Server

Package cloud is the root of the packages used to access Google Cloud Services. See https://pkg.go.dev/cloud.google.com/go#section-directories for a full list of sub-modules. All clients in sub-packages are configurable via client options. These options are described here: https://pkg.go.dev/google.golang.org/api/option. Endpoint configuration is used to specify the URL to which requests are sent. It is used for services that support or require regional endpoints, as well as for other use cases such as testing against fake servers. For example, the Vertex AI service recommends that you configure the endpoint to the location with the features you want that is closest to your physical location or the location of your users. There is no global endpoint for Vertex AI. See Vertex AI - Locations for more details. The following example demonstrates configuring a Vertex AI client with a regional endpoint: All of the clients support authentication via Google Application Default Credentials, or by providing a JSON key file for a Service Account. See examples below. Google Application Default Credentials (ADC) is the recommended way to authorize and authenticate clients. For information on how to create and obtain Application Default Credentials, see https://cloud.google.com/docs/authentication/production. If you have your environment configured correctly you will not need to pass any extra information to the client libraries. Here is an example of a client using ADC to authenticate: You can use a file with credentials to authenticate and authorize, such as a JSON key file associated with a Google service account. Service Account keys can be created and downloaded from https://console.cloud.google.com/iam-admin/serviceaccounts. This example uses the Secret Manger client, but the same steps apply to the all other client libraries this package as well. Example: In some cases (for instance, you don't want to store secrets on disk), you can create credentials from in-memory JSON and use the WithCredentials option. This example uses the Secret Manager client, but the same steps apply to all other client libraries as well. Note that scopes can be found at https://developers.google.com/identity/protocols/oauth2/scopes, and are also provided in all auto-generated libraries: for example, cloud.google.com/go/secretmanager/apiv1 provides DefaultAuthScopes. Example: By default, non-streaming methods, like Create or Get, will have a default deadline applied to the context provided at call time, unless a context deadline is already set. Streaming methods have no default deadline and will run indefinitely. To set timeouts or arrange for cancellation, use context. Transient errors will be retried when correctness allows. Here is an example of setting a timeout for an RPC using context.WithTimeout: Here is an example of setting a timeout for an RPC using github.com/googleapis/gax-go/v2.WithTimeout: Here is an example of how to arrange for an RPC to be canceled, use context.WithCancel: Do not attempt to control the initial connection (dialing) of a service by setting a timeout on the context passed to NewClient. Dialing is non-blocking, so timeouts would be ineffective and would only interfere with credential refreshing, which uses the same context. Regardless of which transport is used, request headers can be set in the same way using [`callctx.SetHeaders`]setheaders. Here is a generic example: There are a some header keys that Google reserves for internal use that must not be ovewritten. The following header keys are broadly considered reserved and should not be conveyed by client library users unless instructed to do so: * `x-goog-api-client` * `x-goog-request-params` Be sure to check the individual package documentation for other service-specific reserved headers. For example, Storage supports a specific auditing header that is mentioned in that [module's documentation]storagedocs. Google Cloud services respect system parameterssystem parameters that can be used to augment request and/or response behavior. For the most part, they are not needed when using one of the enclosed client libraries. However, those that may be necessary are made available via the [`callctx`]callctx package. If not present there, consider opening an issue on that repo to request a new constant. Connection pooling differs in clients based on their transport. Cloud clients either rely on HTTP or gRPC transports to communicate with Google Cloud. Cloud clients that use HTTP rely on the underlying HTTP transport to cache connections for later re-use. These are cached to the http.MaxIdleConns and http.MaxIdleConnsPerHost settings in http.DefaultTransport by default. For gRPC clients, connection pooling is configurable. Users of Cloud Client Libraries may specify google.golang.org/api/option.WithGRPCConnectionPool as a client option to NewClient calls. This configures the underlying gRPC connections to be pooled and accessed in a round robin fashion. Minimal container images like Alpine lack CA certificates. This causes RPCs to appear to hang, because gRPC retries indefinitely. See https://github.com/googleapis/google-cloud-go/issues/928 for more information. For tips on how to write tests against code that calls into our libraries check out our Debugging Guide. For tips on how to write tests against code that calls into our libraries check out our Testing Guide. Most of the errors returned by the generated clients are wrapped in an github.com/googleapis/gax-go/v2/apierror.APIError and can be further unwrapped into a google.golang.org/grpc/status.Status or google.golang.org/api/googleapi.Error depending on the transport used to make the call (gRPC or REST). Converting your errors to these types can be a useful way to get more information about what went wrong while debugging. APIError gives access to specific details in the error. The transport-specific errors can still be unwrapped using the APIError. Semver is used to communicate stability of the sub-modules of this package. Note, some stable sub-modules do contain packages, and sometimes features, that are considered unstable. If something is unstable it will be explicitly labeled as such. Example of package does in an unstable package: Clients that contain alpha and beta in their import path may change or go away without notice. Clients marked stable will maintain compatibility with future versions for as long as we can reasonably sustain. Incompatible changes might be made in some situations, including:

Package api is the root of the packages used to access Google Cloud Services. See https://godoc.org/google.golang.org/api for a full list of sub-packages. Within api there exist numerous clients which connect to Google APIs, and various utility packages. All clients in sub-packages are configurable via client options. These options are described here: https://godoc.org/google.golang.org/api/option. All the clients in sub-packages support authentication via Google Application Default Credentials (see https://cloud.google.com/docs/authentication/production), or by providing a JSON key file for a Service Account. See the authentication examples in https://godoc.org/google.golang.org/api/transport for more details. Due to the auto-generated nature of this collection of libraries, complete APIs or specific versions can appear or go away without notice. As a result, you should always locally vendor any API(s) that your code relies upon. Google APIs follow semver as specified by https://cloud.google.com/apis/design/versioning. The code generator and the code it produces - the libraries in the google.golang.org/api/... subpackages - are beta. Note that versioning and stability is strictly not communicated through Go modules. Go modules are used only for dependency management. Many parameters are specified using ints. However, underlying APIs might operate on a finer granularity, expecting int64, int32, uint64, or uint32, all of whom have different maximum values. Subsequently, specifying an int parameter in one of these clients may result in an error from the API because the value is too large. To see the exact type of int that the API expects, you can inspect the API's discovery doc. A global catalogue pointing to the discovery doc of APIs can be found at https://www.googleapis.com/discovery/v1/apis. This field can be found on all Request/Response structs in the generated clients. All of these types have the JSON `omitempty` field tag present on their fields. This means if a type is set to its default value it will not be marshalled. Sometimes you may actually want to send a default value, for instance sending an int of `0`. In this case you can override the `omitempty` feature by adding the field name to the `ForceSendFields` slice. See docs on any struct for more details. This may be used to include empty fields in Patch requests. This field can be found on all Request/Response structs in the generated clients. It can be be used to send JSON null values for the listed fields. By default, fields with empty values are omitted from API requests because of the presence of the `omitempty` field tag on all fields. However, any field with an empty value appearing in NullFields will be sent to the server as null. It is an error if a field in this list has a non-empty value. This may be used to include null fields in Patch requests. An error returned by a client's Do method may be cast to a *googleapi.Error or unwrapped to an *apierror.APIError. The https://pkg.go.dev/google.golang.org/api/googleapi#Error type is useful for getting the HTTP status code: The https://pkg.go.dev/github.com/googleapis/gax-go/v2/apierror#APIError type is useful for inspecting structured details of the underlying API response, such as the reason for the error and the error domain, which is typically the registered service name of the tool or product that generated the error: If an API call returns an Operation, that means it could take some time to complete the work initiated by the API call. Applications that are interested in the end result of the operation they initiated should wait until the Operation.Done field indicates it is finished. To do this, use the service's Operation client, and a loop, like so:

Package elastic provides an interface to the Elasticsearch server (https://www.elastic.co/products/elasticsearch). The first thing you do is to create a Client. If you have Elasticsearch installed and running with its default settings (i.e. available at http://127.0.0.1:9200), all you need to do is: If your Elasticsearch server is running on a different IP and/or port, just provide a URL to NewClient: You can pass many more configuration parameters to NewClient. Review the documentation of NewClient for more information. If no Elasticsearch server is available, services will fail when creating a new request and will return ErrNoClient. A Client provides services. The services usually come with a variety of methods to prepare the query and a Do function to execute it against the Elasticsearch REST interface and return a response. Here is an example of the IndexExists service that checks if a given index already exists. Look up the documentation for Client to get an idea of the services provided and what kinds of responses you get when executing the Do function of a service. Also see the wiki on Github for more details. Copyright 2012-present Oliver Eilhard. All rights reserved. Use of this source code is governed by a MIT-license. See http://olivere.mit-license.org/license.txt for details.

