to them without a package major version bump. This non-standard API evolution could surprise an uninformed implementation author. They could unknowingly build their implementation in a way that would result in a runtime panic for their users that update to the new API. The API is designed to help inform an instrumentation author about this non-standard API evolution. It requires them to choose a default behavior for unimplemented interface methods. There are three behavior choices they can make: All interfaces in this API embed a corresponding interface from go.opentelemetry.io/otel/trace/embedded. If an author wants the default behavior of their implementations to be a compilation failure, signaling to their users they need to update to the latest version of that implementation, they need to embed the corresponding interface from go.opentelemetry.io/otel/trace/embedded in their implementation. For example, If an author wants the default behavior of their implementations to panic, they can embed the API interface directly. This option is not recommended. It will lead to publishing packages that contain runtime panics when users update to newer versions of go.opentelemetry.io/otel/trace, which may be done with a transitive dependency. Finally, an author can embed another implementation in theirs. The embedded implementation will be used for methods not defined by the author. For example, an author who wants to default to silently dropping the call can use go.opentelemetry.io/otel/trace/noop: It is strongly recommended that authors only embed go.opentelemetry.io/otel/trace/noop if they choose this default behavior. That implementation is the only one OpenTelemetry authors can guarantee will fully implement all the API interfaces when a user updates their API.

Package metric provides an implementation of the OpenTelemetry metrics SDK. See https://opentelemetry.io/docs/concepts/signals/metrics/ for information about the concept of OpenTelemetry metrics and https://opentelemetry.io/docs/concepts/components/ for more information about OpenTelemetry SDKs. The entry point for the metric package is the MeterProvider. It is the object that all API calls use to create Meters, instruments, and ultimately make metric measurements. Also, it is an object that should be used to control the life-cycle (start, flush, and shutdown) of the SDK. A MeterProvider needs to be configured to export the measured data, this is done by configuring it with a Reader implementation (using the WithReader MeterProviderOption). Readers take two forms: ones that push to an endpoint (NewPeriodicReader), and ones that an endpoint pulls from. See go.opentelemetry.io/otel/exporters for exporters that can be used as or with these Readers. Each Reader, when registered with the MeterProvider, can be augmented with a View. Views allow users that run OpenTelemetry instrumented code to modify the generated data of that instrumentation. The data generated by a MeterProvider needs to include information about its origin. A MeterProvider needs to be configured with a Resource, using the WithResource MeterProviderOption, to include this information. This Resource should be used to describe the unique runtime environment instrumented code is being run on. That way when multiple instances of the code are collected at a single endpoint their origin is decipherable. To avoid leaking memory, the SDK returns the same instrument for calls to create new instruments with the same Name, Unit, and Description. Importantly, callbacks provided using metric.WithFloat64Callback or metric.WithInt64Callback will only apply for the first instrument created with a given Name, Unit, and Description. Instead, use Meter.RegisterCallback and Registration.Unregister to add and remove callbacks without leaking memory. See go.opentelemetry.io/otel/metric for more information about the metric API. See go.opentelemetry.io/otel/sdk/metric/internal/x for information about the experimental features. To enable metrics in your application using the SDK, you'll need to have an initialized MeterProvider that will let you create a go.opentelemetry.io/otel/metric.Meter. Here's how you might initialize a metrics provider.

Package bigtable is an API to Google Cloud Bigtable. See https://cloud.google.com/bigtable/docs/ for general product documentation. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. The principal way to read from a Bigtable is to use the ReadRows method on *Table. A RowRange specifies a contiguous portion of a table. A Filter may be provided through RowFilter to limit or transform the data that is returned. To read a single row, use the ReadRow helper method: This API exposes two distinct forms of writing to a Bigtable: a Mutation and a ReadModifyWrite. The former expresses idempotent operations. The latter expresses non-idempotent operations and returns the new values of updated cells. These operations are performed by creating a Mutation or ReadModifyWrite (with NewMutation or NewReadModifyWrite), building up one or more operations on that, and then using the Apply or ApplyReadModifyWrite methods on a Table. For instance, to set a couple of cells in a table: To increment an encoded value in one cell: If a read or write operation encounters a transient error it will be retried until a successful response, an unretryable error or the context deadline is reached. Non-idempotent writes (where the timestamp is set to ServerTime) will not be retried. In the case of ReadRows, retried calls will not re-scan rows that have already been processed.

Package tview implements rich widgets for terminal based user interfaces. The widgets provided with this package are useful for data exploration and data entry. The package implements the following widgets: The package also provides Application which is used to poll the event queue and draw widgets on screen. The following is a very basic example showing a box with the title "Hello, world!": First, we create a box primitive with a border and a title. Then we create an application, set the box as its root primitive, and run the event loop. The application exits when the application's Application.Stop function is called or when Ctrl-C is pressed. You will find more demos in the "demos" subdirectory. It also contains a presentation (written using tview) which gives an overview of the different widgets and how they can be used. Throughout this package, styles are specified using the tcell.Style type. Styles specify colors with the tcell.Color type. Functions such as tcell.GetColor, tcell.NewHexColor, and tcell.NewRGBColor can be used to create colors from W3C color names or RGB values. The tcell.Style type also allows you to specify text attributes such as "bold" or "underline" or a URL which some terminals use to display hyperlinks. Almost all strings which are displayed may contain style tags. A style tag's content is always wrapped in square brackets. In its simplest form, a style tag specifies the foreground color of the text. Colors in these tags are W3C color names or six hexadecimal digits following a hash tag. Examples: A style tag changes the style of the characters following that style tag. There is no style stack and no nesting of style tags. Style tags are used in almost everything from box titles, list text, form item labels, to table cells. In a TextView, this functionality has to be switched on explicitly. See the TextView documentation for more information. A style tag's full format looks like this: Each of the four fields can be left blank and trailing fields can be omitted. (Empty square brackets "[]", however, are not considered style tags.) Fields that are not specified will be left unchanged. A field with just a dash ("-") means "reset to default". You can specify the following flags to turn on certain attributes (some flags may not be supported by your terminal): Use uppercase letters to turn off the corresponding attribute, for example, "B" to turn off bold. Uppercase letters have no effect if the attribute was not previously set. Setting a URL allows you to turn a piece of text into a hyperlink in some terminals. Specify a dash ("-") to specify the end of the hyperlink. Hyperlinks must only contain single-byte characters (e.g. ASCII) and they may not contain bracket characters ("[" or "]"). Examples: In the rare event that you want to display a string such as "[red]" or "[#00ff1a]" without applying its effect, you need to put an opening square bracket before the closing square bracket. Note that the text inside the brackets will be matched less strictly than region or colors tags. I.e. any character that may be used in color or region tags will be recognized. Examples: You can use the Escape() function to insert brackets automatically where needed. When primitives are instantiated, they are initialized with colors taken from the global Styles variable. You may change this variable to adapt the look and feel of the primitives to your preferred style. Note that most terminals will not report information about their color theme. This package therefore does not support using the terminal's color theme. The default style is a dark theme and you must change the Styles variable to switch to a light (or other) theme. This package supports all unicode characters supported by your terminal. If your terminal supports mouse events, you can enable mouse support for your application by calling Application.EnableMouse. Note that this may interfere with your terminal's default mouse behavior. Mouse support is disabled by default. Many functions in this package are not thread-safe. For many applications, this is not an issue: If your code makes changes in response to key events, the corresponding callback function will execute in the main goroutine and thus will not cause any race conditions. (Exceptions to this are documented.) If you access your primitives from other goroutines, however, you will need to synchronize execution. The easiest way to do this is to call Application.QueueUpdate or Application.QueueUpdateDraw (see the function documentation for details): One exception to this is the io.Writer interface implemented by TextView. You can safely write to a TextView from any goroutine. See the TextView documentation for details. You can also call Application.Draw from any goroutine without having to wrap it in Application.QueueUpdate. And, as mentioned above, key event callbacks are executed in the main goroutine and thus should not use Application.QueueUpdate as that may lead to deadlocks. It is also not necessary to call Application.Draw from such callbacks as it will be called automatically. All widgets listed above contain the Box type. All of Box's functions are therefore available for all widgets, too. Please note that if you are using the functions of Box on a subclass, they will return a *Box, not the subclass. This is a Golang limitation. So while tview supports method chaining in many places, these chains must be broken when using Box's functions. Example: You will need to call Box.SetBorder separately: All widgets also implement the Primitive interface. The tview package's rendering is based on version 2 of https://github.com/gdamore/tcell. It uses types and constants from that package (e.g. colors, styles, and keyboard values).

