Debugging

Package clientv3 implements the official Go etcd client for v3. Create client using `clientv3.New`: Make sure to close the client after using it. If the client is not closed, the connection will have leaky goroutines. To specify a client request timeout, wrap the context with context.WithTimeout: The Client has internal state (watchers and leases), so Clients should be reused instead of created as needed. Clients are safe for concurrent use by multiple goroutines. etcd client returns 2 types of errors: See https://github.com/etcd-io/etcd/blob/main/api/v3rpc/rpctypes/error.go Here is the example code to handle client errors: The grpc load balancer is registered statically and is shared across etcd clients. To enable detailed load balancer logging, set the ETCD_CLIENT_DEBUG environment variable. E.g. "ETCD_CLIENT_DEBUG=1".

Package fsnotify provides a cross-platform interface for file system notifications. Currently supported systems: Set the FSNOTIFY_DEBUG environment variable to "1" to print debug messages to stderr. This can be useful to track down some problems, especially in cases where fsnotify is used as an indirect dependency. Every event will be printed as soon as there's something useful to print, with as little processing from fsnotify. Example output:

Package errors provides simple error handling primitives. The traditional error handling idiom in Go is roughly akin to which when applied recursively up the call stack results in error reports without context or debugging information. The errors package allows programmers to add context to the failure path in their code in a way that does not destroy the original value of the error. The errors.Wrap function returns a new error that adds context to the original error by recording a stack trace at the point Wrap is called, together with the supplied message. For example If additional control is required, the errors.WithStack and errors.WithMessage functions destructure errors.Wrap into its component operations: annotating an error with a stack trace and with a message, respectively. Using errors.Wrap constructs a stack of errors, adding context to the preceding error. Depending on the nature of the error it may be necessary to reverse the operation of errors.Wrap to retrieve the original error for inspection. Any error value which implements this interface can be inspected by errors.Cause. errors.Cause will recursively retrieve the topmost error that does not implement causer, which is assumed to be the original cause. For example: Although the causer interface is not exported by this package, it is considered a part of its stable public interface. All error values returned from this package implement fmt.Formatter and can be formatted by the fmt package. The following verbs are supported: New, Errorf, Wrap, and Wrapf record a stack trace at the point they are invoked. This information can be retrieved with the following interface: The returned errors.StackTrace type is defined as The Frame type represents a call site in the stack trace. Frame supports the fmt.Formatter interface that can be used for printing information about the stack trace of this error. For example: Although the stackTracer interface is not exported by this package, it is considered a part of its stable public interface. See the documentation for Frame.Format for more details.

Package cloud is the root of the packages used to access Google Cloud Services. See https://pkg.go.dev/cloud.google.com/go 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: ## Google-reserved headers 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 system parameters 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 option.WithGRPCConnectionPool(n) 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. If the gRPC transport was used, the google.golang.org/grpc/status.Status can still be parsed using the google.golang.org/grpc/status.FromError function. 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 glog implements logging analogous to the Google-internal C++ INFO/ERROR/V setup. It provides functions that have a name matched by regex: If Context is present, function takes context.Context argument. The context is used to pass through the Trace Context to log sinks that can make use of it. It is recommended to use the context variant of the functions over the non-context variants if a context is available to make sure the Trace Contexts are present in logs. If Depth is present, this function calls log from a different depth in the call stack. This enables a callee to emit logs that use the callsite information of its caller or any other callers in the stack. When depth == 0, the original callee's line information is emitted. When depth > 0, depth frames are skipped in the call stack and the final frame is treated like the original callee to Info. If 'f' is present, function formats according to a format specifier. This package also provides V-style logging controlled by the -v and -vmodule=file=2 flags. Basic examples: See the documentation for the V function for an explanation of these examples: Log output is buffered and written periodically using Flush. Programs should call Flush before exiting to guarantee all log output is written. By default, all log statements write to files in a temporary directory. This package provides several flags that modify this behavior. As a result, flag.Parse must be called before any logging is done. Other flags provide aids to debugging.

Package pgx is a PostgreSQL database driver. pgx provides a native PostgreSQL driver and can act as a database/sql driver. The native PostgreSQL interface is similar to the database/sql interface while providing better speed and access to PostgreSQL specific features. Use github.com/jackc/pgx/v5/stdlib to use pgx as a database/sql compatible driver. See that package's documentation for details. The primary way of establishing a connection is with pgx.Connect: The database connection string can be in URL or key/value format. Both PostgreSQL settings and pgx settings can be specified here. In addition, a config struct can be created by ParseConfig and modified before establishing the connection with ConnectConfig to configure settings such as tracing that cannot be configured with a connection string. *pgx.Conn represents a single connection to the database and is not concurrency safe. Use package github.com/jackc/pgx/v5/pgxpool for a concurrency safe connection pool. pgx implements Query in the familiar database/sql style. However, pgx provides generic functions such as CollectRows and ForEachRow that are a simpler and safer way of processing rows than manually calling defer rows.Close(), rows.Next(), rows.Scan, and rows.Err(). CollectRows can be used collect all returned rows into a slice. ForEachRow can be used to execute a callback function for every row. This is often easier than iterating over rows directly. pgx also implements QueryRow in the same style as database/sql. Use Exec to execute a query that does not return a result set. pgx uses the pgtype package to converting Go values to and from PostgreSQL values. It supports many PostgreSQL types directly and is customizable and extendable. User defined data types such as enums, domains, and composite types may require type registration. See that package's documentation for details. Transactions are started by calling Begin. The Tx returned from Begin also implements the Begin method. This can be used to implement pseudo nested transactions. These are internally implemented with savepoints. Use BeginTx to control the transaction mode. BeginTx also can be used to ensure a new transaction is created instead of a pseudo nested transaction. BeginFunc and BeginTxFunc are functions that begin a transaction, execute a function, and commit or rollback the transaction depending on the return value of the function. These can be simpler and less error prone to use. Prepared statements can be manually created with the Prepare method. However, this is rarely necessary because pgx includes an automatic statement cache by default. Queries run through the normal Query, QueryRow, and Exec functions are automatically prepared on first execution and the prepared statement is reused on subsequent executions. See ParseConfig for information on how to customize or disable the statement cache. 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 [][]any use CopyFromRows to wrap it in a CopyFromSource interface. Or implement CopyFromSource to avoid buffering the entire data set in memory. When you already have a typed array using CopyFromSlice can be more convenient. CopyFrom can be faster than an insert with as few as 5 rows. pgx can listen to the PostgreSQL notification system with the `Conn.WaitForNotification` method. It blocks until a notification is received or the context is canceled. pgx supports tracing by setting ConnConfig.Tracer. To combine several tracers you can use the multitracer.Tracer. In addition, the tracelog package provides the TraceLog type which lets a traditional logger act as a Tracer. For debug tracing of the actual PostgreSQL wire protocol messages see github.com/jackc/pgx/v5/pgproto3. github.com/jackc/pgx/v5/pgconn contains a lower level PostgreSQL driver roughly at the level of libpq. pgx.Conn in implemented on top of pgconn. The Conn.PgConn() method can be used to access this lower layer. By default pgx automatically uses prepared statements. Prepared statements are incompatible with PgBouncer. This can be disabled by setting a different QueryExecMode in ConnConfig.DefaultQueryExecMode.