Package elastic provides an interface to the Elasticsearch server (https://www.elastic.co/products/elasticsearch). The first thing you do is to create a Client. If you have Elasticsearch installed and running with its default settings (i.e. available at http://127.0.0.1:9200), all you need to do is: If your Elasticsearch server is running on a different IP and/or port, just provide a URL to NewClient: You can pass many more configuration parameters to NewClient. Review the documentation of NewClient for more information. If no Elasticsearch server is available, services will fail when creating a new request and will return ErrNoClient. A Client provides services. The services usually come with a variety of methods to prepare the query and a Do function to execute it against the Elasticsearch REST interface and return a response. Here is an example of the IndexExists service that checks if a given index already exists. Look up the documentation for Client to get an idea of the services provided and what kinds of responses you get when executing the Do function of a service. Also see the wiki on Github for more details. Copyright 2012-present Oliver Eilhard. All rights reserved. Use of this source code is governed by a MIT-license. See http://olivere.mit-license.org/license.txt for details.

Package elastic provides an interface to the Elasticsearch server (https://www.elastic.co/products/elasticsearch). The first thing you do is to create a Client. If you have Elasticsearch installed and running with its default settings (i.e. available at http://127.0.0.1:9200), all you need to do is: If your Elasticsearch server is running on a different IP and/or port, just provide a URL to NewClient: You can pass many more configuration parameters to NewClient. Review the documentation of NewClient for more information. If no Elasticsearch server is available, services will fail when creating a new request and will return ErrNoClient. A Client provides services. The services usually come with a variety of methods to prepare the query and a Do function to execute it against the Elasticsearch REST interface and return a response. Here is an example of the IndexExists service that checks if a given index already exists. Look up the documentation for Client to get an idea of the services provided and what kinds of responses you get when executing the Do function of a service. Also see the wiki on Github for more details.

GoSNMPServer is an SNMP server library fully written in Go. It **WILL** provides Server Get, GetNext, GetBulk, Walk, BulkWalk, Set and Traps. It supports IPv4 and IPv6, using __SNMPv2c__ or __SNMPv3__. Builds are tested against linux/amd64 and linux/386. Build your own SNMP Server, try this: Some Code Here: This library provides some common oid for use. See godoc for details. See https://github.com/slayercat/GoSNMPServer/tree/master/mibImps for code. Append `GoSNMPServer.PDUValueControlItem` to your SubAgent OIDS:

Package pubsub provides an easy way to publish and receive Google Cloud Pub/Sub messages, hiding the details of the underlying server RPCs. Pub/Sub is a many-to-many, asynchronous messaging system that decouples senders and receivers. More information about Pub/Sub is available at https://cloud.google.com/pubsub/docs See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. Pub/Sub messages are published to topics. A Topic may be created using Client.CreateTopic like so: Messages may then be published to a Topic: Topic.Publish queues the message for publishing and returns immediately. When enough messages have accumulated, or enough time has elapsed, the batch of messages is sent to the Pub/Sub service. Topic.Publish returns a PublishResult, which behaves like a future: its Get method blocks until the message has been sent to the service. The first time you call Topic.Publish on a Topic, goroutines are started in the background. To clean up these goroutines, call Topic.Stop: To receive messages published to a Topic, clients create a Subscription for the topic. There may be more than one subscription per topic ; each message that is published to the topic will be delivered to all associated subscriptions. A Subscription may be created like so: Messages are then consumed from a Subscription via callback. The callback is invoked concurrently by multiple goroutines, maximizing throughput. To terminate a call to Subscription.Receive, cancel its context. Once client code has processed the Message, it must call Message.Ack or Message.Nack; otherwise the Message will eventually be redelivered. Ack/Nack MUST be called within the Subscription.Receive handler function, and not from a goroutine. Otherwise, flow control (e.g. ReceiveSettings.MaxOutstandingMessages) will not be respected, and messages can get orphaned when cancelling Receive. If the client cannot or doesn't want to process the message, it can call Message.Nack to speed redelivery. For more information and configuration options, see Ack Deadlines below. Note: It is possible for a Message to be redelivered even if Message.Ack has been called. Client code must be robust to multiple deliveries of messages. Note: This uses pubsub's streaming pull feature. This feature has properties that may be surprising. Please take a look at https://cloud.google.com/pubsub/docs/pull#streamingpull for more details on how streaming pull behaves compared to the synchronous pull method. The number of StreamingPull connections can be configured by setting NumGoroutines in ReceiveSettings. The default value of 10 means the client library will maintain 10 StreamingPull connections. This is more than sufficient for most use cases, as StreamingPull connections can handle up to 10 MB/s https://cloud.google.com/pubsub/quotas#resource_limits. In some cases, using too many streams can lead to client library behaving poorly as the application becomes I/O bound. By default, the number of connections in the gRPC conn pool is min(4,GOMAXPROCS). Each connection supports up to 100 streams. Thus, if you have 4 or more CPU cores, the default setting allows a maximum of 400 streams which is already excessive for most use cases. If you want to change the limits on the number of streams, you can change the number of connections in the gRPC connection pool as shown below: The default pubsub deadlines are suitable for most use cases, but may be overridden. This section describes the tradeoffs that should be considered when overriding the defaults. Behind the scenes, each message returned by the Pub/Sub server has an associated lease, known as an "ack deadline". Unless a message is acknowledged within the ack deadline, or the client requests that the ack deadline be extended, the message will become eligible for redelivery. As a convenience, the pubsub client will automatically extend deadlines until either: Ack deadlines are extended periodically by the client. The period between extensions, as well as the length of the extension, automatically adjusts based on the time it takes the subscriber application to ack messages (based on the 99th percentile of ack latency). By default, this extension period is capped at 10m, but this limit can be configured by the "MaxExtensionPeriod" setting. This has the effect that subscribers that process messages quickly have their message ack deadlines extended for a short amount, whereas subscribers that process message slowly have their message ack deadlines extended for a large amount. The net effect is fewer RPCs sent from the client library. For example, consider a subscriber that takes 3 minutes to process each message. Since the library has already recorded several 3-minute "ack latencies"s in a percentile distribution, future message extensions are sent with a value of 3 minutes, every 3 minutes. Suppose the application crashes 5 seconds after the library sends such an extension: the Pub/Sub server would wait the remaining 2m55s before re-sending the messages out to other subscribers. Please note that by default, the client library does not use the subscription's AckDeadline for the MaxExtension value. For use cases where message processing exceeds 30 minutes, we recommend using the base client in a pull model, since long-lived streams are periodically killed by firewalls. See the example at https://godoc.org/cloud.google.com/go/pubsub/apiv1#example-SubscriberClient-Pull-LengthyClientProcessing To use an emulator with this library, you can set the PUBSUB_EMULATOR_HOST environment variable to the address at which your emulator is running. This will send requests to that address instead of to Pub/Sub. You can then create and use a client as usual:

`grpc_middleware` is a collection of gRPC middleware packages: interceptors, helpers and tools. gRPC is a fantastic RPC middleware, which sees a lot of adoption in the Golang world. However, the upstream gRPC codebase is relatively bare bones. This package, and most of its child packages provides commonly needed middleware for gRPC: client-side interceptors for retires, server-side interceptors for input validation and auth, functions for chaining said interceptors, metadata convenience methods and more. By default, gRPC doesn't allow one to have more than one interceptor either on the client nor on the server side. `grpc_middleware` provides convenient chaining methods Simple way of turning a multiple interceptors into a single interceptor. Here's an example for server chaining: These interceptors will be executed from left to right: logging, monitoring and auth. Here's an example for client side chaining: These interceptors will be executed from left to right: monitoring and then retry logic. The retry interceptor will call every interceptor that follows it whenever when a retry happens. Implementing your own interceptor is pretty trivial: there are interfaces for that. But the interesting bit exposing common data to handlers (and other middleware), similarly to HTTP Middleware design. For example, you may want to pass the identity of the caller from the auth interceptor all the way to the handling function. For example, a client side interceptor example for auth looks like: Unfortunately, it's not as easy for streaming RPCs. These have the `context.Context` embedded within the `grpc.ServerStream` object. To pass values through context, a wrapper (`WrappedServerStream`) is needed. For example:

Package otlptracegrpc provides an OTLP span exporter using gRPC. By default the telemetry is sent to https://localhost:4317. Exporter should be created using New. The environment variables described below can be used for configuration. OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_TRACES_ENDPOINT (default: "https://localhost:4317") - target to which the exporter sends telemetry. The target syntax is defined in https://github.com/grpc/grpc/blob/master/doc/naming.md. The value must contain a scheme ("http" or "https") and host. The value may additionally contain a port, and a path. The value should not contain a query string or fragment. OTEL_EXPORTER_OTLP_TRACES_ENDPOINT takes precedence over OTEL_EXPORTER_OTLP_ENDPOINT. The configuration can be overridden by WithEndpoint, WithEndpointURL, WithInsecure, and WithGRPCConn options. OTEL_EXPORTER_OTLP_INSECURE, OTEL_EXPORTER_OTLP_TRACES_INSECURE (default: "false") - setting "true" disables client transport security for the exporter's gRPC connection. You can use this only when an endpoint is provided without the http or https scheme. OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_TRACES_ENDPOINT setting overrides the scheme defined via OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_TRACES_ENDPOINT. OTEL_EXPORTER_OTLP_TRACES_INSECURE takes precedence over OTEL_EXPORTER_OTLP_INSECURE. The configuration can be overridden by WithInsecure, WithGRPCConn options. OTEL_EXPORTER_OTLP_HEADERS, OTEL_EXPORTER_OTLP_TRACES_HEADERS (default: none) - key-value pairs used as gRPC metadata associated with gRPC requests. The value is expected to be represented in a format matching the W3C Baggage HTTP Header Content Format, except that additional semi-colon delimited metadata is not supported. Example value: "key1=value1,key2=value2". OTEL_EXPORTER_OTLP_TRACES_HEADERS takes precedence over OTEL_EXPORTER_OTLP_HEADERS. The configuration can be overridden by WithHeaders option. OTEL_EXPORTER_OTLP_TIMEOUT, OTEL_EXPORTER_OTLP_TRACES_TIMEOUT (default: "10000") - maximum time in milliseconds the OTLP exporter waits for each batch export. OTEL_EXPORTER_OTLP_TRACES_TIMEOUT takes precedence over OTEL_EXPORTER_OTLP_TIMEOUT. The configuration can be overridden by WithTimeout option. OTEL_EXPORTER_OTLP_COMPRESSION, OTEL_EXPORTER_OTLP_TRACES_COMPRESSION (default: none) - the gRPC compressor the exporter uses. Supported value: "gzip". OTEL_EXPORTER_OTLP_TRACES_COMPRESSION takes precedence over OTEL_EXPORTER_OTLP_COMPRESSION. The configuration can be overridden by WithCompressor, WithGRPCConn options. OTEL_EXPORTER_OTLP_CERTIFICATE, OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE (default: none) - the filepath to the trusted certificate to use when verifying a server's TLS credentials. OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CERTIFICATE. The configuration can be overridden by WithTLSCredentials, WithGRPCConn options. OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE, OTEL_EXPORTER_OTLP_TRACES_CLIENT_CERTIFICATE (default: none) - the filepath to the client certificate/chain trust for client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_TRACES_CLIENT_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE. The configuration can be overridden by WithTLSCredentials, WithGRPCConn options. OTEL_EXPORTER_OTLP_CLIENT_KEY, OTEL_EXPORTER_OTLP_TRACES_CLIENT_KEY (default: none) - the filepath to the client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_TRACES_CLIENT_KEY takes precedence over OTEL_EXPORTER_OTLP_CLIENT_KEY. The configuration can be overridden by WithTLSCredentials, WithGRPCConn option.

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

Package ants implements an efficient and reliable goroutine pool for Go. With ants, Go applications are able to limit the number of active goroutines, recycle goroutines efficiently, and reduce the memory footprint significantly. Package ants is extremely useful in the scenarios where a massive number of goroutines are created and destroyed frequently, such as highly-concurrent batch processing systems, HTTP servers, services of asynchronous tasks, etc.

Package restful , a lean package for creating REST-style WebServices without magic. A WebService has a collection of Route objects that dispatch incoming Http Requests to a function calls. Typically, a WebService has a root path (e.g. /users) and defines common MIME types for its routes. WebServices must be added to a container (see below) in order to handler Http requests from a server. A Route is defined by a HTTP method, an URL path and (optionally) the MIME types it consumes (Content-Type) and produces (Accept). This package has the logic to find the best matching Route and if found, call its Function. The (*Request, *Response) arguments provide functions for reading information from the request and writing information back to the response. See the example https://github.com/emicklei/go-restful/blob/v3/examples/user-resource/restful-user-resource.go with a full implementation. A Route parameter can be specified using the format "uri/{var[:regexp]}" or the special version "uri/{var:*}" for matching the tail of the path. For example, /persons/{name:[A-Z][A-Z]} can be used to restrict values for the parameter "name" to only contain capital alphabetic characters. Regular expressions must use the standard Go syntax as described in the regexp package. (https://code.google.com/p/re2/wiki/Syntax) This feature requires the use of a CurlyRouter. A Container holds a collection of WebServices, Filters and a http.ServeMux for multiplexing http requests. Using the statements "restful.Add(...) and restful.Filter(...)" will register WebServices and Filters to the Default Container. The Default container of go-restful uses the http.DefaultServeMux. You can create your own Container and create a new http.Server for that particular container. A filter dynamically intercepts requests and responses to transform or use the information contained in the requests or responses. You can use filters to perform generic logging, measurement, authentication, redirect, set response headers etc. In the restful package there are three hooks into the request,response flow where filters can be added. Each filter must define a FilterFunction: Use the following statement to pass the request,response pair to the next filter or RouteFunction These are processed before any registered WebService. These are processed before any Route of a WebService. These are processed before calling the function associated with the Route. See the example https://github.com/emicklei/go-restful/blob/v3/examples/filters/restful-filters.go with full implementations. Two encodings are supported: gzip and deflate. To enable this for all responses: If a Http request includes the Accept-Encoding header then the response content will be compressed using the specified encoding. Alternatively, you can create a Filter that performs the encoding and install it per WebService or Route. See the example https://github.com/emicklei/go-restful/blob/v3/examples/encoding/restful-encoding-filter.go By installing a pre-defined container filter, your Webservice(s) can respond to the OPTIONS Http request. By installing the filter of a CrossOriginResourceSharing (CORS), your WebService(s) can handle CORS requests. Unexpected things happen. If a request cannot be processed because of a failure, your service needs to tell via the response what happened and why. For this reason HTTP status codes exist and it is important to use the correct code in every exceptional situation. If path or query parameters are not valid (content or type) then use http.StatusBadRequest. Despite a valid URI, the resource requested may not be available If the application logic could not process the request (or write the response) then use http.StatusInternalServerError. The request has a valid URL but the method (GET,PUT,POST,...) is not allowed. The request does not have or has an unknown Accept Header set for this operation. The request does not have or has an unknown Content-Type Header set for this operation. In addition to setting the correct (error) Http status code, you can choose to write a ServiceError message on the response. This package has several options that affect the performance of your service. It is important to understand them and how you can change it. DoNotRecover controls whether panics will be caught to return HTTP 500. If set to false, the container will recover from panics. Default value is true If content encoding is enabled then the default strategy for getting new gzip/zlib writers and readers is to use a sync.Pool. Because writers are expensive structures, performance is even more improved when using a preloaded cache. You can also inject your own implementation. This package has the means to produce detail logging of the complete Http request matching process and filter invocation. Enabling this feature requires you to set an implementation of restful.StdLogger (e.g. log.Logger) instance such as: The restful.SetLogger() method allows you to override the logger used by the package. By default restful uses the standard library `log` package and logs to stdout. Different logging packages are supported as long as they conform to `StdLogger` interface defined in the `log` sub-package, writing an adapter for your preferred package is simple. (c) 2012-2015, http://ernestmicklei.com. MIT License

Package otlptracehttp provides an OTLP span exporter using HTTP with protobuf payloads. By default the telemetry is sent to https://localhost:4318/v1/traces. Exporter should be created using New. The environment variables described below can be used for configuration. OTEL_EXPORTER_OTLP_ENDPOINT (default: "https://localhost:4318") - target base URL ("/v1/traces" is appended) to which the exporter sends telemetry. The value must contain a scheme ("http" or "https") and host. The value may additionally contain a port and a path. The value should not contain a query string or fragment. The configuration can be overridden by OTEL_EXPORTER_OTLP_TRACES_ENDPOINT environment variable and by WithEndpoint, WithEndpointURL, WithInsecure options. OTEL_EXPORTER_OTLP_TRACES_ENDPOINT (default: "https://localhost:4318/v1/traces") - target URL to which the exporter sends telemetry. The value must contain a scheme ("http" or "https") and host. The value may additionally contain a port and a path. The value should not contain a query string or fragment. The configuration can be overridden by WithEndpoint, WithEndpointURL, WithInsecure, and WithURLPath options. OTEL_EXPORTER_OTLP_HEADERS, OTEL_EXPORTER_OTLP_TRACES_HEADERS (default: none) - key-value pairs used as headers associated with HTTP requests. The value is expected to be represented in a format matching the W3C Baggage HTTP Header Content Format, except that additional semi-colon delimited metadata is not supported. Example value: "key1=value1,key2=value2". OTEL_EXPORTER_OTLP_TRACES_HEADERS takes precedence over OTEL_EXPORTER_OTLP_HEADERS. The configuration can be overridden by WithHeaders option. OTEL_EXPORTER_OTLP_TIMEOUT, OTEL_EXPORTER_OTLP_TRACES_TIMEOUT (default: "10000") - maximum time in milliseconds the OTLP exporter waits for each batch export. OTEL_EXPORTER_OTLP_TRACES_TIMEOUT takes precedence over OTEL_EXPORTER_OTLP_TIMEOUT. The configuration can be overridden by WithTimeout option. OTEL_EXPORTER_OTLP_COMPRESSION, OTEL_EXPORTER_OTLP_TRACES_COMPRESSION (default: none) - the compression strategy the exporter uses to compress the HTTP body. Supported value: "gzip". OTEL_EXPORTER_OTLP_TRACES_COMPRESSION takes precedence over OTEL_EXPORTER_OTLP_COMPRESSION. The configuration can be overridden by WithCompression option. OTEL_EXPORTER_OTLP_CERTIFICATE, OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE (default: none) - the filepath to the trusted certificate to use when verifying a server's TLS credentials. OTEL_EXPORTER_OTLP_TRACES_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CERTIFICATE. The configuration can be overridden by WithTLSClientConfig option. OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE, OTEL_EXPORTER_OTLP_TRACES_CLIENT_CERTIFICATE (default: none) - the filepath to the client certificate/chain trust for client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_TRACES_CLIENT_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE. The configuration can be overridden by WithTLSClientConfig option. OTEL_EXPORTER_OTLP_CLIENT_KEY, OTEL_EXPORTER_OTLP_TRACES_CLIENT_KEY (default: none) - the filepath to the client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_TRACES_CLIENT_KEY takes precedence over OTEL_EXPORTER_OTLP_CLIENT_KEY. The configuration can be overridden by WithTLSClientConfig option.