Package spanner provides a client for reading and writing to Cloud Spanner databases. See the packages under admin for clients that operate on databases and instances. See https://cloud.google.com/spanner/docs/getting-started/go/ for an introduction to Cloud Spanner and additional help on using this API. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. To start working with this package, create a client that refers to the database of interest: Remember to close the client after use to free up the sessions in the session pool. To use an emulator with this library, you can set the SPANNER_EMULATOR_HOST environment variable to the address at which your emulator is running. This will send requests to that address instead of to Cloud Spanner. You can then create and use a client as usual: Two Client methods, Apply and Single, work well for simple reads and writes. As a quick introduction, here we write a new row to the database and read it back: All the methods used above are discussed in more detail below. Every Cloud Spanner row has a unique key, composed of one or more columns. Construct keys with a literal of type Key: The keys of a Cloud Spanner table are ordered. You can specify ranges of keys using the KeyRange type: By default, a KeyRange includes its start key but not its end key. Use the Kind field to specify other boundary conditions: A KeySet represents a set of keys. A single Key or KeyRange can act as a KeySet. Use the KeySets function to build the union of several KeySets: AllKeys returns a KeySet that refers to all the keys in a table: All Cloud Spanner reads and writes occur inside transactions. There are two types of transactions, read-only and read-write. Read-only transactions cannot change the database, do not acquire locks, and may access either the current database state or states in the past. Read-write transactions can read the database before writing to it, and always apply to the most recent database state. The simplest and fastest transaction is a ReadOnlyTransaction that supports a single read operation. Use Client.Single to create such a transaction. You can chain the call to Single with a call to a Read method. When you only want one row whose key you know, use ReadRow. Provide the table name, key, and the columns you want to read: Read multiple rows with the Read method. It takes a table name, KeySet, and list of columns: Read returns a RowIterator. You can call the Do method on the iterator and pass a callback: RowIterator also follows the standard pattern for the Google Cloud Client Libraries: Always call Stop when you finish using an iterator this way, whether or not you iterate to the end. (Failing to call Stop could lead you to exhaust the database's session quota.) To read rows with an index, use ReadUsingIndex. The most general form of reading uses SQL statements. Construct a Statement with NewStatement, setting any parameters using the Statement's Params map: You can also construct a Statement directly with a struct literal, providing your own map of parameters. Use the Query method to run the statement and obtain an iterator: Once you have a Row, via an iterator or a call to ReadRow, you can extract column values in several ways. Pass in a pointer to a Go variable of the appropriate type when you extract a value. You can extract by column position or name: You can extract all the columns at once: Or you can define a Go struct that corresponds to your columns, and extract into that: For Cloud Spanner columns that may contain NULL, use one of the NullXXX types, like NullString: To perform more than one read in a transaction, use ReadOnlyTransaction: You must call Close when you are done with the transaction. Cloud Spanner read-only transactions conceptually perform all their reads at a single moment in time, called the transaction's read timestamp. Once a read has started, you can call ReadOnlyTransaction's Timestamp method to obtain the read timestamp. By default, a transaction will pick the most recent time (a time where all previously committed transactions are visible) for its reads. This provides the freshest data, but may involve some delay. You can often get a quicker response if you are willing to tolerate "stale" data. You can control the read timestamp selected by a transaction by calling the WithTimestampBound method on the transaction before using it. For example, to perform a query on data that is at most one minute stale, use See the documentation of TimestampBound for more details. To write values to a Cloud Spanner database, construct a Mutation. The spanner package has functions for inserting, updating and deleting rows. Except for the Delete methods, which take a Key or KeyRange, each mutation-building function comes in three varieties. One takes lists of columns and values along with the table name: One takes a map from column names to values: And the third accepts a struct value, and determines the columns from the struct field names: To apply a list of mutations to the database, use Apply: If you need to read before writing in a single transaction, use a ReadWriteTransaction. ReadWriteTransactions may be aborted automatically by the backend and need to be retried. You pass in a function to ReadWriteTransaction, and the client will handle the retries automatically. Use the transaction's BufferWrite method to buffer mutations, which will all be executed at the end of the transaction: Cloud Spanner STRUCT (aka STRUCT) values (https://cloud.google.com/spanner/docs/data-types#struct-type) can be represented by a Go struct value. A proto StructType is built from the field types and field tag information of the Go struct. If a field in the struct type definition has a "spanner:<field_name>" tag, then the value of the "spanner" key in the tag is used as the name for that field in the built StructType, otherwise the field name in the struct definition is used. To specify a field with an empty field name in a Cloud Spanner STRUCT type, use the `spanner:""` tag annotation against the corresponding field in the Go struct's type definition. A STRUCT value can contain STRUCT-typed and Array-of-STRUCT typed fields and these can be specified using named struct-typed and []struct-typed fields inside a Go struct. However, embedded struct fields are not allowed. Unexported struct fields are ignored. NULL STRUCT values in Cloud Spanner are typed. A nil pointer to a Go struct value can be used to specify a NULL STRUCT value of the corresponding StructType. Nil and empty slices of a Go STRUCT type can be used to specify NULL and empty array values respectively of the corresponding StructType. A slice of pointers to a Go struct type can be used to specify an array of NULL-able STRUCT values. Spanner supports DML statements like INSERT, UPDATE and DELETE. Use ReadWriteTransaction.Update to run DML statements. It returns the number of rows affected. (You can call use ReadWriteTransaction.Query with a DML statement. The first call to Next on the resulting RowIterator will return iterator.Done, and the RowCount field of the iterator will hold the number of affected rows.) For large databases, it may be more efficient to partition the DML statement. Use client.PartitionedUpdate to run a DML statement in this way. Not all DML statements can be partitioned. This client has been instrumented to use OpenCensus tracing (http://opencensus.io). To enable tracing, see "Enabling Tracing for a Program" at https://godoc.org/go.opencensus.io/trace. OpenCensus tracing requires Go 1.8 or higher.