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 ebiten provides graphics and input API to develop a 2D game. You can start the game by calling the function RunGame. In the API document, 'the main thread' means the goroutine in init(), main() and their callees without 'go' statement. It is assured that 'the main thread' runs on the OS main thread. There are some Ebitengine functions (e.g., DeviceScaleFactor) that must be called on the main thread under some conditions (typically, before ebiten.RunGame is called). `EBITENGINE_SCREENSHOT_KEY` environment variable specifies the key to take a screenshot. For example, if you run your game with `EBITENGINE_SCREENSHOT_KEY=q`, you can take a game screen's screenshot by pressing Q key. This works only on desktops and browsers. `EBITENGINE_INTERNAL_IMAGES_KEY` environment variable specifies the key to dump all the internal images. This is valid only when the build tag 'ebitenginedebug' is specified. This works only on desktops and browsers. `EBITENGINE_GRAPHICS_LIBRARY` environment variable specifies the graphics library. If the specified graphics library is not available, RunGame returns an error. This environment variable works when RunGame is called or RunGameWithOptions is called with GraphicsLibraryAuto. This can take one of the following value: `EBITENGINE_DIRECTX` environment variable specifies various parameters for DirectX. You can specify multiple values separated by a comma. The default value is empty (i.e. no parameters). The options taking arguments are exclusive, and if multiples are specified, the lastly specified value is adopted. The possible values for the option "version" are "11" and "12". If the version is not specified, the default version 11 is adopted. On Xbox, the "version" option is ignored and DirectX 12 is always adopted. The option "featurelevel" is valid only for DirectX 12. The possible values are "11_0", "11_1", "12_0", "12_1", and "12_2". The default value is "11_0". `ebitenginedebug` outputs a log of graphics commands. This is useful to know what happens in Ebitengine. In general, the number of graphics commands affects the performance of your game. `ebitenginegldebug` enables a debug mode for OpenGL. This is valid only when the graphics library is OpenGL. This affects performance very much. `ebitenginesinglethread` disables Ebitengine's thread safety to unlock maximum performance. If you use this you will have to manage threads yourself. Functions like `SetWindowSize` will no longer be concurrent-safe with this build tag. They must be called from the main thread or the same goroutine as the given game's callback functions like Update `ebitenginesinglethread` works only with desktops and consoles. `ebitenginesinglethread` was deprecated as of v2.7. Use RunGameOptions.SingleThread instead. `microsoftgdk` is for Microsoft GDK (e.g. Xbox). `nintendosdk` is for NintendoSDK (e.g. Nintendo Switch). `nintendosdkprofile` enables a profiler for NintendoSDK. `playstation5` is for PlayStation 5.

Package stdoutmetric provides an exporter for OpenTelemetry metric telemetry. The exporter is intended to be used for testing and debugging, it is not meant for production use. Additionally, it does not provide an interchange format for OpenTelemetry that is supported with any stability or compatibility guarantees. If these are needed features, please use the OTLP exporter instead.

Package rod is a high-level driver directly based on DevTools Protocol. This example opens https://github.com/, searches for "git", and then gets the header element which gives the description for Git. Rod use https://golang.org/pkg/context to handle cancellations for IO blocking operations, most times it's timeout. Context will be recursively passed to all sub-methods. For example, methods like Page.Context(ctx) will return a clone of the page with the ctx, all the methods of the returned page will use the ctx if they have IO blocking operations. Page.Timeout or Page.WithCancel is just a shortcut for Page.Context. Of course, Browser or Element works the same way. Shows how we can further customize the browser with the launcher library. Usually you use launcher lib to set the browser's command line flags (switches). Doc for flags: https://peter.sh/experiments/chromium-command-line-switches Shows how to change the retry/polling options that is used to query elements. This is useful when you want to customize the element query retry logic. When rod doesn't have a feature that you need. You can easily call the cdp to achieve it. List of cdp API: https://github.com/go-rod/rod/tree/main/lib/proto Shows how to disable headless mode and debug. Rod provides a lot of debug options, you can set them with setter methods or use environment variables. Doc for environment variables: https://pkg.go.dev/github.com/go-rod/rod/lib/defaults We use "Must" prefixed functions to write example code. But in production you may want to use the no-prefix version of them. About why we use "Must" as the prefix, it's similar to https://golang.org/pkg/regexp/#MustCompile Shows how to share a remote object reference between two Eval. Shows how to listen for events. Shows how to intercept requests and modify both the request and the response. The entire process of hijacking one request: The --req-> and --res-> are the parts that can be modified. Show how to handle multiple results of an action. Such as when you login a page, the result can be success or wrong password. Example_search shows how to use Search to get element inside nested iframes or shadow DOMs. It works the same as https://developers.google.com/web/tools/chrome-devtools/dom#search Shows how to update the state of the current page. In this example we enable the network domain. Rod uses mouse cursor to simulate clicks, so if a button is moving because of animation, the click may not work as expected. We usually use WaitStable to make sure the target isn't changing anymore. When you want to wait for an ajax request to complete, this example will be useful.

Package seelog implements logging functionality with flexible dispatching, filtering, and formatting. To create a logger, use one of the following constructors: Example: The "defer" line is important because if you are using asynchronous logger behavior, without this line you may end up losing some messages when you close your application because they are processed in another non-blocking goroutine. To avoid that you explicitly defer flushing all messages before closing. Logger created using one of the LoggerFrom* funcs can be used directly by calling one of the main log funcs. Example: Having loggers as variables is convenient if you are writing your own package with internal logging or if you have several loggers with different options. But for most standalone apps it is more convenient to use package level funcs and vars. There is a package level var 'Current' made for it. You can replace it with another logger using 'ReplaceLogger' and then use package level funcs: Last lines do the same as In this example the 'Current' logger was replaced using a 'ReplaceLogger' call and became equal to 'logger' variable created from config. This way you are able to use package level funcs instead of passing the logger variable. Main seelog point is to configure logger via config files and not the code. The configuration is read by LoggerFrom* funcs. These funcs read xml configuration from different sources and try to create a logger using it. All the configuration features are covered in detail in the official wiki: https://github.com/cihub/seelog/wiki. There are many sections covering different aspects of seelog, but the most important for understanding configs are: After you understand these concepts, check the 'Reference' section on the main wiki page to get the up-to-date list of dispatchers, receivers, formats, and logger types. Here is an example config with all these features: This config represents a logger with adaptive timeout between log messages (check logger types reference) which logs to console, all.log, and errors.log depending on the log level. Its output formats also depend on log level. This logger will only use log level 'debug' and higher (minlevel is set) for all files with names that don't start with 'test'. For files starting with 'test' this logger prohibits all levels below 'error'. Although configuration using code is not recommended, it is sometimes needed and it is possible to do with seelog. Basically, what you need to do to get started is to create constraints, exceptions and a dispatcher tree (same as with config). Most of the New* functions in this package are used to provide such capabilities. Here is an example of configuration in code, that demonstrates an async loop logger that logs to a simple split dispatcher with a console receiver using a specified format and is filtered using a top-level min-max constraints and one expection for the 'main.go' file. So, this is basically a demonstration of configuration of most of the features: To learn seelog features faster you should check the examples package: https://github.com/cihub/seelog-examples It contains many example configs and usecases.

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

Package pretty provides pretty-printing for Go values. This is useful during debugging, to avoid wrapping long output lines in the terminal. It provides a function, Formatter, that can be used with any function that accepts a format string. It also provides convenience wrappers for functions in packages fmt and log.

Package validator implements value validations for structs and individual fields based on tags. It can also handle Cross Field and Cross Struct validation for nested structs. Validate A simple example usage: The error can be used like so Both StructErrors and FieldError implement the Error interface but it's intended use is for development + debugging, not a production error message. Why not a better error message? because this library intends for you to handle your own error messages Why should I handle my own errors? Many reasons, for us building an internationalized application I needed to know the field and what validation failed so that I could provide an error in the users specific language. The hierarchical error structure is hard to work with sometimes.. Agreed Flatten function to the rescue! Flatten will return a map of FieldError's but the field name will be namespaced. Custom functions can be added Cross Field Validation can be implemented, for example Start & End Date range validation Multiple validators on a field will process in the order defined Bad Validator definitions are not handled by the library NOTE: Baked In Cross field validation only compares fields on the same struct, if cross field + cross struct validation is needed your own custom validator should be implemented. NOTE2: comma is the default separator of validation tags, if you wish to have a comma included within the parameter i.e. excludesall=, you will need to use the UTF-8 hex representation 0x2C, which is replaced in the code as a comma, so the above will become excludesall=0x2C Here is a list of the current built in validators: Validator notes: This package panics when bad input is provided, this is by design, bad code like that should not make it to production.