Package pgx is a PostgreSQL database driver. pgx provides lower level access to PostgreSQL than the standard database/sql. It remains as similar to the database/sql interface as possible while providing better speed and access to PostgreSQL specific features. Import github.com/jackc/pgx/stdlib to use pgx as a database/sql compatible driver. pgx implements Query and Scan in the familiar database/sql style. pgx also implements QueryRow in the same style as database/sql. Use Exec to execute a query that does not return a result set. Connection pool usage is explicit and configurable. In pgx, a connection can be created and managed directly, or a connection pool with a configurable maximum connections can be used. The connection pool offers an after connect hook that allows every connection to be automatically setup before being made available in the connection pool. It delegates methods such as QueryRow to an automatically checked out and released connection so you can avoid manually acquiring and releasing connections when you do not need that level of control. pgx maps between all common base types directly between Go and PostgreSQL. In particular: pgx can map nulls in two ways. The first is package pgtype provides types that have a data field and a status field. They work in a similar fashion to database/sql. The second is to use a pointer to a pointer. pgx maps between int16, int32, int64, float32, float64, and string Go slices and the equivalent PostgreSQL array type. Go slices of native types do not support nulls, so if a PostgreSQL array that contains a null is read into a native Go slice an error will occur. The pgtype package includes many more array types for PostgreSQL types that do not directly map to native Go types. pgx includes built-in support to marshal and unmarshal between Go types and the PostgreSQL JSON and JSONB. pgx encodes from net.IPNet to and from inet and cidr PostgreSQL types. In addition, as a convenience pgx will encode from a net.IP; it will assume a /32 netmask for IPv4 and a /128 for IPv6. pgx includes support for the common data types like integers, floats, strings, dates, and times that have direct mappings between Go and SQL. In addition, pgx uses the github.com/jackc/pgx/pgtype library to support more types. See documention for that library for instructions on how to implement custom types. See example_custom_type_test.go for an example of a custom type for the PostgreSQL point type. pgx also includes support for custom types implementing the database/sql.Scanner and database/sql/driver.Valuer interfaces. If pgx does cannot natively encode a type and that type is a renamed type (e.g. type MyTime time.Time) pgx will attempt to encode the underlying type. While this is usually desired behavior it can produce suprising behavior if one the underlying type and the renamed type each implement database/sql interfaces and the other implements pgx interfaces. It is recommended that this situation be avoided by implementing pgx interfaces on the renamed type. []byte passed as arguments to Query, QueryRow, and Exec are passed unmodified to PostgreSQL. Transactions are started by calling Begin or BeginEx. The BeginEx variant can create a transaction with a specified isolation level. Use CopyFrom to efficiently insert multiple rows at a time using the PostgreSQL copy protocol. CopyFrom accepts a CopyFromSource interface. If the data is already in a [][]interface{} use CopyFromRows to wrap it in a CopyFromSource interface. Or implement CopyFromSource to avoid buffering the entire data set in memory. CopyFrom can be faster than an insert with as few as 5 rows. pgx can listen to the PostgreSQL notification system with the WaitForNotification function. It takes a maximum time to wait for a notification. The pgx ConnConfig struct has a TLSConfig field. If this field is nil, then TLS will be disabled. If it is present, then it will be used to configure the TLS connection. This allows total configuration of the TLS connection. pgx has never explicitly supported Postgres < 9.6's `ssl_renegotiation` option. As of v3.3.0, it doesn't send `ssl_renegotiation: 0` either to support Redshift (https://github.com/jackc/pgx/pull/476). If you need TLS Renegotiation, consider supplying `ConnConfig.TLSConfig` with a non-zero `Renegotiation` value and if it's not the default on your server, set `ssl_renegotiation` via `ConnConfig.RuntimeParams`. pgx defines a simple logger interface. Connections optionally accept a logger that satisfies this interface. Set LogLevel to control logging verbosity. Adapters for github.com/inconshreveable/log15, github.com/sirupsen/logrus, and the testing log are provided in the log directory.

This executable provides an HTTP server that watches for file system changes to .go files within the working directory (and all nested go packages). Navigating to the configured host and port in a web browser will display the latest results of running `go test` in each go package.

Package server contains every kpng's function related to serving its API. The general approach is that you want to provide a proxystore.Store and make something of it. This store contains what we call the globalv1 model, representing the cluster-wide information needed by kpng to provide what we call the local model, representing the node-level information. There are 3 ways to provide a proxystore.Store, all using jobs: From a proxystore.Store, you can: The main goal of kpng is to provide a local model. Currently, the local model is provided as a stream of changes. This stream is sent over the localsink.Sink interface. There are 2 ways to get the local model's stream:

Package datastore provides a client for Google Cloud Datastore. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. Entities are the unit of storage and are associated with a key. A key consists of an optional parent key, a string application ID, a string kind (also known as an entity type), and either a StringID or an IntID. A StringID is also known as an entity name or key name. It is valid to create a key with a zero StringID and a zero IntID; this is called an incomplete key, and does not refer to any saved entity. Putting an entity into the datastore under an incomplete key will cause a unique key to be generated for that entity, with a non-zero IntID. An entity's contents are a mapping from case-sensitive field names to values. Valid value types are: Slices of structs are valid, as are structs that contain slices. The Get and Put functions load and save an entity's contents. An entity's contents are typically represented by a struct pointer. Example code: GetMulti, PutMulti and DeleteMulti are batch versions of the Get, Put and Delete functions. They take a []*Key instead of a *Key, and may return a datastore.MultiError when encountering partial failure. Mutate generalizes PutMulti and DeleteMulti to a sequence of any Datastore mutations. It takes a series of mutations created with NewInsert, NewUpdate, NewUpsert and NewDelete and applies them. Datastore.Mutate uses non-transactional mode; if atomicity is required, use Transaction.Mutate instead. An entity's contents can be represented by a variety of types. These are typically struct pointers, but can also be any type that implements the PropertyLoadSaver interface. If using a struct pointer, you do not have to explicitly implement the PropertyLoadSaver interface; the datastore will automatically convert via reflection. If a struct pointer does implement PropertyLoadSaver then those methods will be used in preference to the default behavior for struct pointers. Struct pointers are more strongly typed and are easier to use; PropertyLoadSavers are more flexible. The actual types passed do not have to match between Get and Put calls or even across different calls to datastore. It is valid to put a *PropertyList and get that same entity as a *myStruct, or put a *myStruct0 and get a *myStruct1. Conceptually, any entity is saved as a sequence of properties, and is loaded into the destination value on a property-by-property basis. When loading into a struct pointer, an entity that cannot be completely represented (such as a missing field) will result in an ErrFieldMismatch error but it is up to the caller whether this error is fatal, recoverable or ignorable. By default, for struct pointers, all properties are potentially indexed, and the property name is the same as the field name (and hence must start with an upper case letter). Fields may have a `datastore:"name,options"` tag. The tag name is the property name, which must be one or more valid Go identifiers joined by ".", but may start with a lower case letter. An empty tag name means to just use the field name. A "-" tag name means that the datastore will ignore that field. The only valid options are "omitempty", "noindex" and "flatten". If the options include "omitempty" and the value of the field is an empty value, then the field will be omitted on Save. Empty values are defined as false, 0, a nil pointer, a nil interface value, the zero time.Time, and any empty slice or string. (Empty slices are never saved, even without "omitempty".) Other structs, including GeoPoint, are never considered empty. If options include "noindex" then the field will not be indexed. All fields are indexed by default. Strings or byte slices longer than 1500 bytes cannot be indexed; fields used to store long strings and byte slices must be tagged with "noindex" or they will cause Put operations to fail. For a nested struct field, the options may also include "flatten". This indicates that the immediate fields and any nested substruct fields of the nested struct should be flattened. See below for examples. To use multiple options together, separate them by a comma. The order does not matter. If the options is "" then the comma may be omitted. Example code: A field of slice type corresponds to a Datastore array property, except for []byte, which corresponds to a Datastore blob. Zero-length slice fields are not saved. Slice fields of length 1 or greater are saved as Datastore arrays. When a zero-length Datastore array is loaded into a slice field, the slice field remains unchanged. If a non-array value is loaded into a slice field, the result will be a slice with one element, containing the value. Loading a Datastore Null into a basic type (int, float, etc.) results in a zero value. Loading a Null into a slice of basic type results in a slice of size 1 containing the zero value. Loading a Null into a pointer field results in nil. Loading a Null into a field of struct type is an error. A struct field can be a pointer to a signed integer, floating-point number, string or bool. Putting a non-nil pointer will store its dereferenced value. Putting a nil pointer will store a Datastore Null property, unless the field is marked omitempty, in which case no property will be stored. Loading a Null into a pointer field sets the pointer to nil. Loading any other value allocates new storage with the value, and sets the field to point to it. If the struct contains a *datastore.Key field tagged with the name "__key__", its value will be ignored on Put. When reading the Entity back into the Go struct, the field will be populated with the *datastore.Key value used to query for the Entity. Example code: If the struct pointed to contains other structs, then the nested or embedded structs are themselves saved as Entity values. For example, given these definitions: then an Outer would have one property, Inner, encoded as an Entity value. Note: embedded struct fields must be named to be encoded as an Entity. For example, in case of a type Outer with an embedded field Inner: all the Inner struct fields will be treated as fields of Outer itself. If an outer struct is tagged "noindex" then all of its implicit flattened fields are effectively "noindex". If the Inner struct contains a *Key field with the name "__key__", like so: then the value of K will be used as the Key for Inner, represented as an Entity value in datastore. If any nested struct fields should be flattened, instead of encoded as Entity values, the nested struct field should be tagged with the "flatten" option. For example, given the following: an Outer's properties would be equivalent to those of: Note that the "flatten" option cannot be used for Entity value fields or PropertyLoadSaver implementers. The server will reject any dotted field names for an Entity value. An entity's contents can also be represented by any type that implements the PropertyLoadSaver interface. This type may be a struct pointer, but it does not have to be. The datastore package will call Load when getting the entity's contents, and Save when putting the entity's contents. Possible uses include deriving non-stored fields, verifying fields, or indexing a field only if its value is positive. Example code: The *PropertyList type implements PropertyLoadSaver, and can therefore hold an arbitrary entity's contents. If a type implements the PropertyLoadSaver interface, it may also want to implement the KeyLoader interface. The KeyLoader interface exists to allow implementations of PropertyLoadSaver to also load an Entity's Key into the Go type. This type may be a struct pointer, but it does not have to be. The datastore package will call LoadKey when getting the entity's contents, after calling Load. Example code: To load a Key into a struct which does not implement the PropertyLoadSaver interface, see the "Key Field" section above. Queries retrieve entities based on their properties or key's ancestry. Running a query yields an iterator of results: either keys or (key, entity) pairs. Queries are re-usable and it is safe to call Query.Run from concurrent goroutines. Iterators are not safe for concurrent use. Queries are immutable, and are either created by calling NewQuery, or derived from an existing query by calling a method like Filter or Order that returns a new query value. A query is typically constructed by calling NewQuery followed by a chain of zero or more such methods. These methods are: Example code: Client.RunInTransaction runs a function in a transaction. Example code: Pass the ReadOnly option to RunInTransaction if your transaction is used only for Get, GetMulti or queries. Read-only transactions are more efficient. This package supports the Cloud Datastore emulator, which is useful for testing and development. Environment variables are used to indicate that datastore traffic should be directed to the emulator instead of the production Datastore service. To install and set up the emulator and its environment variables, see the documentation at https://cloud.google.com/datastore/docs/tools/datastore-emulator. To use the emulator with this library, you can set the DATASTORE_EMULATOR_HOST environment variable to the address at which your emulator is running. This will send requests to that address instead of to Cloud Datastore. You can then create and use a client as usual:

Package swagger (2.0) provides a powerful interface to your API Contains an implementation of Swagger 2.0. It knows how to serialize, deserialize and validate swagger specifications. Swagger is a simple yet powerful representation of your RESTful API. With the largest ecosystem of API tooling on the planet, thousands of developers are supporting Swagger in almost every modern programming language and deployment environment. With a Swagger-enabled API, you get interactive documentation, client SDK generation and discoverability. We created Swagger to help fulfill the promise of APIs. Swagger helps companies like Apigee, Getty Images, Intuit, LivingSocial, McKesson, Microsoft, Morningstar, and PayPal build the best possible services with RESTful APIs.Now in version 2.0, Swagger is more enabling than ever. And it's 100% open source software. More detailed documentation is available at https://goswagger.io. Install: The implementation also provides a number of command line tools to help working with swagger. Currently there is a spec validator tool: To generate a server for a swagger spec document: To generate a client for a swagger spec document: To generate a swagger spec document for a go application: There are several other sub commands available for the generate command You're free to add files to the directories the generated code lands in, but the files generated by the generator itself will be regenerated on following generation runs so any changes to those files will be lost. However extra files you create won't be lost so they are safe to use for customizing the application to your needs. To generate a server for a swagger spec document:

Package controllerruntime provides tools to construct Kubernetes-style controllers that manipulate both Kubernetes CRDs and aggregated/built-in Kubernetes APIs. It defines easy helpers for the common use cases when building CRDs, built on top of customizable layers of abstraction. Common cases should be easy, and uncommon cases should be possible. In general, controller-runtime tries to guide users towards Kubernetes controller best-practices. The main entrypoint for controller-runtime is this root package, which contains all of the common types needed to get started building controllers: The examples in this package walk through a basic controller setup. The kubebuilder book (https://book.kubebuilder.io) has some more in-depth walkthroughs. controller-runtime favors structs with sane defaults over constructors, so it's fairly common to see structs being used directly in controller-runtime. A brief-ish walkthrough of the layout of this library can be found below. Each package contains more information about how to use it. Frequently asked questions about using controller-runtime and designing controllers can be found at https://github.com/kubernetes-sigs/controller-runtime/blob/main/FAQ.md. Every controller and webhook is ultimately run by a Manager (pkg/manager). A manager is responsible for running controllers and webhooks, and setting up common dependencies, like shared caches and clients, as well as managing leader election (pkg/leaderelection). Managers are generally configured to gracefully shut down controllers on pod termination by wiring up a signal handler (pkg/manager/signals). Controllers (pkg/controller) use events (pkg/event) to eventually trigger reconcile requests. They may be constructed manually, but are often constructed with a Builder (pkg/builder), which eases the wiring of event sources (pkg/source), like Kubernetes API object changes, to event handlers (pkg/handler), like "enqueue a reconcile request for the object owner". Predicates (pkg/predicate) can be used to filter which events actually trigger reconciles. There are pre-written utilities for the common cases, and interfaces and helpers for advanced cases. Controller logic is implemented in terms of Reconcilers (pkg/reconcile). A Reconciler implements a function which takes a reconcile Request containing the name and namespace of the object to reconcile, reconciles the object, and returns a Response or an error indicating whether to requeue for a second round of processing. Reconcilers use Clients (pkg/client) to access API objects. The default client provided by the manager reads from a local shared cache (pkg/cache) and writes directly to the API server, but clients can be constructed that only talk to the API server, without a cache. The Cache will auto-populate with watched objects, as well as when other structured objects are requested. The default split client does not promise to invalidate the cache during writes (nor does it promise sequential create/get coherence), and code should not assume a get immediately following a create/update will return the updated resource. Caches may also have indexes, which can be created via a FieldIndexer (pkg/client) obtained from the manager. Indexes can used to quickly and easily look up all objects with certain fields set. Reconcilers may retrieve event recorders (pkg/recorder) to emit events using the manager. Clients, Caches, and many other things in Kubernetes use Schemes (pkg/scheme) to associate Go types to Kubernetes API Kinds (Group-Version-Kinds, to be specific). Similarly, webhooks (pkg/webhook/admission) may be implemented directly, but are often constructed using a builder (pkg/webhook/admission/builder). They are run via a server (pkg/webhook) which is managed by a Manager. Logging (pkg/log) in controller-runtime is done via structured logs, using a log set of interfaces called logr (https://pkg.go.dev/github.com/go-logr/logr). While controller-runtime provides easy setup for using Zap (https://go.uber.org/zap, pkg/log/zap), you can provide any implementation of logr as the base logger for controller-runtime. Metrics (pkg/metrics) provided by controller-runtime are registered into a controller-runtime-specific Prometheus metrics registry. The manager can serve these by an HTTP endpoint, and additional metrics may be registered to this Registry as normal. You can easily build integration and unit tests for your controllers and webhooks using the test Environment (pkg/envtest). This will automatically stand up a copy of etcd and kube-apiserver, and provide the correct options to connect to the API server. It's designed to work well with the Ginkgo testing framework, but should work with any testing setup. This example creates a simple application Controller that is configured for ReplicaSets and Pods. * Create a new application for ReplicaSets that manages Pods owned by the ReplicaSet and calls into ReplicaSetReconciler. * Start the application. This example creates a simple application Controller that is configured for ExampleCRDWithConfigMapRef CRD. Any change in the configMap referenced in this Custom Resource will cause the re-reconcile of the parent ExampleCRDWithConfigMapRef due to the implementation of the .Watches method of "sigs.k8s.io/controller-runtime/pkg/builder".Builder. This example creates a simple application Controller that is configured for ReplicaSets and Pods. This application controller will be running leader election with the provided configuration in the manager options. If leader election configuration is not provided, controller runs leader election with default values. Default values taken from: https://github.com/kubernetes/component-base/blob/master/config/v1alpha1/defaults.go * defaultLeaseDuration = 15 * time.Second * defaultRenewDeadline = 10 * time.Second * defaultRetryPeriod = 2 * time.Second * Create a new application for ReplicaSets that manages Pods owned by the ReplicaSet and calls into ReplicaSetReconciler. * Start 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 hashivault provides a secrets implementation using the Transit Secrets Engine of Vault by Hashicorp. Use OpenKeeper to construct a *secrets.Keeper. For secrets.OpenKeeper, hashivault registers for the scheme "hashivault". The default URL opener will dial a Vault server using the environment variables "VAULT_SERVER_URL" (or "VAULT_ADDR") and "VAULT_SERVER_TOKEN" (or "VAULT_TOKEN"). To customize the URL opener, or for more details on the URL format, see URLOpener. See https://gocloud.dev/concepts/urls/ for background information. hashivault does not support any types for As.