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

Package amqp is an AMQP 0.9.1 client with RabbitMQ extensions Understand the AMQP 0.9.1 messaging model by reviewing these links first. Much of the terminology in this library directly relates to AMQP concepts. Most other broker clients publish to queues, but in AMQP, clients publish Exchanges instead. AMQP is programmable, meaning that both the producers and consumers agree on the configuration of the broker, instead of requiring an operator or system configuration that declares the logical topology in the broker. The routing between producers and consumer queues is via Bindings. These bindings form the logical topology of the broker. In this library, a message sent from publisher is called a "Publishing" and a message received to a consumer is called a "Delivery". The fields of Publishings and Deliveries are close but not exact mappings to the underlying wire format to maintain stronger types. Many other libraries will combine message properties with message headers. In this library, the message well known properties are strongly typed fields on the Publishings and Deliveries, whereas the user defined headers are in the Headers field. The method naming closely matches the protocol's method name with positional parameters mapping to named protocol message fields. The motivation here is to present a comprehensive view over all possible interactions with the server. Generally, methods that map to protocol methods of the "basic" class will be elided in this interface, and "select" methods of various channel mode selectors will be elided for example Channel.Confirm and Channel.Tx. The library is intentionally designed to be synchronous, where responses for each protocol message are required to be received in an RPC manner. Some methods have a noWait parameter like Channel.QueueDeclare, and some methods are asynchronous like Channel.Publish. The error values should still be checked for these methods as they will indicate IO failures like when the underlying connection closes. Clients of this library may be interested in receiving some of the protocol messages other than Deliveries like basic.ack methods while a channel is in confirm mode. The Notify* methods with Connection and Channel receivers model the pattern of asynchronous events like closes due to exceptions, or messages that are sent out of band from an RPC call like basic.ack or basic.flow. Any asynchronous events, including Deliveries and Publishings must always have a receiver until the corresponding chans are closed. Without asynchronous receivers, the sychronous methods will block. It's important as a client to an AMQP topology to ensure the state of the broker matches your expectations. For both publish and consume use cases, make sure you declare the queues, exchanges and bindings you expect to exist prior to calling Channel.Publish or Channel.Consume. SSL/TLS - Secure connections When Dial encounters an amqps:// scheme, it will use the zero value of a tls.Config. This will only perform server certificate and host verification. Use DialTLS when you wish to provide a client certificate (recommended), include a private certificate authority's certificate in the cert chain for server validity, or run insecure by not verifying the server certificate dial your own connection. DialTLS will use the provided tls.Config when it encounters an amqps:// scheme and will dial a plain connection when it encounters an amqp:// scheme. SSL/TLS in RabbitMQ is documented here: http://www.rabbitmq.com/ssl.html This exports a Session object that wraps this library. It automatically reconnects when the connection fails, and blocks all pushes until the connection succeeds. It also confirms every outgoing message, so none are lost. It doesn't automatically ack each message, but leaves that to the parent process, since it is usage-dependent. Try running this in one terminal, and `rabbitmq-server` in another. Stop & restart RabbitMQ to see how the queue reacts.

package forms is a lightweight, but incredibly useful library for parsing form data from an http.Request. It supports multipart forms, url-encoded forms, json data, and url query parameters. It also provides helper methods for converting data into other types and a Validator object which can be used to validate the data. Forms is framework-agnostic and works directly with the http package. For the full source code, example usage, and more, visit https://github.com/albrow/forms. Version 0.3.2

Package pflag is a drop-in replacement for Go's flag package, implementing POSIX/GNU-style --flags. pflag is compatible with the GNU extensions to the POSIX recommendations for command-line options. See http://www.gnu.org/software/libc/manual/html_node/Argument-Syntax.html Usage: pflag is a drop-in replacement of Go's native flag package. If you import pflag under the name "flag" then all code should continue to function with no changes. There is one exception to this: if you directly instantiate the Flag struct there is one more field "Shorthand" that you will need to set. Most code never instantiates this struct directly, and instead uses functions such as String(), BoolVar(), and Var(), and is therefore unaffected. Define flags using flag.String(), Bool(), Int(), etc. This declares an integer flag, -flagname, stored in the pointer ip, with type *int. If you like, you can bind the flag to a variable using the Var() functions. Or you can create custom flags that satisfy the Value interface (with pointer receivers) and couple them to flag parsing by For such flags, the default value is just the initial value of the variable. After all flags are defined, call to parse the command line into the defined flags. Flags may then be used directly. If you're using the flags themselves, they are all pointers; if you bind to variables, they're values. After parsing, the arguments after the flag are available as the slice flag.Args() or individually as flag.Arg(i). The arguments are indexed from 0 through flag.NArg()-1. The pflag package also defines some new functions that are not in flag, that give one-letter shorthands for flags. You can use these by appending 'P' to the name of any function that defines a flag. Shorthand letters can be used with single dashes on the command line. Boolean shorthand flags can be combined with other shorthand flags. Command line flag syntax: Unlike the flag package, a single dash before an option means something different than a double dash. Single dashes signify a series of shorthand letters for flags. All but the last shorthand letter must be boolean flags. Flag parsing stops after the terminator "--". Unlike the flag package, flags can be interspersed with arguments anywhere on the command line before this terminator. Integer flags accept 1234, 0664, 0x1234 and may be negative. Boolean flags (in their long form) accept 1, 0, t, f, true, false, TRUE, FALSE, True, False. Duration flags accept any input valid for time.ParseDuration. The default set of command-line flags is controlled by top-level functions. The FlagSet type allows one to define independent sets of flags, such as to implement subcommands in a command-line interface. The methods of FlagSet are analogous to the top-level functions for the command-line flag set.

Package sessions provides cookie and filesystem sessions and infrastructure for custom session backends. The key features are: Let's start with an example that shows the sessions API in a nutshell: First we initialize a session store calling NewCookieStore() and passing a secret key used to authenticate the session. Inside the handler, we call store.Get() to retrieve an existing session or a new one. Then we set some session values in session.Values, which is a map[interface{}]interface{}. And finally we call session.Save() to save the session in the response. Note that in production code, we should check for errors when calling session.Save(r, w), and either display an error message or otherwise handle it. Save must be called before writing to the response, otherwise the session cookie will not be sent to the client. That's all you need to know for the basic usage. Let's take a look at other options, starting with flash messages. Flash messages are session values that last until read. The term appeared with Ruby On Rails a few years back. When we request a flash message, it is removed from the session. To add a flash, call session.AddFlash(), and to get all flashes, call session.Flashes(). Here is an example: Flash messages are useful to set information to be read after a redirection, like after form submissions. There may also be cases where you want to store a complex datatype within a session, such as a struct. Sessions are serialised using the encoding/gob package, so it is easy to register new datatypes for storage in sessions: As it's not possible to pass a raw type as a parameter to a function, gob.Register() relies on us passing it a value of the desired type. In the example above we've passed it a pointer to a struct and a pointer to a custom type representing a map[string]interface. (We could have passed non-pointer values if we wished.) This will then allow us to serialise/deserialise values of those types to and from our sessions. Note that because session values are stored in a map[string]interface{}, there's a need to type-assert data when retrieving it. We'll use the Person struct we registered above: By default, session cookies last for a month. This is probably too long for some cases, but it is easy to change this and other attributes during runtime. Sessions can be configured individually or the store can be configured and then all sessions saved using it will use that configuration. We access session.Options or store.Options to set a new configuration. The fields are basically a subset of http.Cookie fields. Let's change the maximum age of a session to one week: Sometimes we may want to change authentication and/or encryption keys without breaking existing sessions. The CookieStore supports key rotation, and to use it you just need to set multiple authentication and encryption keys, in pairs, to be tested in order: New sessions will be saved using the first pair. Old sessions can still be read because the first pair will fail, and the second will be tested. This makes it easy to "rotate" secret keys and still be able to validate existing sessions. Note: for all pairs the encryption key is optional; set it to nil or omit it and and encryption won't be used. Multiple sessions can be used in the same request, even with different session backends. When this happens, calling Save() on each session individually would be cumbersome, so we have a way to save all sessions at once: it's sessions.Save(). Here's an example: This is possible because when we call Get() from a session store, it adds the session to a common registry. Save() uses it to save all registered sessions.