Package log15 provides an opinionated, simple toolkit for best-practice logging that is both human and machine readable. It is modeled after the standard library's io and net/http packages. This package enforces you to only log key/value pairs. Keys must be strings. Values may be any type that you like. The default output format is logfmt, but you may also choose to use JSON instead if that suits you. Here's how you log: This will output a line that looks like: To get started, you'll want to import the library: Now you're ready to start logging: Because recording a human-meaningful message is common and good practice, the first argument to every logging method is the value to the *implicit* key 'msg'. Additionally, the level you choose for a message will be automatically added with the key 'lvl', and so will the current timestamp with key 't'. You may supply any additional context as a set of key/value pairs to the logging function. log15 allows you to favor terseness, ordering, and speed over safety. This is a reasonable tradeoff for logging functions. You don't need to explicitly state keys/values, log15 understands that they alternate in the variadic argument list: If you really do favor your type-safety, you may choose to pass a log.Ctx instead: Frequently, you want to add context to a logger so that you can track actions associated with it. An http request is a good example. You can easily create new loggers that have context that is automatically included with each log line: This will output a log line that includes the path context that is attached to the logger: The Handler interface defines where log lines are printed to and how they are formated. Handler is a single interface that is inspired by net/http's handler interface: Handlers can filter records, format them, or dispatch to multiple other Handlers. This package implements a number of Handlers for common logging patterns that are easily composed to create flexible, custom logging structures. Here's an example handler that prints logfmt output to Stdout: Here's an example handler that defers to two other handlers. One handler only prints records from the rpc package in logfmt to standard out. The other prints records at Error level or above in JSON formatted output to the file /var/log/service.json This package implements three Handlers that add debugging information to the context, CallerFileHandler, CallerFuncHandler and CallerStackHandler. Here's an example that adds the source file and line number of each logging call to the context. This will output a line that looks like: Here's an example that logs the call stack rather than just the call site. This will output a line that looks like: The "%+v" format instructs the handler to include the path of the source file relative to the compile time GOPATH. The github.com/go-stack/stack package documents the full list of formatting verbs and modifiers available. The Handler interface is so simple that it's also trivial to write your own. Let's create an example handler which tries to write to one handler, but if that fails it falls back to writing to another handler and includes the error that it encountered when trying to write to the primary. This might be useful when trying to log over a network socket, but if that fails you want to log those records to a file on disk. This pattern is so useful that a generic version that handles an arbitrary number of Handlers is included as part of this library called FailoverHandler. Sometimes, you want to log values that are extremely expensive to compute, but you don't want to pay the price of computing them if you haven't turned up your logging level to a high level of detail. This package provides a simple type to annotate a logging operation that you want to be evaluated lazily, just when it is about to be logged, so that it would not be evaluated if an upstream Handler filters it out. Just wrap any function which takes no arguments with the log.Lazy type. For example: If this message is not logged for any reason (like logging at the Error level), then factorRSAKey is never evaluated. The same log.Lazy mechanism can be used to attach context to a logger which you want to be evaluated when the message is logged, but not when the logger is created. For example, let's imagine a game where you have Player objects: You always want to log a player's name and whether they're alive or dead, so when you create the player object, you might do: Only now, even after a player has died, the logger will still report they are alive because the logging context is evaluated when the logger was created. By using the Lazy wrapper, we can defer the evaluation of whether the player is alive or not to each log message, so that the log records will reflect the player's current state no matter when the log message is written: If log15 detects that stdout is a terminal, it will configure the default handler for it (which is log.StdoutHandler) to use TerminalFormat. This format logs records nicely for your terminal, including color-coded output based on log level. Becasuse log15 allows you to step around the type system, there are a few ways you can specify invalid arguments to the logging functions. You could, for example, wrap something that is not a zero-argument function with log.Lazy or pass a context key that is not a string. Since logging libraries are typically the mechanism by which errors are reported, it would be onerous for the logging functions to return errors. Instead, log15 handles errors by making these guarantees to you: - Any log record containing an error will still be printed with the error explained to you as part of the log record. - Any log record containing an error will include the context key LOG15_ERROR, enabling you to easily (and if you like, automatically) detect if any of your logging calls are passing bad values. Understanding this, you might wonder why the Handler interface can return an error value in its Log method. Handlers are encouraged to return errors only if they fail to write their log records out to an external source like if the syslog daemon is not responding. This allows the construction of useful handlers which cope with those failures like the FailoverHandler. log15 is intended to be useful for library authors as a way to provide configurable logging to users of their library. Best practice for use in a library is to always disable all output for your logger by default and to provide a public Logger instance that consumers of your library can configure. Like so: Users of your library may then enable it if they like: The ability to attach context to a logger is a powerful one. Where should you do it and why? I favor embedding a Logger directly into any persistent object in my application and adding unique, tracing context keys to it. For instance, imagine I am writing a web browser: When a new tab is created, I assign a logger to it with the url of the tab as context so it can easily be traced through the logs. Now, whenever we perform any operation with the tab, we'll log with its embedded logger and it will include the tab title automatically: There's only one problem. What if the tab url changes? We could use log.Lazy to make sure the current url is always written, but that would mean that we couldn't trace a tab's full lifetime through our logs after the user navigate to a new URL. Instead, think about what values to attach to your loggers the same way you think about what to use as a key in a SQL database schema. If it's possible to use a natural key that is unique for the lifetime of the object, do so. But otherwise, log15's ext package has a handy RandId function to let you generate what you might call "surrogate keys" They're just random hex identifiers to use for tracing. Back to our Tab example, we would prefer to set up our Logger like so: Now we'll have a unique traceable identifier even across loading new urls, but we'll still be able to see the tab's current url in the log messages. For all Handler functions which can return an error, there is a version of that function which will return no error but panics on failure. They are all available on the Must object. For example: All of the following excellent projects inspired the design of this library: code.google.com/p/log4go github.com/op/go-logging github.com/technoweenie/grohl github.com/Sirupsen/logrus github.com/kr/logfmt github.com/spacemonkeygo/spacelog golang's stdlib, notably io and net/http https://xkcd.com/927/