Package mgo offers a rich MongoDB driver for Go. ######################################################### THIS DRIVER IS UNMAINTAINED! See here for details: https://github.com/go-mgo/mgo/blob/v2-unstable/README.md ######################################################### Usage of the driver revolves around the concept of sessions. To get started, obtain a session using the Dial function: This will establish one or more connections with the cluster of servers defined by the url parameter. From then on, the cluster may be queried with multiple consistency rules (see SetMode) and documents retrieved with statements such as: New sessions are typically created by calling session.Copy on the initial session obtained at dial time. These new sessions will share the same cluster information and connection pool, and may be easily handed into other methods and functions for organizing logic. Every session created must have its Close method called at the end of its life time, so its resources may be put back in the pool or collected, depending on the case. For more details, see the documentation for the types and methods.

Package grpcurl provides the core functionality exposed by the grpcurl command, for dynamically connecting to a server, using the reflection service to inspect the server, and invoking RPCs. The grpcurl command-line tool constructs a DescriptorSource, based on the command-line parameters, and supplies an InvocationEventHandler to supply request data (which can come from command-line args or the process's stdin) and to log the events (to the process's stdout).

The plugin package exposes functions and helpers for communicating to plugins which are implemented as standalone binary applications. plugin.Client fully manages the lifecycle of executing the application, connecting to it, and returning the RPC client for dispensing plugins. plugin.Serve fully manages listeners to expose an RPC server from a binary that plugin.Client can connect to.

Package gomail provides a simple interface to compose emails and to mail them efficiently. More info on Github: https://github.com/go-gomail/gomail A daemon that listens to a channel and sends all incoming messages. Efficiently send a customized newsletter to a list of recipients. Send an email using a local SMTP server. Send an email using an API or postfix.

Package firestore provides a client for reading and writing to a Cloud Firestore database. See https://cloud.google.com/firestore/docs for an introduction to Cloud Firestore and additional help on using the Firestore API. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. Note: you can't use both Cloud Firestore and Cloud Datastore in the same project. To start working with this package, create a client with a project ID: In Firestore, documents are sets of key-value pairs, and collections are groups of documents. A Firestore database consists of a hierarchy of alternating collections and documents, referred to by slash-separated paths like "States/California/Cities/SanFrancisco". This client is built around references to collections and documents. CollectionRefs and DocumentRefs are lightweight values that refer to the corresponding database entities. Creating a ref does not involve any network traffic. Use DocumentRef.Get to read a document. The result is a DocumentSnapshot. Call its Data method to obtain the entire document contents as a map. You can also obtain a single field with DataAt, or extract the data into a struct with DataTo. With the type definition we can extract the document's data into a value of type State: Note that this client supports struct tags beginning with "firestore:" that work like the tags of the encoding/json package, letting you rename fields, ignore them, or omit their values when empty. To retrieve multiple documents from their references in a single call, use Client.GetAll. For writing individual documents, use the methods on DocumentReference. Create creates a new document. The first return value is a WriteResult, which contains the time at which the document was updated. Create fails if the document exists. Another method, Set, either replaces an existing document or creates a new one. To update some fields of an existing document, use Update. It takes a list of paths to update and their corresponding values. Use DocumentRef.Delete to delete a document. You can condition Deletes or Updates on when a document was last changed. Specify these preconditions as an option to a Delete or Update method. The check and the write happen atomically with a single RPC. Here we update a doc only if it hasn't changed since we read it. You could also do this with a transaction. To perform multiple writes at once, use a WriteBatch. Its methods chain for convenience. WriteBatch.Commit sends the collected writes to the server, where they happen atomically. You can use SQL to select documents from a collection. Begin with the collection, and build up a query using Select, Where and other methods of Query. Supported operators include '<', '<=', '>', '>=', '==', 'in', 'array-contains', and 'array-contains-any'. Call the Query's Documents method to get an iterator, and use it like the other Google Cloud Client iterators. To get all the documents in a collection, you can use the collection itself as a query. Firestore supports similarity search over embedding vectors. See Query.FindNearest for details. You can partition the documents of a Collection Group allowing for smaller subqueries. You can also Serialize/Deserialize queries making it possible to run/stream the queries elsewhere; another process or machine for instance. Use a transaction to execute reads and writes atomically. All reads must happen before any writes. Transaction creation, commit, rollback and retry are handled for you by the Client.RunTransaction method; just provide a function and use the read and write methods of the Transaction passed to it. This package supports the Cloud Firestore emulator, which is useful for testing and development. Environment variables are used to indicate that Firestore traffic should be directed to the emulator instead of the production Firestore service. To install and run the emulator and its environment variables, see the documentation at https://cloud.google.com/sdk/gcloud/reference/beta/emulators/firestore/. Once the emulator is running, set FIRESTORE_EMULATOR_HOST to the API endpoint.

Package pt implements the Tor pluggable transports specification. Sample client usage: Sample server usage: Some additional care is needed to handle signals and shutdown properly. See the example programs dummy-client and dummy-server. Tor pluggable transports specification: https://spec.torproject.org/pt-spec Extended ORPort: https://gitweb.torproject.org/torspec.git/tree/ext-orport-spec.txt The package implements a SOCKS5 server sufficient for a Tor client transport plugin. https://www.ietf.org/rfc/rfc1928.txt https://www.ietf.org/rfc/rfc1929.txt

Package profiler is a client for the Cloud Profiler service. Usage example: Calling Start will start a goroutine to collect profiles and upload to the profiler server, at the rhythm specified by the server. The caller must provide the service string in the config, and may provide other information as well. See Config for details. Profiler has CPU, heap and goroutine profiling enabled by default. Mutex profiling can be enabled in the config. Note that goroutine and mutex profiles are shown as "threads" and "contention" profiles in the profiler UI.