Package azcore implements an HTTP request/response middleware pipeline used by Azure SDK clients. The middleware consists of three components. A Policy can be implemented in two ways; as a first-class function for a stateless Policy, or as a method on a type for a stateful Policy. Note that HTTP requests made via the same pipeline share the same Policy instances, so if a Policy mutates its state it MUST be properly synchronized to avoid race conditions. A Policy's Do method is called when an HTTP request wants to be sent over the network. The Do method can perform any operation(s) it desires. For example, it can log the outgoing request, mutate the URL, headers, and/or query parameters, inject a failure, etc. Once the Policy has successfully completed its request work, it must call the Next() method on the *policy.Request instance in order to pass the request to the next Policy in the chain. When an HTTP response comes back, the Policy then gets a chance to process the response/error. The Policy instance can log the response, retry the operation if it failed due to a transient error or timeout, unmarshal the response body, etc. Once the Policy has successfully completed its response work, it must return the *http.Response and error instances to its caller. Template for implementing a stateless Policy: Template for implementing a stateful Policy: The Transporter interface is responsible for sending the HTTP request and returning the corresponding HTTP response or error. The Transporter is invoked by the last Policy in the chain. The default Transporter implementation uses a shared http.Client from the standard library. The same stateful/stateless rules for Policy implementations apply to Transporter implementations. To use the Policy and Transporter instances, an application passes them to the runtime.NewPipeline function. The specified Policy instances form a chain and are invoked in the order provided to NewPipeline followed by the Transporter. Once the Pipeline has been created, create a runtime.Request instance and pass it to Pipeline's Do method. The Pipeline.Do method sends the specified Request through the chain of Policy and Transporter instances. The response/error is then sent through the same chain of Policy instances in reverse order. For example, assuming there are Policy types PolicyA, PolicyB, and PolicyC along with TransportA. The flow of Request and Response looks like the following: The Request instance passed to Pipeline's Do method is a wrapper around an *http.Request. It also contains some internal state and provides various convenience methods. You create a Request instance by calling the runtime.NewRequest function: If the Request should contain a body, call the SetBody method. A seekable stream is required so that upon retry, the retry Policy instance can seek the stream back to the beginning before retrying the network request and re-uploading the body. Operations like JSON-MERGE-PATCH send a JSON null to indicate a value should be deleted. This requirement conflicts with the SDK's default marshalling that specifies "omitempty" as a means to resolve the ambiguity between a field to be excluded and its zero-value. In the above example, Name and Count are defined as pointer-to-type to disambiguate between a missing value (nil) and a zero-value (0) which might have semantic differences. In a PATCH operation, any fields left as nil are to have their values preserved. When updating a Widget's count, one simply specifies the new value for Count, leaving Name nil. To fulfill the requirement for sending a JSON null, the NullValue() function can be used. This sends an explict "null" for Count, indicating that any current value for Count should be deleted. When the HTTP response is received, the *http.Response is returned directly. Each Policy instance can inspect/mutate the *http.Response. To enable logging, set environment variable AZURE_SDK_GO_LOGGING to "all" before executing your program. By default the logger writes to stderr. This can be customized by calling log.SetListener, providing a callback that writes to the desired location. Any custom logging implementation MUST provide its own synchronization to handle concurrent invocations. See the docs for the log package for further details. Pageable operations return potentially large data sets spread over multiple GET requests. The result of each GET is a "page" of data consisting of a slice of items. Pageable operations can be identified by their New*Pager naming convention and return type of *runtime.Pager[T]. The call to WidgetClient.NewListWidgetsPager() returns an instance of *runtime.Pager[T] for fetching pages and determining if there are more pages to fetch. No IO calls are made until the NextPage() method is invoked. Long-running operations (LROs) are operations consisting of an initial request to start the operation followed by polling to determine when the operation has reached a terminal state. An LRO's terminal state is one of the following values. LROs can be identified by their Begin* prefix and their return type of *runtime.Poller[T]. When a call to WidgetClient.BeginCreateOrUpdate() returns a nil error, it means that the LRO has started. It does _not_ mean that the widget has been created or updated (or failed to be created/updated). The *runtime.Poller[T] provides APIs for determining the state of the LRO. To wait for the LRO to complete, call the PollUntilDone() method. The call to PollUntilDone() will block the current goroutine until the LRO has reached a terminal state or the context is canceled/timed out. Note that LROs can take anywhere from several seconds to several minutes. The duration is operation-dependent. Due to this variant behavior, pollers do _not_ have a preconfigured time-out. Use a context with the appropriate cancellation mechanism as required. Pollers provide the ability to serialize their state into a "resume token" which can be used by another process to recreate the poller. This is achieved via the runtime.Poller[T].ResumeToken() method. Note that a token can only be obtained for a poller that's in a non-terminal state. Also note that any subsequent calls to poller.Poll() might change the poller's state. In this case, a new token should be created. After the token has been obtained, it can be used to recreate an instance of the originating poller. When resuming a poller, no IO is performed, and zero-value arguments can be used for everything but the Options.ResumeToken. Resume tokens are unique per service client and operation. Attempting to resume a poller for LRO BeginB() with a token from LRO BeginA() will result in an error. The fake package contains types used for constructing in-memory fake servers used in unit tests. This allows writing tests to cover various success/error conditions without the need for connecting to a live service. Please see https://github.com/Azure/azure-sdk-for-go/tree/main/sdk/samples/fakes for details and examples on how to use fakes.

Package xid is a globally unique id generator suited for web scale Xid is using Mongo Object ID algorithm to generate globally unique ids: https://docs.mongodb.org/manual/reference/object-id/ The binary representation of the id is compatible with Mongo 12 bytes Object IDs. The string representation is using base32 hex (w/o padding) for better space efficiency when stored in that form (20 bytes). The hex variant of base32 is used to retain the sortable property of the id. Xid doesn't use base64 because case sensitivity and the 2 non alphanum chars may be an issue when transported as a string between various systems. Base36 wasn't retained either because 1/ it's not standard 2/ the resulting size is not predictable (not bit aligned) and 3/ it would not remain sortable. To validate a base32 `xid`, expect a 20 chars long, all lowercase sequence of `a` to `v` letters and `0` to `9` numbers (`[0-9a-v]{20}`). UUID is 16 bytes (128 bits), snowflake is 8 bytes (64 bits), xid stands in between with 12 bytes with a more compact string representation ready for the web and no required configuration or central generation server. Features: Best used with xlog's RequestIDHandler (https://godoc.org/github.com/rs/xlog#RequestIDHandler). References:

Gnostic is a tool for building better REST APIs through knowledge. Gnostic reads declarative descriptions of REST APIs that conform to the OpenAPI Specification, reports errors, resolves internal dependencies, and puts the results in a binary form that can be used in any language that is supported by the Protocol Buffer tools. Gnostic models are validated and typed. This allows API tool developers to focus on their product and not worry about input validation and type checking. Gnostic calls plugins that implement a variety of API implementation and support features including generation of client and server support code.

Gnostic is a tool for building better REST APIs through knowledge. Gnostic reads declarative descriptions of REST APIs that conform to the OpenAPI Specification, reports errors, resolves internal dependencies, and puts the results in a binary form that can be used in any language that is supported by the Protocol Buffer tools. Gnostic models are validated and typed. This allows API tool developers to focus on their product and not worry about input validation and type checking. Gnostic calls plugins that implement a variety of API implementation and support features including generation of client and server support code.