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

Package log15 provides an opinionated, simple toolkit for best-practice logging that is both human and machine readable. It is modeled after the standard library's io and net/http packages. This package enforces you to only log key/value pairs. Keys must be strings. Values may be any type that you like. The default output format is logfmt, but you may also choose to use JSON instead if that suits you. Here's how you log: This will output a line that looks like: To get started, you'll want to import the library: Now you're ready to start logging: Because recording a human-meaningful message is common and good practice, the first argument to every logging method is the value to the *implicit* key 'msg'. Additionally, the level you choose for a message will be automatically added with the key 'lvl', and so will the current timestamp with key 't'. You may supply any additional context as a set of key/value pairs to the logging function. log15 allows you to favor terseness, ordering, and speed over safety. This is a reasonable tradeoff for logging functions. You don't need to explicitly state keys/values, log15 understands that they alternate in the variadic argument list: If you really do favor your type-safety, you may choose to pass a log.Ctx instead: Frequently, you want to add context to a logger so that you can track actions associated with it. An http request is a good example. You can easily create new loggers that have context that is automatically included with each log line: This will output a log line that includes the path context that is attached to the logger: The Handler interface defines where log lines are printed to and how they are formated. Handler is a single interface that is inspired by net/http's handler interface: Handlers can filter records, format them, or dispatch to multiple other Handlers. This package implements a number of Handlers for common logging patterns that are easily composed to create flexible, custom logging structures. Here's an example handler that prints logfmt output to Stdout: Here's an example handler that defers to two other handlers. One handler only prints records from the rpc package in logfmt to standard out. The other prints records at Error level or above in JSON formatted output to the file /var/log/service.json This package implements three Handlers that add debugging information to the context, CallerFileHandler, CallerFuncHandler and CallerStackHandler. Here's an example that adds the source file and line number of each logging call to the context. This will output a line that looks like: Here's an example that logs the call stack rather than just the call site. This will output a line that looks like: The "%+v" format instructs the handler to include the path of the source file relative to the compile time GOPATH. The github.com/go-stack/stack package documents the full list of formatting verbs and modifiers available. The Handler interface is so simple that it's also trivial to write your own. Let's create an example handler which tries to write to one handler, but if that fails it falls back to writing to another handler and includes the error that it encountered when trying to write to the primary. This might be useful when trying to log over a network socket, but if that fails you want to log those records to a file on disk. This pattern is so useful that a generic version that handles an arbitrary number of Handlers is included as part of this library called FailoverHandler. Sometimes, you want to log values that are extremely expensive to compute, but you don't want to pay the price of computing them if you haven't turned up your logging level to a high level of detail. This package provides a simple type to annotate a logging operation that you want to be evaluated lazily, just when it is about to be logged, so that it would not be evaluated if an upstream Handler filters it out. Just wrap any function which takes no arguments with the log.Lazy type. For example: If this message is not logged for any reason (like logging at the Error level), then factorRSAKey is never evaluated. The same log.Lazy mechanism can be used to attach context to a logger which you want to be evaluated when the message is logged, but not when the logger is created. For example, let's imagine a game where you have Player objects: You always want to log a player's name and whether they're alive or dead, so when you create the player object, you might do: Only now, even after a player has died, the logger will still report they are alive because the logging context is evaluated when the logger was created. By using the Lazy wrapper, we can defer the evaluation of whether the player is alive or not to each log message, so that the log records will reflect the player's current state no matter when the log message is written: If log15 detects that stdout is a terminal, it will configure the default handler for it (which is log.StdoutHandler) to use TerminalFormat. This format logs records nicely for your terminal, including color-coded output based on log level. Becasuse log15 allows you to step around the type system, there are a few ways you can specify invalid arguments to the logging functions. You could, for example, wrap something that is not a zero-argument function with log.Lazy or pass a context key that is not a string. Since logging libraries are typically the mechanism by which errors are reported, it would be onerous for the logging functions to return errors. Instead, log15 handles errors by making these guarantees to you: - Any log record containing an error will still be printed with the error explained to you as part of the log record. - Any log record containing an error will include the context key LOG15_ERROR, enabling you to easily (and if you like, automatically) detect if any of your logging calls are passing bad values. Understanding this, you might wonder why the Handler interface can return an error value in its Log method. Handlers are encouraged to return errors only if they fail to write their log records out to an external source like if the syslog daemon is not responding. This allows the construction of useful handlers which cope with those failures like the FailoverHandler. log15 is intended to be useful for library authors as a way to provide configurable logging to users of their library. Best practice for use in a library is to always disable all output for your logger by default and to provide a public Logger instance that consumers of your library can configure. Like so: Users of your library may then enable it if they like: The ability to attach context to a logger is a powerful one. Where should you do it and why? I favor embedding a Logger directly into any persistent object in my application and adding unique, tracing context keys to it. For instance, imagine I am writing a web browser: When a new tab is created, I assign a logger to it with the url of the tab as context so it can easily be traced through the logs. Now, whenever we perform any operation with the tab, we'll log with its embedded logger and it will include the tab title automatically: There's only one problem. What if the tab url changes? We could use log.Lazy to make sure the current url is always written, but that would mean that we couldn't trace a tab's full lifetime through our logs after the user navigate to a new URL. Instead, think about what values to attach to your loggers the same way you think about what to use as a key in a SQL database schema. If it's possible to use a natural key that is unique for the lifetime of the object, do so. But otherwise, log15's ext package has a handy RandId function to let you generate what you might call "surrogate keys" They're just random hex identifiers to use for tracing. Back to our Tab example, we would prefer to set up our Logger like so: Now we'll have a unique traceable identifier even across loading new urls, but we'll still be able to see the tab's current url in the log messages. For all Handler functions which can return an error, there is a version of that function which will return no error but panics on failure. They are all available on the Must object. For example: All of the following excellent projects inspired the design of this library: code.google.com/p/log4go github.com/op/go-logging github.com/technoweenie/grohl github.com/Sirupsen/logrus github.com/kr/logfmt github.com/spacemonkeygo/spacelog golang's stdlib, notably io and net/http https://xkcd.com/927/

Package sfn provides the API client, operations, and parameter types for AWS Step Functions. Step Functions coordinates the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on Amazon Web Services, your own servers, or any system that has access to Amazon Web Services. You can access and use Step Functions using the console, the Amazon Web Services SDKs, or an HTTP API. For more information about Step Functions, see the Step Functions Developer Guide. If you use the Step Functions API actions using Amazon Web Services SDK integrations, make sure the API actions are in camel case and parameter names are in Pascal case. For example, you could use Step Functions API action startSyncExecution and specify its parameter as StateMachineArn .

Package netlink provides low-level access to Linux netlink sockets (AF_NETLINK). If you have any questions or you'd like some guidance, please join us on Gophers Slack (https://invite.slack.golangbridge.org) in the #networking channel! This package is aware of Linux network namespaces, and can enter different network namespaces either implicitly or explicitly, depending on configuration. The Config structure passed to Dial to create a Conn controls these behaviors. See the documentation of Config.NetNS for details. This package supports rudimentary netlink connection debugging support. To enable this, run your binary with the NLDEBUG environment variable set. Debugging information will be output to stderr with a prefix of "nl:". To use the debugging defaults, use: To configure individual aspects of the debugger, pass key/value options such as: Available key/value debugger options include:

Package goutil 💪 Useful utils for Go: int, string, array/slice, map, error, time, format, CLI, ENV, filesystem, system, testing, debug and more.

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

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

Package health provides a generic health checking framework. The health package works expvar style. By importing the package the debug server is getting a "/debug/health" endpoint that returns the current status of the application. If there are no errors, "/debug/health" will return a HTTP 200 status, together with an empty JSON reply "{}". If there are any checks with errors, the JSON reply will include all the failed checks, and the response will be have an HTTP 503 status. A Check can either be run synchronously, or asynchronously. We recommend that most checks are registered as an asynchronous check, so a call to the "/debug/health" endpoint always returns immediately. This pattern is particularly useful for checks that verify upstream connectivity or database status, since they might take a long time to return/timeout. To install health, just import it in your application: You can also (optionally) import "health/api" that will add two convenience endpoints: "/debug/health/down" and "/debug/health/up". These endpoints add "manual" checks that allow the service to quickly be brought in/out of rotation. After importing these packages to your main application, you can start registering checks. The recommended way of registering checks is using a periodic Check. PeriodicChecks run on a certain schedule and asynchronously update the status of the check. This allows CheckStatus to return without blocking on an expensive check. A trivial example of a check that runs every 5 seconds and shuts down our server if the current minute is even, could be added as follows: Alternatively, you can also make use of "RegisterPeriodicThresholdFunc" to implement the exact same check, but add a threshold of failures after which the check will be unhealthy. This is particularly useful for flaky Checks, ensuring some stability of the service when handling them. The lowest-level way to interact with the health package is calling "Register" directly. Register allows you to pass in an arbitrary string and something that implements "Checker" and runs your check. If your method returns an error with nil, it is considered a healthy check, otherwise it will make the health check endpoint "/debug/health" start returning a 503 and list the specific check that failed. Assuming you wish to register a method called "currentMinuteEvenCheck() error" you could do that by doing: CheckFunc is a convenience type that implements Checker. Another way of registering a check could be by using an anonymous function and the convenience method RegisterFunc. An example that makes the status endpoint always return an error: You could also use the health checker mechanism to ensure your application only comes up if certain conditions are met, or to allow the developer to take the service out of rotation immediately. An example that checks database connectivity and immediately takes the server out of rotation on err: You can also use the predefined Checkers that come included with the health package. First, import the checks: After that you can make use of any of the provided checks. An example of using a `FileChecker` to take the application out of rotation if a certain file exists can be done as follows: After registering the check, it is trivial to take an application out of rotation from the console: You could also test the connectivity to a downstream service by using a "HTTPChecker", but ensure that you only mark the test unhealthy if there are a minimum of two failures in a row:

Package cli provides a framework to build command line applications in Go with most of the burden of arguments parsing and validation placed on the framework instead of the user. To create a new application, initialize an app with cli.App. Specify a name and a brief description for the application: To attach code to execute when the app is launched, assign a function to the Action field: To assign a version to the application, use Version method and specify the flags that will be used to invoke the version command: Finally, in the main func, call Run passing in the arguments for parsing: To add one or more command line options (also known as flags), use one of the short-form StringOpt, StringsOpt, IntOpt, IntsOpt, Float64Opt, Floats64Opt, or BoolOpt methods on App (or Cmd if adding flags to a command or a subcommand). For example, to add a boolean flag to the cp command that specifies recursive mode, use the following: or: The first version returns a new pointer to a bool value which will be populated when the app is run, whereas the second version will populate a pointer to an existing variable you specify. The option name(s) is a space separated list of names (without the dashes). The one letter names can then be called with a single dash (short option, -R), the others with two dashes (long options, --recursive). You also specify the default value for the option if it is not supplied by the user. The last parameter is the description to be shown in help messages. There is also a second set of methods on App called String, Strings, Int, Ints, and Bool, which accept a long-form struct of the type: cli.StringOpt, cli.StringsOpt, cli.IntOpt, cli.IntsOpt, cli.Float64Opt, cli.Floats64Opt, cli.BoolOpt. The struct describes the option and allows the use of additional features not available in the short-form methods described above: Or: The first version returns a new pointer to a value which will be populated when the app is run, whereas the second version will populate a pointer to an existing variable you specify. Two features, EnvVar and SetByUser, can be defined in the long-form struct method. EnvVar is a space separated list of environment variables used to initialize the option if a value is not provided by the user. When help messages are shown, the value of any environment variables will be displayed. SetByUser is a pointer to a boolean variable that is set to true if the user specified the value on the command line. This can be useful to determine if the value of the option was explicitly set by the user or set via the default value. You can only access the values stored in the pointers in the Action func, which is invoked after argument parsing has been completed. This precludes using the value of one option as the default value of another. On the command line, the following syntaxes are supported when specifying options. Boolean options: String, int and float options: Slice options (StringsOpt, IntsOpt, Floats64Opt) where option is repeated to accumulate values in a slice: To add one or more command line arguments (not prefixed by dashes), use one of the short-form StringArg, StringsArg, IntArg, IntsArg, Float64Arg, Floats64Arg, or BoolArg methods on App (or Cmd if adding arguments to a command or subcommand). For example, to add two string arguments to our cp command, use the following calls: Or: The first version returns a new pointer to a value which will be populated when the app is run, whereas the second version will populate a pointer to an existing variable you specify. You then specify the argument as will be displayed in help messages. Argument names must be specified as all uppercase. The next parameter is the default value for the argument if it is not supplied. And the last is the description to be shown in help messages. There is also a second set of methods on App called String, Strings, Int, Ints, Float64, Floats64 and Bool, which accept a long-form struct of the type: cli.StringArg, cli.StringsArg, cli.IntArg, cli.IntsArg, cli.BoolArg. The struct describes the arguments and allows the use of additional features not available in the short-form methods described above: Or: The first version returns a new pointer to a value which will be populated when the app is run, whereas the second version will populate a pointer to an existing variable you specify. Two features, EnvVar and SetByUser, can be defined in the long-form struct method. EnvVar is a space separated list of environment variables used to initialize the argument if a value is not provided by the user. When help messages are shown, the value of any environment variables will be displayed. SetByUser is a pointer to a boolean variable that is set to true if the user specified the value on the command line. This can be useful to determine if the value of the argument was explicitly set by the user or set via the default value. You can only access the values stored in the pointers in the Action func, which is invoked after argument parsing has been completed. This precludes using the value of one argument as the default value of another. The -- operator marks the end of command line options. Everything that follows will be treated as an argument, even if starts with a dash. For example, the standard POSIX touch command, which takes a filename as an argument (and possibly other options that we'll ignore here), could be defined as: If we try to create a file named "-f" via our touch command: It will fail because the -f will be parsed as an option, not as an argument. The fix is to insert -- after all flags have been specified, so the remaining arguments are parsed as arguments instead of options as follows: This ensures the -f is parsed as an argument instead of a flag named f. This package supports nesting of commands and subcommands. Declare a top-level command by calling the Command func on the top-level App struct. For example, the following creates an application called docker that will have one command called run: The first argument is the name of the command the user will specify on the command line to invoke this command. The second argument is the description of the command shown in help messages. And, the last argument is a CmdInitializer, which is a function that receives a pointer to a Cmd struct representing the command. Within this function, define the options and arguments for the command by calling the same methods as you would with top-level App struct (BoolOpt, StringArg, ...). To execute code when the command is invoked, assign a function to the Action field of the Cmd struct. Within that function, you can safely refer to the options and arguments as command line parsing will be completed at the time the function is invoked: Optionally, to provide a more extensive description of the command, assign a string to LongDesc, which is displayed when a user invokes --help. A LongDesc can be provided for Cmds as well as the top-level App: Subcommands can be added by calling Command on the Cmd struct. They can by defined to any depth if needed: Command and subcommand aliases are also supported. To define one or more aliases, specify a space-separated list of strings to the first argument of Command: With the command structure defined above, users can invoke the app in a variety of ways: Commands can be hidden in the help messages. This can prove useful to deprecate a command so that it does not appear to new users in the help, but still exists to not break existing scripts. To hide a command, set the Hidden field to true: As a convenience, to assign an Action to a func with no arguments, use ActionCommand when defining the Command. For example, the following two statements are equivalent: Please note that options, arguments, specs, and long descriptions cannot be provided when using ActionCommand. This is intended for very simple command invocations that take no arguments. Finally, as a side-note, it may seem a bit weird that this package uses a function to initialize a command instead of simply returning a command struct. The motivation behind this API decision is scoping: as with the standard flag package, adding an option or an argument returns a pointer to a value which will be populated when the app is run. Since you'll want to store these pointers in variables, and to avoid having dozens of them in the same scope (the main func for example or as global variables), this API was specifically tailored to take a func parameter (called CmdInitializer), which accepts the command struct. With this design, the command's specific variables are limited in scope to this function. Interceptors, or hooks, can be defined to be executed before and after a command or when any of its subcommands are executed. For example, the following app defines multiple commands as well as a global flag which toggles verbosity: Instead of duplicating the check for the verbose flag and setting the debug level in every command (and its sub-commands), a Before interceptor can be set on the top-level App instead: Whenever a valid command is called by the user, all the Before interceptors defined on the app and the intermediate commands will be called, in order from the root to the leaf. Similarly, to execute a hook after a command has been called, e.g. to cleanup resources allocated in Before interceptors, simply set the After field of the App struct or any other Command. After interceptors will be called, in order, from the leaf up to the root (the opposite order of the Before interceptors). The following diagram shows when and in which order multiple Before and After interceptors are executed: To exit the application, use cli.Exit function, which accepts an exit code and exits the app with the provided code. It is important to use cli.Exit instead of os.Exit as the former ensures that all of the After interceptors are executed before exiting. An App or Command's invocation syntax can be customized using spec strings. This can be useful to indicate that an argument is optional or that two options are mutually exclusive. The spec string is one of the key differentiators between this package and other CLI packages as it allows the developer to express usage in a simple, familiar, yet concise grammar. To define option and argument usage for the top-level App, assign a spec string to the App's Spec field: Likewise, to define option and argument usage for a command or subcommand, assign a spec string to the Command's Spec field: The spec syntax is mostly based on the conventions used in POSIX command line applications (help messages and man pages). This syntax is described in full below. If a user invokes the app or command with the incorrect syntax, the app terminates with a help message showing the proper invocation. The remainder of this section describes the many features and capabilities of the spec string grammar. Options can use both short and long option names in spec strings. In the example below, the option is mandatory and must be provided. Any options referenced in a spec string MUST be explicitly declared, otherwise this package will panic. I.e. for each item in the spec string, a corresponding *Opt or *Arg is required: Arguments are specified with all-uppercased words. In the example below, both SRC and DST must be provided by the user (two arguments). Like options, any argument referenced in a spec string MUST be explicitly declared, otherwise this package will panic: With the exception of options, the order of the elements in a spec string is respected and enforced when command line arguments are parsed. In the example below, consecutive options (-f and -g) are parsed regardless of the order they are specified (both "-f=5 -g=6" and "-g=6 -f=5" are valid). Order between options and arguments is significant (-f and -g must appear before the SRC argument). The same holds true for arguments, where SRC must appear before DST: Optionality of options and arguments is specified in a spec string by enclosing the item in square brackets []. If the user does not provide an optional value, the app will use the default value specified when the argument was defined. In the example below, if -x is not provided, heapSize will default to 1024: Choice between two or more items is specified in a spec string by separating each choice with the | operator. Choices are mutually exclusive. In the examples below, only a single choice can be provided by the user otherwise the app will terminate displaying a help message on proper usage: Repetition of options and arguments is specified in a spec string with the ... postfix operator to mark an item as repeatable. Both options and arguments support repitition. In the example below, users may invoke the command with multiple -e options and multiple SRC arguments: Grouping of options and arguments is specified in a spec string with parenthesis. When combined with the choice | and repetition ... operators, complex syntaxes can be created. The parenthesis in the example below indicate a repeatable sequence of a -e option followed by an argument, and that is mutually exclusive to a choice between -x and -y options. Option groups, or option folding, are a shorthand method to declaring a choice between multiple options. I.e. any combination of the listed options in any order with at least one option selected. The following two statements are equivalent: Option groups are typically used in conjunction with optionality [] operators. I.e. any combination of the listed options in any order or none at all. The following two statements are equivalent: All of the options can be specified using a special syntax: [OPTIONS]. This is a special token in the spec string (not optionality and not an argument called OPTIONS). It is equivalent to an optional repeatable choice between all the available options. For example, if an app or a command declares 4 options a, b, c and d, then the following two statements are equivalent: Inline option values are specified in the spec string with the =<some-text> notation immediately following an option (long or short form) to provide users with an inline description or value. The actual inline values are ignored by the spec parser as they exist only to provide a contextual hint to the user. In the example below, "absolute-path" and "in seconds" are ignored by the parser: The -- operator can be used to automatically treat everything following it as arguments. In other words, placing a -- in the spec string automatically inserts a -- in the same position in the program call arguments. This lets you write programs such as the POSIX time utility for example: Below is the full EBNF grammar for the Specs language: By combining a few of these building blocks together (while respecting the grammar above), powerful and sophisticated validation constraints can be created in a simple and concise manner without having to define in code. This is one of the key differentiators between this package and other CLI packages. Validation of usage is handled entirely by the package through the spec string. Behind the scenes, this package parses the spec string and constructs a finite state machine used to parse the command line arguments. It also handles backtracking, which allows it to handle tricky cases, or what I like to call "the cp test": Without backtracking, this deceptively simple spec string cannot be parsed correctly. For instance, docopt can't handle this case, whereas this package does. By default an auto-generated spec string is created for the app and every command unless a spec string has been set by the user. This can simplify use of the package even further for simple syntaxes. The following logic is used to create an auto-generated spec string: 1) start with an empty spec string, 2) if at least one option was declared, append "[OPTIONS]" to the spec string, and 3) for each declared argument, append it, in the order of declaration, to the spec string. For example, given this command declaration: The auto-generated spec string, which should suffice for simple cases, would be: If additional constraints are required, the spec string must be set explicitly using the grammar documented above. By default, the following types are supported for options and arguments: bool, string, int, float64, strings (slice of strings), ints (slice of ints) and floats64 (slice of float64). You can, however, extend this package to handle other types, e.g. time.Duration, float64, or even your own struct types. To define your own custom type, you must implement the flag.Value interface for your custom type, and then declare the option or argument using VarOpt or VarArg respectively if using the short-form methods. If using the long-form struct, then use Var instead. The following example defines a custom type for a duration. It defines a duration argument that users will be able to invoke with strings in the form of "1h31m42s": To make a custom type to behave as a boolean option, i.e. doesn't take a value, it must implement the IsBoolFlag method that returns true: To make a custom type behave as a multi-valued option or argument, i.e. takes multiple values, it must implement the Clear method, which is called whenever the values list needs to be cleared, e.g. when the value was initially populated from an environment variable, and then explicitly set from the CLI: To hide the default value of a custom type, it must implement the IsDefault method that returns a boolean. The help message generator will use the return value to decide whether or not to display the default value to users:

Package pagerduty is a Go API client for both the PagerDuty v2 REST and Events API. Most methods should be implemented, and it's recommended to use the WithContext variant of each method and to specify a context with a timeout. To debug responses from the API, you can instruct the client to capture the last response from the API. Please see the documentation for the SetDebugFlag() and LastAPIResponse() methods for more details.

Package xray provides the API client, operations, and parameter types for AWS X-Ray. Amazon Web Services X-Ray provides APIs for managing debug traces and retrieving service maps and other data created by processing those traces.

Package sqlite is a sql/database driver using a CGo-free port of the C SQLite3 library. SQLite is an in-process implementation of a self-contained, serverless, zero-configuration, transactional SQL database engine. When you import this package you should use in your go.mod file the exact same version of modernc.org/libc as seen in the go.mod file of this repository. See the discussion at https://gitlab.com/cznic/sqlite/-/issues/177 for more details. This project is sponsored by Schleibinger Geräte Teubert u. Greim GmbH by allowing one of the maintainers to work on it also in office hours. These combinations of GOOS and GOARCH are currently supported Builder results available at: https://modern-c.appspot.com/-/builder/?importpath=modernc.org%2fsqlite 2024-11-16 v1.34.0: Implement ResetSession and IsValid methods in connection 2024-07-22 v1.31.0: Support windows/386. 2024-06-04 v1.30.0: Upgrade to SQLite 3.46.0, release notes at https://sqlite.org/releaselog/3_46_0.html. 2024-02-13 v1.29.0: Upgrade to SQLite 3.45.1, release notes at https://sqlite.org/releaselog/3_45_1.html. 2023-12-14: v1.28.0: Add (*Driver).RegisterConnectionHook, ConnectionHookFn, ExecQuerierContext, RegisterConnectionHook. 2023-08-03 v1.25.0: enable SQLITE_ENABLE_DBSTAT_VTAB. 2023-07-11 v1.24.0: Add (*conn).{Serialize,Deserialize,NewBackup,NewRestore} methods, add Backup type. 2023-06-01 v1.23.0: Allow registering aggregate functions. 2023-04-22 v1.22.0: Support linux/s390x. 2023-02-23 v1.21.0: Upgrade to SQLite 3.41.0, release notes at https://sqlite.org/releaselog/3_41_0.html. 2022-11-28 v1.20.0: Support linux/ppc64le. 2022-09-16 v1.19.0: Support frebsd/arm64. 2022-07-26 v1.18.0: Add support for Go fs.FS based SQLite virtual filesystems, see function New in modernc.org/sqlite/vfs and/or TestVFS in all_test.go 2022-04-24 v1.17.0: Support windows/arm64. 2022-04-04 v1.16.0: Support scalar application defined functions written in Go. See https://www.sqlite.org/appfunc.html 2022-03-13 v1.15.0: Support linux/riscv64. 2021-11-13 v1.14.0: Support windows/amd64. This target had previously only experimental status because of a now resolved memory leak. 2021-09-07 v1.13.0: Support freebsd/amd64. 2021-06-23 v1.11.0: Upgrade to use sqlite 3.36.0, release notes at https://www.sqlite.org/releaselog/3_36_0.html. 2021-05-06 v1.10.6: Fixes a memory corruption issue (https://gitlab.com/cznic/sqlite/-/issues/53). Versions since v1.8.6 were affected and should be updated to v1.10.6. 2021-03-14 v1.10.0: Update to use sqlite 3.35.0, release notes at https://www.sqlite.org/releaselog/3_35_0.html. 2021-03-11 v1.9.0: Support darwin/arm64. 2021-01-08 v1.8.0: Support darwin/amd64. 2020-09-13 v1.7.0: Support linux/arm and linux/arm64. 2020-09-08 v1.6.0: Support linux/386. 2020-09-03 v1.5.0: This project is now completely CGo-free, including the Tcl tests. 2020-08-26 v1.4.0: First stable release for linux/amd64. The database/sql driver and its tests are CGo free. Tests of the translated sqlite3.c library still require CGo. 2020-07-26 v1.4.0-beta1: The project has reached beta status while supporting linux/amd64 only at the moment. The 'extraquick' Tcl testsuite reports 2019-12-28 v1.2.0-alpha.3: Third alpha fixes issue #19. 2019-12-26 v1.1.0-alpha.2: Second alpha release adds support for accessing a database concurrently by multiple goroutines and/or processes. v1.1.0 is now considered feature-complete. Next planed release should be a beta with a proper test suite. 2019-12-18 v1.1.0-alpha.1: First alpha release using the new cc/v3, gocc, qbe toolchain. Some primitive tests pass on linux_{amd64,386}. Not yet safe for concurrent access by multiple goroutines. Next alpha release is planed to arrive before the end of this year. 2017-06-10: Windows/Intel no more uses the VM (thanks Steffen Butzer). 2017-06-05 Linux/Intel no more uses the VM (cznic/virtual). To access a Sqlite database do something like A comma separated list of options can be passed to `go generate` via the environment variable GO_GENERATE. Some useful options include for example: To create a debug/development version, issue for example: Note: To run `go generate` you need to have modernc.org/ccgo/v3 installed. This is an example of how to use the debug logs in modernc.org/libc when hunting a bug. The /tmp/libc.log file is created as requested. No useful messages there because none are enabled in libc. Let's try to enable Xwrite as an example. We need to tell the Go build system to use our local, patched/debug libc: And run the test again: See https://sqlite.org/docs.html