Package gocql implements a fast and robust Cassandra driver for the Go programming language. Pass a list of initial node IP addresses to NewCluster to create a new cluster configuration: Port can be specified as part of the address, the above is equivalent to: It is recommended to use the value set in the Cassandra config for broadcast_address or listen_address, an IP address not a domain name. This is because events from Cassandra will use the configured IP address, which is used to index connected hosts. If the domain name specified resolves to more than 1 IP address then the driver may connect multiple times to the same host, and will not mark the node being down or up from events. Then you can customize more options (see ClusterConfig): The driver tries to automatically detect the protocol version to use if not set, but you might want to set the protocol version explicitly, as it's not defined which version will be used in certain situations (for example during upgrade of the cluster when some of the nodes support different set of protocol versions than other nodes). The driver advertises the module name and version in the STARTUP message, so servers are able to detect the version. If you use replace directive in go.mod, the driver will send information about the replacement module instead. When ready, create a session from the configuration. Don't forget to Close the session once you are done with it: CQL protocol uses a SASL-based authentication mechanism and so consists of an exchange of server challenges and client response pairs. The details of the exchanged messages depend on the authenticator used. To use authentication, set ClusterConfig.Authenticator or ClusterConfig.AuthProvider. PasswordAuthenticator is provided to use for username/password authentication: It is possible to secure traffic between the client and server with TLS. To use TLS, set the ClusterConfig.SslOpts field. SslOptions embeds *tls.Config so you can set that directly. There are also helpers to load keys/certificates from files. Warning: Due to historical reasons, the SslOptions is insecure by default, so you need to set EnableHostVerification to true if no Config is set. Most users should set SslOptions.Config to a *tls.Config. SslOptions and Config.InsecureSkipVerify interact as follows: For example: To route queries to local DC first, use DCAwareRoundRobinPolicy. For example, if the datacenter you want to primarily connect is called dc1 (as configured in the database): The driver can route queries to nodes that hold data replicas based on partition key (preferring local DC). Note that TokenAwareHostPolicy can take options such as gocql.ShuffleReplicas and gocql.NonLocalReplicasFallback. We recommend running with a token aware host policy in production for maximum performance. The driver can only use token-aware routing for queries where all partition key columns are query parameters. For example, instead of use The DCAwareRoundRobinPolicy can be replaced with RackAwareRoundRobinPolicy, which takes two parameters, datacenter and rack. Instead of dividing hosts with two tiers (local datacenter and remote datacenters) it divides hosts into three (the local rack, the rest of the local datacenter, and everything else). RackAwareRoundRobinPolicy can be combined with TokenAwareHostPolicy in the same way as DCAwareRoundRobinPolicy. Create queries with Session.Query. Query values must not be reused between different executions and must not be modified after starting execution of the query. To execute a query without reading results, use Query.Exec: Single row can be read by calling Query.Scan: Multiple rows can be read using Iter.Scanner: See Example for complete example. The driver automatically prepares DML queries (SELECT/INSERT/UPDATE/DELETE/BATCH statements) and maintains a cache of prepared statements. CQL protocol does not support preparing other query types. When using CQL protocol >= 4, it is possible to use gocql.UnsetValue as the bound value of a column. This will cause the database to ignore writing the column. The main advantage is the ability to keep the same prepared statement even when you don't want to update some fields, where before you needed to make another prepared statement. Session is safe to use from multiple goroutines, so to execute multiple concurrent queries, just execute them from several worker goroutines. Gocql provides synchronously-looking API (as recommended for Go APIs) and the queries are executed asynchronously at the protocol level. Null values are are unmarshalled as zero value of the type. If you need to distinguish for example between text column being null and empty string, you can unmarshal into *string variable instead of string. See Example_nulls for full example. The driver reuses backing memory of slices when unmarshalling. This is an optimization so that a buffer does not need to be allocated for every processed row. However, you need to be careful when storing the slices to other memory structures. When you want to save the data for later use, pass a new slice every time. A common pattern is to declare the slice variable within the scanner loop: The driver supports paging of results with automatic prefetch, see ClusterConfig.PageSize, Session.SetPrefetch, Query.PageSize, and Query.Prefetch. It is also possible to control the paging manually with Query.PageState (this disables automatic prefetch). Manual paging is useful if you want to store the page state externally, for example in a URL to allow users browse pages in a result. You might want to sign/encrypt the paging state when exposing it externally since it contains data from primary keys. Paging state is specific to the CQL protocol version and the exact query used. It is meant as opaque state that should not be modified. If you send paging state from different query or protocol version, then the behaviour is not defined (you might get unexpected results or an error from the server). For example, do not send paging state returned by node using protocol version 3 to a node using protocol version 4. Also, when using protocol version 4, paging state between Cassandra 2.2 and 3.0 is incompatible (https://issues.apache.org/jira/browse/CASSANDRA-10880). The driver does not check whether the paging state is from the same protocol version/statement. You might want to validate yourself as this could be a problem if you store paging state externally. For example, if you store paging state in a URL, the URLs might become broken when you upgrade your cluster. Call Query.PageState(nil) to fetch just the first page of the query results. Pass the page state returned by Iter.PageState to Query.PageState of a subsequent query to get the next page. If the length of slice returned by Iter.PageState is zero, there are no more pages available (or an error occurred). Using too low values of PageSize will negatively affect performance, a value below 100 is probably too low. While Cassandra returns exactly PageSize items (except for last page) in a page currently, the protocol authors explicitly reserved the right to return smaller or larger amount of items in a page for performance reasons, so don't rely on the page having the exact count of items. See Example_paging for an example of manual paging. There are certain situations when you don't know the list of columns in advance, mainly when the query is supplied by the user. Iter.Columns, Iter.RowData, Iter.MapScan and Iter.SliceMap can be used to handle this case. See Example_dynamicColumns. The CQL protocol supports sending batches of DML statements (INSERT/UPDATE/DELETE) and so does gocql. Use Session.NewBatch to create a new batch and then fill-in details of individual queries. Then execute the batch with Session.ExecuteBatch. Logged batches ensure atomicity, either all or none of the operations in the batch will succeed, but they have overhead to ensure this property. Unlogged batches don't have the overhead of logged batches, but don't guarantee atomicity. Updates of counters are handled specially by Cassandra so batches of counter updates have to use CounterBatch type. A counter batch can only contain statements to update counters. For unlogged batches it is recommended to send only single-partition batches (i.e. all statements in the batch should involve only a single partition). Multi-partition batch needs to be split by the coordinator node and re-sent to correct nodes. With single-partition batches you can send the batch directly to the node for the partition without incurring the additional network hop. It is also possible to pass entire BEGIN BATCH .. APPLY BATCH statement to Query.Exec. There are differences how those are executed. BEGIN BATCH statement passed to Query.Exec is prepared as a whole in a single statement. Session.ExecuteBatch prepares individual statements in the batch. If you have variable-length batches using the same statement, using Session.ExecuteBatch is more efficient. See Example_batch for an example. Query.ScanCAS or Query.MapScanCAS can be used to execute a single-statement lightweight transaction (an INSERT/UPDATE .. IF statement) and reading its result. See example for Query.MapScanCAS. Multiple-statement lightweight transactions can be executed as a logged batch that contains at least one conditional statement. All the conditions must return true for the batch to be applied. You can use Session.ExecuteBatchCAS and Session.MapExecuteBatchCAS when executing the batch to learn about the result of the LWT. See example for Session.MapExecuteBatchCAS. Queries can be marked as idempotent. Marking the query as idempotent tells the driver that the query can be executed multiple times without affecting its result. Non-idempotent queries are not eligible for retrying nor speculative execution. Idempotent queries are retried in case of errors based on the configured RetryPolicy. Queries can be retried even before they fail by setting a SpeculativeExecutionPolicy. The policy can cause the driver to retry on a different node if the query is taking longer than a specified delay even before the driver receives an error or timeout from the server. When a query is speculatively executed, the original execution is still executing. The two parallel executions of the query race to return a result, the first received result will be returned. UDTs can be mapped (un)marshaled from/to map[string]interface{} a Go struct (or a type implementing UDTUnmarshaler, UDTMarshaler, Unmarshaler or Marshaler interfaces). For structs, cql tag can be used to specify the CQL field name to be mapped to a struct field: See Example_userDefinedTypesMap, Example_userDefinedTypesStruct, ExampleUDTMarshaler, ExampleUDTUnmarshaler. It is possible to provide observer implementations that could be used to gather metrics: CQL protocol also supports tracing of queries. When enabled, the database will write information about internal events that happened during execution of the query. You can use Query.Trace to request tracing and receive the session ID that the database used to store the trace information in system_traces.sessions and system_traces.events tables. NewTraceWriter returns an implementation of Tracer that writes the events to a writer. Gathering trace information might be essential for debugging and optimizing queries, but writing traces has overhead, so this feature should not be used on production systems with very high load unless you know what you are doing. Example_batch demonstrates how to execute a batch of statements. Example_dynamicColumns demonstrates how to handle dynamic column list. Example_marshalerUnmarshaler demonstrates how to implement a Marshaler and Unmarshaler. Example_nulls demonstrates how to distinguish between null and zero value when needed. Null values are unmarshalled as zero value of the type. If you need to distinguish for example between text column being null and empty string, you can unmarshal into *string field. Example_paging demonstrates how to manually fetch pages and use page state. See also package documentation about paging. Example_set demonstrates how to use sets. Example_userDefinedTypesMap demonstrates how to work with user-defined types as maps. See also Example_userDefinedTypesStruct and examples for UDTMarshaler and UDTUnmarshaler if you want to map to structs. Example_userDefinedTypesStruct demonstrates how to work with user-defined types as structs. See also examples for UDTMarshaler and UDTUnmarshaler if you need more control/better performance.