Package fuse enables writing FUSE file systems on Linux and FreeBSD. There are two approaches to writing a FUSE file system. The first is to speak the low-level message protocol, reading from a Conn using ReadRequest and writing using the various Respond methods. This approach is closest to the actual interaction with the kernel and can be the simplest one in contexts such as protocol translators. Servers of synthesized file systems tend to share common bookkeeping abstracted away by the second approach, which is to call fs.Serve to serve the FUSE protocol using an implementation of the service methods in the interfaces FS* (file system), Node* (file or directory), and Handle* (opened file or directory). There are a daunting number of such methods that can be written, but few are required. The specific methods are described in the documentation for those interfaces. The examples/hellofs subdirectory contains a simple illustration of the fs.Serve approach. The required and optional methods for the FS, Node, and Handle interfaces have the general form where Op is the name of a FUSE operation. Op reads request parameters from req and writes results to resp. An operation whose only result is the error result omits the resp parameter. Multiple goroutines may call service methods simultaneously; the methods being called are responsible for appropriate synchronization. The operation must not hold on to the request or response, including any []byte fields such as WriteRequest.Data or SetxattrRequest.Xattr. Operations can return errors. The FUSE interface can only communicate POSIX errno error numbers to file system clients, the message is not visible to file system clients. The returned error can implement ErrorNumber to control the errno returned. Without ErrorNumber, a generic errno (EIO) is returned. Error messages will be visible in the debug log as part of the response. In some file systems, some operations may take an undetermined amount of time. For example, a Read waiting for a network message or a matching Write might wait indefinitely. If the request is cancelled and no longer needed, the context will be cancelled. Blocking operations should select on a receive from ctx.Done() and attempt to abort the operation early if the receive succeeds (meaning the channel is closed). To indicate that the operation failed because it was aborted, return syscall.EINTR. If an operation does not block for an indefinite amount of time, supporting cancellation is not necessary. All requests types embed a Header, meaning that the method can inspect req.Pid, req.Uid, and req.Gid as necessary to implement permission checking. The kernel FUSE layer normally prevents other users from accessing the FUSE file system (to change this, see AllowOther), but does not enforce access modes (to change this, see DefaultPermissions). Behavior and metadata of the mounted file system can be changed by passing MountOption values to Mount.

Package gorilla/schema fills a struct with form values. The basic usage is really simple. Given this struct: ...we can fill it passing a map to the Decode() function: This is just a simple example and it doesn't make a lot of sense to create the map manually. Typically it will come from a http.Request object and will be of type url.Values, http.Request.Form, or http.Request.MultipartForm: Note: it is a good idea to set a Decoder instance as a package global, because it caches meta-data about structs, and an instance can be shared safely: To define custom names for fields, use a struct tag "schema". To not populate certain fields, use a dash for the name and it will be ignored: The supported field types in the destination struct are: Non-supported types are simply ignored, however custom types can be registered to be converted. To fill nested structs, keys must use a dotted notation as the "path" for the field. So for example, to fill the struct Person below: ...the source map must have the keys "Name", "Phone.Label" and "Phone.Number". This means that an HTML form to fill a Person struct must look like this: Single values are filled using the first value for a key from the source map. Slices are filled using all values for a key from the source map. So to fill a Person with multiple Phone values, like: ...an HTML form that accepts three Phone values would look like this: Notice that only for slices of structs the slice index is required. This is needed for disambiguation: if the nested struct also had a slice field, we could not translate multiple values to it if we did not use an index for the parent struct. There's also the possibility to create a custom type that implements the TextUnmarshaler interface, and in this case there's no need to register a converter, like: ...an HTML form that accepts three Email values would look like this:

Package aztables can access an Azure Storage or CosmosDB account. The aztables package is capable of: The Azure Data Tables library allows you to interact with two types of resources: * the tables in your account * the entities within those tables. Interaction with these resources starts with an instance of a client. To create a client object, you will need the account's table service endpoint URL and a credential that allows you to access the account. The clients support different forms of authentication. The aztables library supports any of the `azcore.TokenCredential` interfaces, authorization via a Connection String, or authorization with a Shared Access Signature token. To use an account shared key (aka account key or access key), provide the key as a string. This can be found in your storage account in the Azure Portal under the "Access Keys" section. Use the key as the credential parameter to authenticate the client: Using a Connection String Depending on your use case and authorization method, you may prefer to initialize a client instance with a connection string instead of providing the account URL and credential separately. To do this, pass the connection string to the client's `from_connection_string` class method. The connection string can be found in your storage account in the [Azure Portal][azure_portal_account_url] under the "Access Keys" section or with the following Azure CLI command: Using a Shared Access Signature To use a shared access signature (SAS) token, provide the token at the end of your service URL. You can generate a SAS token from the Azure Portal under Shared Access Signature or use the ServiceClient.GetAccountSASToken or Client.GetTableSASToken() functions. Common uses of the Table service included: * Storing TBs of structured data capable of serving web scale applications * Storing datasets that do not require complex joins, foreign keys, or stored procedures and can be de-normalized for fast access * Quickly querying data using a clustered index * Accessing data using the OData protocol and LINQ filter expressions The following components make up the Azure Data Tables Service: * The account * A table within the account, which contains a set of entities * An entity within a table, as a dictionary The Azure Data Tables client library for Go allows you to interact with each of these components through the use of a dedicated client object. Two different clients are provided to interact with the various components of the Table Service: 1. **`ServiceClient`** - 2. **`Client`** - Entities are similar to rows. An entity has a PartitionKey, a RowKey, and a set of properties. A property is a name value pair, similar to a column. Every entity in a table does not need to have the same properties. Entities are returned as JSON, allowing developers to use JSON marshalling and unmarshalling techniques. Additionally, you can use the aztables.EDMEntity to ensure proper round-trip serialization of all properties. The following sections provide several code snippets covering some of the most common Table tasks, including: * Creating a table * Creating entities * Querying entities Create a table in your account and get a `Client` to perform operations on the newly created table: Creating Entities Querying entities