Package gosnowflake is a pure Go Snowflake driver for the database/sql package. Clients can use the database/sql package directly. For example: Use the Open() function to create a database handle with connection parameters: The Go Snowflake Driver supports the following connection syntaxes (or data source name (DSN) formats): where all parameters must be escaped or use Config and DSN to construct a DSN string. For information about account identifiers, see the Snowflake documentation (https://docs.snowflake.com/en/user-guide/admin-account-identifier.html). The following example opens a database handle with the Snowflake account named "my_account" under the organization named "my_organization", where the username is "jsmith", password is "mypassword", database is "mydb", schema is "testschema", and warehouse is "mywh": The connection string (DSN) can contain both connection parameters (described below) and session parameters (https://docs.snowflake.com/en/sql-reference/parameters.html). The following connection parameters are supported: account <string>: Specifies your Snowflake account, where "<string>" is the account identifier assigned to your account by Snowflake. For information about account identifiers, see the Snowflake documentation (https://docs.snowflake.com/en/user-guide/admin-account-identifier.html). If you are using a global URL, then append the connection group and ".global" (e.g. "<account_identifier>-<connection_group>.global"). The account identifier and the connection group are separated by a dash ("-"), as shown above. This parameter is optional if your account identifier is specified after the "@" character in the connection string. region <string>: DEPRECATED. You may specify a region, such as "eu-central-1", with this parameter. However, since this parameter is deprecated, it is best to specify the region as part of the account parameter. For details, see the description of the account parameter. database: Specifies the database to use by default in the client session (can be changed after login). schema: Specifies the database schema to use by default in the client session (can be changed after login). warehouse: Specifies the virtual warehouse to use by default for queries, loading, etc. in the client session (can be changed after login). role: Specifies the role to use by default for accessing Snowflake objects in the client session (can be changed after login). passcode: Specifies the passcode provided by Duo when using multi-factor authentication (MFA) for login. passcodeInPassword: false by default. Set to true if the MFA passcode is embedded in the login password. Appends the MFA passcode to the end of the password. loginTimeout: Specifies the timeout, in seconds, for login. The default is 60 seconds. The login request gives up after the timeout length if the HTTP response is success. requestTimeout: Specifies the timeout, in seconds, for a query to complete. 0 (zero) specifies that the driver should wait indefinitely. The default is 0 seconds. The query request gives up after the timeout length if the HTTP response is success. authenticator: Specifies the authenticator to use for authenticating user credentials: To use the internal Snowflake authenticator, specify snowflake (Default). If you want to cache your MFA logins, use AuthTypeUsernamePasswordMFA authenticator. To authenticate through Okta, specify https://<okta_account_name>.okta.com (URL prefix for Okta). To authenticate using your IDP via a browser, specify externalbrowser. To authenticate via OAuth, specify oauth and provide an OAuth Access Token (see the token parameter below). application: Identifies your application to Snowflake Support. disableOCSPChecks: false by default. Set to true to bypass the Online Certificate Status Protocol (OCSP) certificate revocation check. IMPORTANT: Change the default value for testing or emergency situations only. insecureMode: deprecated. Use disableOCSPChecks instead. token: a token that can be used to authenticate. Should be used in conjunction with the "oauth" authenticator. client_session_keep_alive: Set to true have a heartbeat in the background every hour to keep the connection alive such that the connection session will never expire. Care should be taken in using this option as it opens up the access forever as long as the process is alive. ocspFailOpen: true by default. Set to false to make OCSP check fail closed mode. validateDefaultParameters: true by default. Set to false to disable checks on existence and privileges check for Database, Schema, Warehouse and Role when setting up the connection tracing: Specifies the logging level to be used. Set to error by default. Valid values are trace, debug, info, print, warning, error, fatal, panic. disableQueryContextCache: disables parsing of query context returned from server and resending it to server as well. Default value is false. clientConfigFile: specifies the location of the client configuration json file. In this file you can configure Easy Logging feature. disableSamlURLCheck: disables the SAML URL check. Default value is false. All other parameters are interpreted as session parameters (https://docs.snowflake.com/en/sql-reference/parameters.html). For example, the TIMESTAMP_OUTPUT_FORMAT session parameter can be set by adding: A complete connection string looks similar to the following: Session-level parameters can also be set by using the SQL command "ALTER SESSION" (https://docs.snowflake.com/en/sql-reference/sql/alter-session.html). Alternatively, use OpenWithConfig() function to create a database handle with the specified Config. # Connection Config You can also connect to your warehouse using the connection config. The dbSql library states that when you want to take advantage of driver-specific connection features that aren’t available in a connection string. Each driver supports its own set of connection properties, often providing ways to customize the connection request specific to the DBMS For example: If you are using this method, you dont need to pass a driver name to specify the driver type in which you are looking to connect. Since the driver name is not needed, you can optionally bypass driver registration on startup. To do this, set `GOSNOWFLAKE_SKIP_REGISTERATION` in your environment. This is useful you wish to register multiple verions of the driver. Note: GOSNOWFLAKE_SKIP_REGISTERATION should not be used if sql.Open() is used as the method to connect to the server, as sql.Open will require registration so it can map the driver name to the driver type, which in this case is "snowflake" and SnowflakeDriver{}. You can load the connnection configuration with .toml file format. With two environment variables SNOWFLAKE_HOME(connections.toml file directory) SNOWFLAKE_DEFAULT_CONNECTION_NAME(DSN name), the driver will search the config file and load the connection. You can find how to use this connection way at ./cmd/tomlfileconnection or Snowflake doc: https://docs.snowflake.com/en/developer-guide/snowflake-cli-v2/connecting/specify-credentials The Go Snowflake Driver honors the environment variables HTTP_PROXY, HTTPS_PROXY and NO_PROXY for the forward proxy setting. NO_PROXY specifies which hostname endings should be allowed to bypass the proxy server, e.g. no_proxy=.amazonaws.com means that Amazon S3 access does not need to go through the proxy. NO_PROXY does not support wildcards. Each value specified should be one of the following: The end of a hostname (or a complete hostname), for example: ".amazonaws.com" or "xy12345.snowflakecomputing.com". An IP address, for example "192.196.1.15". If more than one value is specified, values should be separated by commas, for example: By default, the driver's builtin logger is exposing logrus's FieldLogger and default at INFO level. Users can use SetLogger in driver.go to set a customized logger for gosnowflake package. In order to enable debug logging for the driver, user could use SetLogLevel("debug") in SFLogger interface as shown in demo code at cmd/logger.go. To redirect the logs SFlogger.SetOutput method could do the work. If you want to define S3 client logging, override S3LoggingMode variable using configuration: https://pkg.go.dev/github.com/aws/aws-sdk-go-v2/aws#ClientLogMode Example: A custom query tag can be set in the context. Each query run with this context will include the custom query tag as metadata that will appear in the Query Tag column in the Query History log. For example: A specific query request ID can be set in the context and will be passed through in place of the default randomized request ID. For example: If you need query ID for your query you have to use raw connection. For queries: ``` ``` For execs: ``` ``` The result of your query can be retrieved by setting the query ID in the WithFetchResultByID context. ``` ``` From 0.5.0, a signal handling responsibility has moved to the applications. If you want to cancel a query/command by Ctrl+C, add a os.Interrupt trap in context to execute methods that can take the context parameter (e.g. QueryContext, ExecContext). See cmd/selectmany.go for the full example. The Go Snowflake Driver now supports the Arrow data format for data transfers between Snowflake and the Golang client. The Arrow data format avoids extra conversions between binary and textual representations of the data. The Arrow data format can improve performance and reduce memory consumption in clients. Snowflake continues to support the JSON data format. The data format is controlled by the session-level parameter GO_QUERY_RESULT_FORMAT. To use JSON format, execute: The valid values for the parameter are: If the user attempts to set the parameter to an invalid value, an error is returned. The parameter name and the parameter value are case-insensitive. This parameter can be set only at the session level. Usage notes: The Arrow data format reduces rounding errors in floating point numbers. You might see slightly different values for floating point numbers when using Arrow format than when using JSON format. In order to take advantage of the increased precision, you must pass in the context.Context object provided by the WithHigherPrecision function when querying. Traditionally, the rows.Scan() method returned a string when a variable of types interface was passed in. Turning on the flag ENABLE_HIGHER_PRECISION via WithHigherPrecision will return the natural, expected data type as well. For some numeric data types, the driver can retrieve larger values when using the Arrow format than when using the JSON format. For example, using Arrow format allows the full range of SQL NUMERIC(38,0) values to be retrieved, while using JSON format allows only values in the range supported by the Golang int64 data type. Users should ensure that Golang variables are declared using the appropriate data type