Package elastic provides an interface to the Elasticsearch server (https://www.elastic.co/products/elasticsearch). The first thing you do is to create a Client. If you have Elasticsearch installed and running with its default settings (i.e. available at http://127.0.0.1:9200), all you need to do is: If your Elasticsearch server is running on a different IP and/or port, just provide a URL to NewClient: You can pass many more configuration parameters to NewClient. Review the documentation of NewClient for more information. If no Elasticsearch server is available, services will fail when creating a new request and will return ErrNoClient. A Client provides services. The services usually come with a variety of methods to prepare the query and a Do function to execute it against the Elasticsearch REST interface and return a response. Here is an example of the IndexExists service that checks if a given index already exists. Look up the documentation for Client to get an idea of the services provided and what kinds of responses you get when executing the Do function of a service. Also see the wiki on Github for more details. Copyright 2012-present Oliver Eilhard. All rights reserved. Use of this source code is governed by a MIT-license. See http://olivere.mit-license.org/license.txt for details.

Package otlpmetricgrpc provides an OTLP metrics exporter using gRPC. By default the telemetry is sent to https://localhost:4317. Exporter should be created using New and used with a metric.PeriodicReader. The environment variables described below can be used for configuration. OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_METRICS_ENDPOINT (default: "https://localhost:4317") - target to which the exporter sends telemetry. The target syntax is defined in https://github.com/grpc/grpc/blob/master/doc/naming.md. The value must contain a scheme ("http" or "https") and host. The value may additionally contain a port, and a path. The value should not contain a query string or fragment. OTEL_EXPORTER_OTLP_METRICS_ENDPOINT takes precedence over OTEL_EXPORTER_OTLP_ENDPOINT. The configuration can be overridden by WithEndpoint, WithEndpointURL, WithInsecure, and WithGRPCConn options. OTEL_EXPORTER_OTLP_INSECURE, OTEL_EXPORTER_OTLP_METRICS_INSECURE (default: "false") - setting "true" disables client transport security for the exporter's gRPC connection. You can use this only when an endpoint is provided without the http or https scheme. OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_METRICS_ENDPOINT setting overrides the scheme defined via OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_METRICS_ENDPOINT. OTEL_EXPORTER_OTLP_METRICS_INSECURE takes precedence over OTEL_EXPORTER_OTLP_INSECURE. The configuration can be overridden by WithInsecure, WithGRPCConn options. OTEL_EXPORTER_OTLP_HEADERS, OTEL_EXPORTER_OTLP_METRICS_HEADERS (default: none) - key-value pairs used as gRPC metadata associated with gRPC requests. The value is expected to be represented in a format matching the W3C Baggage HTTP Header Content Format, except that additional semi-colon delimited metadata is not supported. Example value: "key1=value1,key2=value2". OTEL_EXPORTER_OTLP_METRICS_HEADERS takes precedence over OTEL_EXPORTER_OTLP_HEADERS. The configuration can be overridden by WithHeaders option. OTEL_EXPORTER_OTLP_TIMEOUT, OTEL_EXPORTER_OTLP_METRICS_TIMEOUT (default: "10000") - maximum time in milliseconds the OTLP exporter waits for each batch export. OTEL_EXPORTER_OTLP_METRICS_TIMEOUT takes precedence over OTEL_EXPORTER_OTLP_TIMEOUT. The configuration can be overridden by WithTimeout option. OTEL_EXPORTER_OTLP_COMPRESSION, OTEL_EXPORTER_OTLP_METRICS_COMPRESSION (default: none) - the gRPC compressor the exporter uses. Supported value: "gzip". OTEL_EXPORTER_OTLP_METRICS_COMPRESSION takes precedence over OTEL_EXPORTER_OTLP_COMPRESSION. The configuration can be overridden by WithCompressor, WithGRPCConn options. OTEL_EXPORTER_OTLP_CERTIFICATE, OTEL_EXPORTER_OTLP_METRICS_CERTIFICATE (default: none) - the filepath to the trusted certificate to use when verifying a server's TLS credentials. OTEL_EXPORTER_OTLP_METRICS_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CERTIFICATE. The configuration can be overridden by WithTLSCredentials, WithGRPCConn options. OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE, OTEL_EXPORTER_OTLP_METRICS_CLIENT_CERTIFICATE (default: none) - the filepath to the client certificate/chain trust for client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_METRICS_CLIENT_CERTIFICATE takes precedence over OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE. The configuration can be overridden by WithTLSCredentials, WithGRPCConn options. OTEL_EXPORTER_OTLP_CLIENT_KEY, OTEL_EXPORTER_OTLP_METRICS_CLIENT_KEY (default: none) - the filepath to the client's private key to use in mTLS communication in PEM format. OTEL_EXPORTER_OTLP_METRICS_CLIENT_KEY takes precedence over OTEL_EXPORTER_OTLP_CLIENT_KEY. The configuration can be overridden by WithTLSCredentials, WithGRPCConn option. OTEL_EXPORTER_OTLP_METRICS_TEMPORALITY_PREFERENCE (default: "cumulative") - aggregation temporality to use on the basis of instrument kind. Supported values: The configuration can be overridden by WithTemporalitySelector option. OTEL_EXPORTER_OTLP_METRICS_DEFAULT_HISTOGRAM_AGGREGATION (default: "explicit_bucket_histogram") - default aggregation to use for histogram instruments. Supported values: The configuration can be overridden by WithAggregationSelector option.

Package ws implements a client and server for the WebSocket protocol as specified in RFC 6455. The main purpose of this package is to provide simple low-level API for efficient work with protocol. Overview. Upgrade to WebSocket (or WebSocket handshake) can be done in two ways. The first way is to use `net/http` server: The second and much more efficient way is so-called "zero-copy upgrade". It avoids redundant allocations and copying of not used headers or other request data. User decides by himself which data should be copied. For customization details see `ws.Upgrader` documentation. After WebSocket handshake you can work with connection in multiple ways. That is, `ws` does not force the only one way of how to work with WebSocket: As you can see, it stream friendly: Or: For more info see the documentation.

Package middleware `middleware` is a collection of gRPC middleware packages: interceptors, helpers and tools. gRPC is a fantastic RPC middleware, which sees a lot of adoption in the Golang world. However, the upstream gRPC codebase is relatively bare bones. This package, and most of its child packages provides commonly needed middleware for gRPC: client-side interceptors for retires, server-side interceptors for input validation and auth, functions for chaining said interceptors, metadata convenience methods and more. Simple way of turning a multiple interceptors into a single interceptor. Here's an example for server chaining: These interceptors will be executed from left to right: logging, monitoring and auth. Here's an example for client side chaining: These interceptors will be executed from left to right: monitoring and then retry logic. The retry interceptor will call every interceptor that follows it whenever when a retry happens. Implementing your own interceptor is pretty trivial: there are interfaces for that. But the interesting bit exposing common data to handlers (and other middleware), similarly to HTTP Middleware design. For example, you may want to pass the identity of the caller from the auth interceptor all the way to the handling function. For example, a client side interceptor example for auth looks like: Unfortunately, it's not as easy for streaming RPCs. These have the `context.Context` embedded within the `grpc.ServerStream` object. To pass values through context, a wrapper (`WrappedServerStream`) is needed. For example:

Package ssh wraps the crypto/ssh package with a higher-level API for building SSH servers. The goal of the API was to make it as simple as using net/http, so the API is very similar. You should be able to build any SSH server using only this package, which wraps relevant types and some functions from crypto/ssh. However, you still need to use crypto/ssh for building SSH clients. ListenAndServe starts an SSH server with a given address, handler, and options. The handler is usually nil, which means to use DefaultHandler. Handle sets DefaultHandler: If you don't specify a host key, it will generate one every time. This is convenient except you'll have to deal with clients being confused that the host key is different. It's a better idea to generate or point to an existing key on your system: Although all options have functional option helpers, another way to control the server's behavior is by creating a custom Server: This package automatically handles basic SSH requests like setting environment variables, requesting PTY, and changing window size. These requests are processed, responded to, and any relevant state is updated. This state is then exposed to you via the Session interface. The one big feature missing from the Session abstraction is signals. This was started, but not completed. Pull Requests welcome!

Package smtpd implements a basic SMTP server.

package mssql implements the TDS protocol used to connect to MS SQL Server (sqlserver) database servers. This package registers the driver: If the ordinal position is used for query parameters, identifiers will be named "@p1", "@p2", ... "@pN". Please refer to the README for the format of the DSN. There are multiple DSN formats accepted: ADO style, ODBC style, and URL style. The following is an example of a URL style DSN:

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.