Package saml contains a partial implementation of the SAML standard in golang. SAML is a standard for identity federation, i.e. either allowing a third party to authenticate your users or allowing third parties to rely on us to authenticate their users. In SAML parlance an Identity Provider (IDP) is a service that knows how to authenticate users. A Service Provider (SP) is a service that delegates authentication to an IDP. If you are building a service where users log in with someone else's credentials, then you are a Service Provider. This package supports implementing both service providers and identity providers. The core package contains the implementation of SAML. The package samlsp provides helper middleware suitable for use in Service Provider applications. The package samlidp provides a rudimentary IDP service that is useful for testing or as a starting point for other integrations. Version 0.4.0 introduces a few breaking changes to the _samlsp_ package in order to make the package more extensible, and to clean up the interfaces a bit. The default behavior remains the same, but you can now provide interface implementations of _RequestTracker_ (which tracks pending requests), _Session_ (which handles maintaining a session) and _OnError_ which handles reporting errors. Public fields of _samlsp.Middleware_ have changed, so some usages may require adjustment. See [issue 231](https://github.com/crewjam/saml/issues/231) for details. The option to provide an IDP metadata URL has been deprecated. Instead, we recommend that you use the `FetchMetadata()` function, or fetch the metadata yourself and use the new `ParseMetadata()` function, and pass the metadata in _samlsp.Options.IDPMetadata_. Similarly, the _HTTPClient_ field is now deprecated because it was only used for fetching metdata, which is no longer directly implemented. The fields that manage how cookies are set are deprecated as well. To customize how cookies are managed, provide custom implementation of _RequestTracker_ and/or _Session_, perhaps by extending the default implementations. The deprecated fields have not been removed from the Options structure, but will be in future. In particular we have deprecated the following fields in _samlsp.Options_: - `Logger` - This was used to emit errors while validating, which is an anti-pattern. - `IDPMetadataURL` - Instead use `FetchMetadata()` - `HTTPClient` - Instead pass httpClient to FetchMetadata - `CookieMaxAge` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieName` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider Let us assume we have a simple web application to protect. We'll modify this application so it uses SAML to authenticate users. ```golang package main import ( ) ``` Each service provider must have an self-signed X.509 key pair established. You can generate your own with something like this: We will use `samlsp.Middleware` to wrap the endpoint we want to protect. Middleware provides both an `http.Handler` to serve the SAML specific URLs and a set of wrappers to require the user to be logged in. We also provide the URL where the service provider can fetch the metadata from the IDP at startup. In our case, we'll use [samltest.id](https://samltest.id/), an identity provider designed for testing. ```golang package main import ( ) ``` Next we'll have to register our service provider with the identity provider to establish trust from the service provider to the IDP. For [samltest.id](https://samltest.id/), you can do something like: Navigate to https://samltest.id/upload.php and upload the file you fetched. Now you should be able to authenticate. The flow should look like this: 1. You browse to `localhost:8000/hello` 1. The middleware redirects you to `https://samltest.id/idp/profile/SAML2/Redirect/SSO` 1. samltest.id prompts you for a username and password. 1. samltest.id returns you an HTML document which contains an HTML form setup to POST to `localhost:8000/saml/acs`. The form is automatically submitted if you have javascript enabled. 1. The local service validates the response, issues a session cookie, and redirects you to the original URL, `localhost:8000/hello`. 1. This time when `localhost:8000/hello` is requested there is a valid session and so the main content is served. Please see `example/idp/` for a substantially complete example of how to use the library and helpers to be an identity provider. The SAML standard is huge and complex with many dark corners and strange, unused features. This package implements the most commonly used subset of these features required to provide a single sign on experience. The package supports at least the subset of SAML known as [interoperable SAML](http://saml2int.org). This package supports the Web SSO profile. Message flows from the service provider to the IDP are supported using the HTTP Redirect binding and the HTTP POST binding. Message flows from the IDP to the service provider are supported via the HTTP POST binding. The package can produce signed SAML assertions, and can validate both signed and encrypted SAML assertions. It does not support signed or encrypted requests. The _RelayState_ parameter allows you to pass user state information across the authentication flow. The most common use for this is to allow a user to request a deep link into your site, be redirected through the SAML login flow, and upon successful completion, be directed to the originally requested link, rather than the root. Unfortunately, _RelayState_ is less useful than it could be. Firstly, it is not authenticated, so anything you supply must be signed to avoid XSS or CSRF. Secondly, it is limited to 80 bytes in length, which precludes signing. (See section 3.6.3.1 of SAMLProfiles.) The SAML specification is a collection of PDFs (sadly): - [SAMLCore](http://docs.oasis-open.org/security/saml/v2.0/saml-core-2.0-os.pdf) defines data types. - [SAMLBindings](http://docs.oasis-open.org/security/saml/v2.0/saml-bindings-2.0-os.pdf) defines the details of the HTTP requests in play. - [SAMLProfiles](http://docs.oasis-open.org/security/saml/v2.0/saml-profiles-2.0-os.pdf) describes data flows. - [SAMLConformance](http://docs.oasis-open.org/security/saml/v2.0/saml-conformance-2.0-os.pdf) includes a support matrix for various parts of the protocol. [SAMLtest](https://samltest.id/) is a testing ground for SAML service and identity providers. Please do not report security issues in the issue tracker. Rather, please contact me directly at ross@kndr.org ([PGP Key `78B6038B3B9DFB88`](https://keybase.io/crewjam)).

Package grpcui provides a gRPC web UI in the form of HTTP handlers that can be added to a web server. This package provides multiple functions which, all combined, provide a fully functional web UI. Users of this package can use these pieces to embed a UI into any existing web application. The web form sources can be embedded in an existing HTML page, and the HTTP handlers wired up to make the form fully functional. For users that don't need as much control over layout and style of the web page, instead consider using standalone.Handler, which is an all-in-one handler that includes its own HTML and CSS as well as all other dependencies.

Package sling is a Go HTTP client library for creating and sending API requests. Slings store HTTP Request properties to simplify sending requests and decoding responses. Check the examples to learn how to compose a Sling into your API client. Use a Sling to set path, method, header, query, or body properties and create an http.Request. Use Path to set or extend the URL for created Requests. Extension means the path will be resolved relative to the existing URL. Use Get, Post, Put, Patch, Delete, or Head which are exactly the same as Path except they set the HTTP method too. Add or Set headers for requests created by a Sling. Define url parameter structs (https://godoc.org/github.com/google/go-querystring/query). Use QueryStruct to encode a struct as query parameters on requests. Define JSON tagged structs (https://golang.org/pkg/encoding/json/). Use BodyJSON to JSON encode a struct as the Body on requests. Requests will include an "application/json" Content-Type header. Define url tagged structs (https://godoc.org/github.com/google/go-querystring/query). Use BodyForm to form url encode a struct as the Body on requests. Requests will include an "application/x-www-form-urlencoded" Content-Type header. Use Body to set a plain io.Reader on requests created by a Sling. Set a content type header, if desired (e.g. Set("Content-Type", "text/plain")). Each Sling generates an http.Request (say with some path and query params) each time Request() is called, based on its state. When creating different slings, you may wish to extend an existing Sling to minimize duplication (e.g. a common client). Each Sling instance provides a New() method which creates an independent copy, so setting properties on the child won't mutate the parent Sling. Without the calls to base.New(), tweetShowSling and tweetPostSling would reference the base Sling and POST to "https://api.twitter.com/1.1/statuses/show.json/statuses/update.json", which is undesired. Recap: If you wish to extend a Sling, create a new child copy with New(). Define a JSON struct to decode a type from 2XX success responses. Use ReceiveSuccess(successV interface{}) to send a new Request and decode the response body into successV if it succeeds. Most APIs return failure responses with JSON error details. To decode these, define success and failure JSON structs. Use Receive(successV, failureV interface{}) to send a new Request that will automatically decode the response into the successV for 2XX responses or into failureV for non-2XX responses. Pass a nil successV or failureV argument to skip JSON decoding into that value.

Package httpexpect helps with end-to-end HTTP and REST API testing. See example directory: There are two common ways to test API with httpexpect: The second approach works only if the server is a Go module and its handler can be imported in tests. Concrete behaviour is determined by Client implementation passed to Config struct. If you're using http.Client, set its Transport field (http.RoundTriper) to one of the following: Note that http handler can be usually obtained from http framework you're using. E.g., echo framework provides either http.Handler or fasthttp.RequestHandler. You can also provide your own implementation of RequestFactory (creates http.Request), or Client (gets http.Request and returns http.Response). If you're starting server from tests, it's very handy to use net/http/httptest. Whenever values are checked for equality in httpexpect, they are converted to "canonical form": This is equivalent to subsequently json.Marshal() and json.Unmarshal() the value and currently is implemented so. When some check fails, failure is reported. If non-fatal failures are used (see Reporter interface), execution is continued and instance that was checked is marked as failed. If specific instance is marked as failed, all subsequent checks are ignored for this instance and for any child instances retrieved after failure. Example:

Package azcosmos implements the client to interact with the Azure Cosmos DB SQL API. The azcosmos package is capable of: Types of Credentials The clients support different forms of authentication. The azcosmos library supports authorization via Azure Active Directory or an account key. Using Azure Active Directory To create a client, you can use any of the TokenCredential implementations provided by `azidentity`. Using account keys To create a client, you will need the account's endpoint URL and a key credential. Using connection string To create a client, you will need the account's connection string. The following are relevant concepts for the usage of the client: The following sections provide several code snippets covering some of the most common Table tasks, including: Create a database and obtain a `DatabaseClient` to perform operations on your newly created database. Create a container on an existing database and obtain a `ContainerClient` to perform operations on your newly created container. Creating, reading, and deleting items Querying items Querying items with parametrized queries Using Transactional batch

Package captcha implements generation and verification of image and audio CAPTCHAs. A captcha solution is the sequence of digits 0-9 with the defined length. There are two captcha representations: image and audio. An image representation is a PNG-encoded image with the solution printed on it in such a way that makes it hard for computers to solve it using OCR. An audio representation is a WAVE-encoded (8 kHz unsigned 8-bit) sound with the spoken solution (currently in English, Russian, Chinese, and Japanese). To make it hard for computers to solve audio captcha, the voice that pronounces numbers has random speed and pitch, and there is a randomly generated background noise mixed into the sound. This package doesn't require external files or libraries to generate captcha representations; it is self-contained. To make captchas one-time, the package includes a memory storage that stores captcha ids, their solutions, and expiration time. Used captchas are removed from the store immediately after calling Verify or VerifyString, while unused captchas (user loaded a page with captcha, but didn't submit the form) are collected automatically after the predefined expiration time. Developers can also provide custom store (for example, which saves captcha ids and solutions in database) by implementing Store interface and registering the object with SetCustomStore. Captchas are created by calling New, which returns the captcha id. Their representations, though, are created on-the-fly by calling WriteImage or WriteAudio functions. Created representations are not stored anywhere, but subsequent calls to these functions with the same id will write the same captcha solution. Reload function will create a new different solution for the provided captcha, allowing users to "reload" captcha if they can't solve the displayed one without reloading the whole page. Verify and VerifyString are used to verify that the given solution is the right one for the given captcha id. Server provides an http.Handler which can serve image and audio representations of captchas automatically from the URL. It can also be used to reload captchas. Refer to Server function documentation for details, or take a look at the example in "capexample" subdirectory.

Package csrf (gorilla/csrf) provides Cross Site Request Forgery (CSRF) prevention middleware for Go web applications & services. It includes: * The `csrf.Protect` middleware/handler provides CSRF protection on routes attached to a router or a sub-router. * A `csrf.Token` function that provides the token to pass into your response, whether that be a HTML form or a JSON response body. * ... and a `csrf.TemplateField` helper that you can pass into your `html/template` templates to replace a `{{ .csrfField }}` template tag with a hidden input field. gorilla/csrf is easy to use: add the middleware to individual handlers with the below: ... and then collect the token with `csrf.Token(r)` before passing it to the template, JSON body or HTTP header (you pick!). gorilla/csrf inspects the form body (first) and HTTP headers (second) on subsequent POST/PUT/PATCH/DELETE/etc. requests for the token. Note that the authentication key passed to `csrf.Protect([]byte(key))` should be 32-bytes long and persist across application restarts. Generating a random key won't allow you to authenticate existing cookies and will break your CSRF validation. Here's the common use-case: HTML forms you want to provide CSRF protection for, in order to protect malicious POST requests being made: Note that the CSRF middleware will (by necessity) consume the request body if the token is passed via POST form values. If you need to consume this in your handler, insert your own middleware earlier in the chain to capture the request body. You can also send the CSRF token in the response header. This approach is useful if you're using a front-end JavaScript framework like Ember or Angular, or are providing a JSON API: If you're writing a client that's supposed to mimic browser behavior, make sure to send back the CSRF cookie (the default name is _gorilla_csrf, but this can be changed with the CookieName Option) along with either the X-CSRF-Token header or the gorilla.csrf.Token form field. In addition: getting CSRF protection right is important, so here's some background: * This library generates unique-per-request (masked) tokens as a mitigation against the BREACH attack (http://breachattack.com/). * The 'base' (unmasked) token is stored in the session, which means that multiple browser tabs won't cause a user problems as their per-request token is compared with the base token. * Operates on a "whitelist only" approach where safe (non-mutating) HTTP methods (GET, HEAD, OPTIONS, TRACE) are the *only* methods where token validation is not enforced. * The design is based on the battle-tested Django (https://docs.djangoproject.com/en/1.8/ref/csrf/) and Ruby on Rails (http://api.rubyonrails.org/classes/ActionController/RequestForgeryProtection.html) approaches. * Cookies are authenticated and based on the securecookie (https://github.com/gorilla/securecookie) library. They're also Secure (issued over HTTPS only) and are HttpOnly by default, because sane defaults are important. * Go's `crypto/rand` library is used to generate the 32 byte (256 bit) tokens and the one-time-pad used for masking them. This library does not seek to be adventurous.

Package logr defines a general-purpose logging API and abstract interfaces to back that API. Packages in the Go ecosystem can depend on this package, while callers can implement logging with whatever backend is appropriate. Logging is done using a Logger instance. Logger is a concrete type with methods, which defers the actual logging to a LogSink interface. The main methods of Logger are Info() and Error(). Arguments to Info() and Error() are key/value pairs rather than printf-style formatted strings, emphasizing "structured logging". With Go's standard log package, we might write: With logr's structured logging, we'd write: Errors are much the same. Instead of: We'd write: Info() and Error() are very similar, but they are separate methods so that LogSink implementations can choose to do things like attach additional information (such as stack traces) on calls to Error(). Error() messages are always logged, regardless of the current verbosity. If there is no error instance available, passing nil is valid. Often we want to log information only when the application in "verbose mode". To write log lines that are more verbose, Logger has a V() method. The higher the V-level of a log line, the less critical it is considered. Log-lines with V-levels that are not enabled (as per the LogSink) will not be written. Level V(0) is the default, and logger.V(0).Info() has the same meaning as logger.Info(). Negative V-levels have the same meaning as V(0). Error messages do not have a verbosity level and are always logged. Where we might have written: We can write: Logger instances can have name strings so that all messages logged through that instance have additional context. For example, you might want to add a subsystem name: The WithName() method returns a new Logger, which can be passed to constructors or other functions for further use. Repeated use of WithName() will accumulate name "segments". These name segments will be joined in some way by the LogSink implementation. It is strongly recommended that name segments contain simple identifiers (letters, digits, and hyphen), and do not contain characters that could muddle the log output or confuse the joining operation (e.g. whitespace, commas, periods, slashes, brackets, quotes, etc). Logger instances can store any number of key/value pairs, which will be logged alongside all messages logged through that instance. For example, you might want to create a Logger instance per managed object: With the standard log package, we might write: With logr we'd write: Logger has very few hard rules, with the goal that LogSink implementations might have a lot of freedom to differentiate. There are, however, some things to consider. The log message consists of a constant message attached to the log line. This should generally be a simple description of what's occurring, and should never be a format string. Variable information can then be attached using named values. Keys are arbitrary strings, but should generally be constant values. Values may be any Go value, but how the value is formatted is determined by the LogSink implementation. Logger instances are meant to be passed around by value. Code that receives such a value can call its methods without having to check whether the instance is ready for use. The zero logger (= Logger{}) is identical to Discard() and discards all log entries. Code that receives a Logger by value can simply call it, the methods will never crash. For cases where passing a logger is optional, a pointer to Logger should be used. Keys are not strictly required to conform to any specification or regex, but it is recommended that they: These guidelines help ensure that log data is processed properly regardless of the log implementation. For example, log implementations will try to output JSON data or will store data for later database (e.g. SQL) queries. While users are generally free to use key names of their choice, it's generally best to avoid using the following keys, as they're frequently used by implementations: Implementations are encouraged to make use of these keys to represent the above concepts, when necessary (for example, in a pure-JSON output form, it would be necessary to represent at least message and timestamp as ordinary named values). Implementations may choose to give callers access to the underlying logging implementation. The recommended pattern for this is: Logger grants access to the sink to enable type assertions like this: Custom `With*` functions can be implemented by copying the complete Logger struct and replacing the sink in the copy: Don't use New to construct a new Logger with a LogSink retrieved from an existing Logger. Source code attribution might not work correctly and unexported fields in Logger get lost. Beware that the same LogSink instance may be shared by different logger instances. Calling functions that modify the LogSink will affect all of those.

Package arg parses command line arguments using the fields from a struct. For example, defines two command line arguments, which can be set using any of The fastest way to see how to use go-arg is to read the examples below. Fields can be bool, string, any float type, or any signed or unsigned integer type. They can also be slices of any of the above, or slices of pointers to any of the above. Tags can be specified using the `arg` and `help` tag names: Any tag string that starts with a single hyphen is the short form for an argument (e.g. `./example -d`), and any tag string that starts with two hyphens is the long form for the argument (instead of the field name). Other valid tag strings are `positional` and `required`. Fields can be excluded from processing with `arg:"-"`. This example demonstrates basic usage This example demonstrates arguments that have default values This example shows the error string generated by go-arg when an invalid option is provided This example shows the error string generated by go-arg when an invalid option is provided This example shows the usage string generated by go-arg with customized placeholders This example shows the usage string generated by go-arg This example shows the usage string generated by go-arg when using subcommands This example shows the usage string generated by go-arg when using subcommands This example demonstrates arguments with keys and values separated by commas This example demonstrates arguments with keys and values This eample demonstrates multiple value arguments that can be mixed with other arguments. This example demonstrates arguments that have multiple values This example demonstrates positional arguments This example demonstrates arguments that are required This example demonstrates use of subcommands This example shows how to print help for an explicit subcommand This example shows how to print help for a subcommand that is nested several levels deep

Package inject provides a reflect based injector. A large application built with dependency injection in mind will typically involve the boring work of setting up the object graph. This library attempts to take care of this boring work by creating and connecting the various objects. Its use involves you seeding the object graph with some (possibly incomplete) objects, where the underlying types have been tagged for injection. Given this, the library will populate the objects creating new ones as necessary. It uses singletons by default, supports optional private instances as well as named instances. It works using Go's reflection package and is inherently limited in what it can do as opposed to a code-gen system with respect to private fields. The usage pattern for the library involves struct tags. It requires the tag format used by the various standard libraries, like json, xml etc. It involves tags in one of the three forms below: The first no value syntax is for the common case of a singleton dependency of the associated type. The second triggers creation of a private instance for the associated type. Finally the last form is asking for a named dependency called "dev logger".

Package appconfig provides the API client, operations, and parameter types for Amazon AppConfig. AppConfig feature flags and dynamic configurations help software builders quickly and securely adjust application behavior in production environments without full code deployments. AppConfig speeds up software release frequency, improves application resiliency, and helps you address emergent issues more quickly. With feature flags, you can gradually release new capabilities to users and measure the impact of those changes before fully deploying the new capabilities to all users. With operational flags and dynamic configurations, you can update block lists, allow lists, throttling limits, logging verbosity, and perform other operational tuning to quickly respond to issues in production environments. AppConfig is a capability of Amazon Web Services Systems Manager. Despite the fact that application configuration content can vary greatly from application to application, AppConfig supports the following use cases, which cover a broad spectrum of customer needs: Feature flags and toggles - Safely release new capabilities to your customers in a controlled environment. Instantly roll back changes if you experience a problem. Application tuning - Carefully introduce application changes while testing the impact of those changes with users in production environments. Allow list or block list - Control access to premium features or instantly block specific users without deploying new code. Centralized configuration storage - Keep your configuration data organized and consistent across all of your workloads. You can use AppConfig to deploy configuration data stored in the AppConfig hosted configuration store, Secrets Manager, Systems Manager, Parameter Store, or Amazon S3. This section provides a high-level description of how AppConfig works and how you get started. 1. Identify configuration values in code you want to manage in the cloud Before you start creating AppConfig artifacts, we recommend you identify configuration data in your code that you want to dynamically manage using AppConfig. Good examples include feature flags or toggles, allow and block lists, logging verbosity, service limits, and throttling rules, to name a few. If your configuration data already exists in the cloud, you can take advantage of AppConfig validation, deployment, and extension features to further streamline configuration data management. 2. Create an application namespace To create a namespace, you create an AppConfig artifact called an application. An application is simply an organizational construct like a folder. 3. Create environments For each AppConfig application, you define one or more environments. An environment is a logical grouping of targets, such as applications in a Beta or Production environment, Lambda functions, or containers. You can also define environments for application subcomponents, such as the Web , Mobile , and Back-end . You can configure Amazon CloudWatch alarms for each environment. The system monitors alarms during a configuration deployment. If an alarm is triggered, the system rolls back the configuration. 4. Create a configuration profile A configuration profile includes, among other things, a URI that enables AppConfig to locate your configuration data in its stored location and a profile type. AppConfig supports two configuration profile types: feature flags and freeform configurations. Feature flag configuration profiles store their data in the AppConfig hosted configuration store and the URI is simply hosted . For freeform configuration profiles, you can store your data in the AppConfig hosted configuration store or any Amazon Web Services service that integrates with AppConfig, as described in Creating a free form configuration profilein the the AppConfig User Guide. A configuration profile can also include optional validators to ensure your configuration data is syntactically and semantically correct. AppConfig performs a check using the validators when you start a deployment. If any errors are detected, the deployment rolls back to the previous configuration data. 5. Deploy configuration data When you create a new deployment, you specify the following: An application ID A configuration profile ID A configuration version An environment ID where you want to deploy the configuration data A deployment strategy ID that defines how fast you want the changes to take effect When you call the StartDeployment API action, AppConfig performs the following tasks: Retrieves the configuration data from the underlying data store by using the location URI in the configuration profile. Verifies the configuration data is syntactically and semantically correct by using the validators you specified when you created your configuration profile. Caches a copy of the data so it is ready to be retrieved by your application. This cached copy is called the deployed data. 6. Retrieve the configuration You can configure AppConfig Agent as a local host and have the agent poll AppConfig for configuration updates. The agent calls the StartConfigurationSessionand GetLatestConfiguration API actions and caches your configuration data locally. To retrieve the data, your application makes an HTTP call to the localhost server. AppConfig Agent supports several use cases, as described in Simplified retrieval methodsin the the AppConfig User Guide. If AppConfig Agent isn't supported for your use case, you can configure your application to poll AppConfig for configuration updates by directly calling the StartConfigurationSession and GetLatestConfigurationAPI actions. This reference is intended to be used with the AppConfig User Guide.

Package httpexpect helps with end-to-end HTTP and REST API testing. See example directory: There are two common ways to test API with httpexpect: The second approach works only if the server is a Go module and its handler can be imported in tests. Concrete behaviour is determined by Client implementation passed to Config struct. If you're using http.Client, set its Transport field (http.RoundTriper) to one of the following: Note that http handler can be usually obtained from http framework you're using. E.g., echo framework provides either http.Handler or fasthttp.RequestHandler. You can also provide your own implementation of RequestFactory (creates http.Request), or Client (gets http.Request and returns http.Response). If you're starting server from tests, it's very handy to use net/http/httptest. Whenever values are checked for equality in httpexpect, they are converted to "canonical form": This is equivalent to subsequently json.Marshal() and json.Unmarshal() the value and currently is implemented so. When some check fails, failure is reported. If non-fatal failures are used (see Reporter interface), execution is continued and instance that was checked is marked as failed. If specific instance is marked as failed, all subsequent checks are ignored for this instance and for any child instances retrieved after failure. Example: If you want to be informed about every asserion made, successful or failed, you can use AssertionHandler interface. Default implementation of this interface ignores successful assertions and reports failed assertions using Formatter and Reporter objects. Custom AssertionHandler can handle all assertions (e.g. dump them in JSON format) and is free to use or not to use Formatter and Reporter in its sole discretion.