for the full range of values contained in the column. For an example, see below. When using the Arrow format, the driver supports more Golang data types and more ways to convert SQL values to those Golang data types. The table below lists the supported Snowflake SQL data types and the corresponding Golang data types. The columns are: The SQL data type. The default Golang data type that is returned when you use snowflakeRows.Scan() to read data from Arrow data format via an interface{}. The possible Golang data types that can be returned when you use snowflakeRows.Scan() to read data from Arrow data format directly. The default Golang data type that is returned when you use snowflakeRows.Scan() to read data from JSON data format via an interface{}. (All returned values are strings.) The standard Golang data type that is returned when you use snowflakeRows.Scan() to read data from JSON data format directly. Go Data Types for Scan() =================================================================================================================== | ARROW | JSON =================================================================================================================== SQL Data Type | Default Go Data Type | Supported Go Data | Default Go Data Type | Supported Go Data | for Scan() interface{} | Types for Scan() | for Scan() interface{} | Types for Scan() =================================================================================================================== BOOLEAN | bool | string | bool ------------------------------------------------------------------------------------------------------------------- VARCHAR | string | string ------------------------------------------------------------------------------------------------------------------- DOUBLE | float32, float64 [1] , [2] | string | float32, float64 ------------------------------------------------------------------------------------------------------------------- INTEGER that | int, int8, int16, int32, int64 | string | int, int8, int16, fits in int64 | [1] , [2] | | int32, int64 ------------------------------------------------------------------------------------------------------------------- INTEGER that doesn't | int, int8, int16, int32, int64, *big.Int | string | error fit in int64 | [1] , [2] , [3] , [4] | ------------------------------------------------------------------------------------------------------------------- NUMBER(P, S) | float32, float64, *big.Float | string | float32, float64 where S > 0 | [1] , [2] , [3] , [5] | ------------------------------------------------------------------------------------------------------------------- DATE | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIME | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_LTZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_NTZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- TIMESTAMP_TZ | time.Time | string | time.Time ------------------------------------------------------------------------------------------------------------------- BINARY | []byte | string | []byte ------------------------------------------------------------------------------------------------------------------- ARRAY [6] | string / array | string / array ------------------------------------------------------------------------------------------------------------------- OBJECT [6] | string / struct | string / struct ------------------------------------------------------------------------------------------------------------------- VARIANT | string | string ------------------------------------------------------------------------------------------------------------------- MAP | map | map [1] Converting from a higher precision data type to a lower precision data type via the snowflakeRows.Scan() method can lose low bits (lose precision), lose high bits (completely change the value), or result in error. [2] Attempting to convert from a higher precision data type to a lower precision data type via interface{} causes an error. [3] Higher precision data types like *big.Int and *big.Float can be accessed by querying with a context returned by WithHigherPrecision(). [4] You cannot directly Scan() into the alternative data types via snowflakeRows.Scan(), but can convert to those data types by using .Int64()/.String()/.Uint64() methods. For an example, see below. [5] You cannot directly Scan() into the alternative data types via snowflakeRows.Scan(), but can convert to those data types by using .Float32()/.String()/.Float64() methods. For an example, see below. [6] Arrays and objects can be either semistructured or structured, see more info in section below. Note: SQL NULL values are converted to Golang nil values, and vice-versa. Snowflake supports two flavours of "structured data" - semistructured and structured. Semistructured types are variants, objects and arrays without schema. When data is fetched, it's represented as strings and the client is responsible for its interpretation. Example table definition: The data not have any corresponding schema, so values in table may be slightly different. Semistuctured variants, objects and arrays are always represented as strings for scanning: When inserting, a marker indicating correct type must be used, for example: Structured types differentiate from semistructured types by having specific schema. In all rows of the table, values must conform to this schema. Example table definition: To retrieve structured objects, follow these steps: 1. Create a struct implementing sql.Scanner interface, example: a) b) Automatic scan goes through all fields in a struct and read object fields. Struct fields have to be public. Embedded structs have to be pointers. Matching name is built using struct field name with first letter lowercase. Additionally, `sf` tag can be added: - first value is always a name of a field in an SQL object - additionally `ignore` parameter can be passed to omit this field 2. Use WithStructuredTypesEnabled context while querying data. 3. Use it in regular scan: See StructuredObject for all available operations including null support, embedding nested structs, etc. Retrieving array of simple types works exactly the same like normal values - using Scan function. You can use WithMapValuesNullable and WithArrayValuesNullable contexts to handle null values in, respectively, maps and arrays of simple types in the database. In that case, sql null types will be used: If you want to scan array of structs, you have to use a helper function ScanArrayOfScanners: Retrieving structured maps is very similar to retrieving arrays: To bind structured objects use: 1. Create a type which implements a StructuredObjectWriter interface, example: a) b) 2. Use an instance as regular bind. 3. If you need to bind nil value, use special syntax: Binding structured arrays are like any other parameter. The only difference is - if you want to insert empty array (not nil but empty), you have to use: The following example shows how to retrieve very large values using the math/big package. This example retrieves a large INTEGER value to an interface and then extracts a big.Int value from that interface. If the value fits into an int64, then the code also copies the value to a variable of type int64. Note that a context that enables higher precision must be passed in with the query. If the variable named "rows" is known to contain a big.Int, then you can use the following instead of scanning into an interface and then converting to a big.Int: If the variable named "rows" contains a big.Int, then each of the following fails: Similar code and rules also apply to big.Float values. If you are not sure what data type will be returned, you can use code similar to the following to check the data type of the returned value: You can retrieve data in a columnar format similar to the format a server returns, without transposing them to rows. When working with the arrow columnar format in go driver, ArrowBatch structs are used. These are structs mostly corresponding to data chunks received from the backend. They allow for access to specific arrow.Record structs. An ArrowBatch can exist in a state where the underlying data has not yet been loaded. The data is downloaded and translated only on demand. Translation options are retrieved from a context.Context interface, which is either passed from query context or set by the user using WithContext(ctx) method. In order to access them you must use `WithArrowBatches` context, similar to the following: This returns []*ArrowBatch. ArrowBatch functions: GetRowCount(): Returns the number of rows in the ArrowBatch. Note that this returns 0 if the data has not yet been loaded, irrespective of it’s actual size. WithContext(ctx context.Context): Sets the context of the ArrowBatch to the one provided. Note that the context will not retroactively apply to data that has already been downloaded. For example: will produce the same result in records1 and records2, irrespective of the newly provided ctx. Context worth noting are: -WithArrowBatchesTimestampOption -WithHigherPrecision -WithArrowBatchesUtf8Validation described in more detail later. Fetch(): Returns the underlying records as *[]arrow.Record. When this function is called, the ArrowBatch checks whether the underlying data has already been loaded, and downloads it if not. Limitations: How to handle timestamps in Arrow batches: Snowflake returns timestamps natively (from backend to driver) in multiple formats. The Arrow timestamp is an 8-byte data type, which is insufficient to handle the larger date and time ranges used by Snowflake. Also, Snowflake supports 0-9 (nanosecond) digit precision for seconds, while Arrow supports only 3 (millisecond), 6 (microsecond), an 9 (nanosecond) precision. Consequently, Snowflake uses a custom timestamp format in Arrow, which differs on timestamp type and precision. If you want to use timestamps in Arrow batches, you have two options: How to handle invalid UTF-8 characters in Arrow batches: Snowflake previously allowed users to upload data with invalid UTF-8 characters. Consequently, Arrow records containing string columns in Snowflake could include these invalid UTF-8 characters. However, according to the Arrow specifications (https://arrow.apache.org/docs/cpp/api/datatype.html and https://github.com/apache/arrow/blob/a03d957b5b8d0425f9d5b6c98b6ee1efa56a1248/go/arrow/datatype.go#L73-L74), Arrow string columns should only contain UTF-8 characters. To address this issue and prevent potential downstream disruptions, the context WithArrowBatchesUtf8Validation, is introduced. When enabled, this feature iterates through all values in string columns, identifying and replacing any invalid characters with `�`. This ensures that Arrow records conform to the UTF-8 standards, preventing validation failures in downstream services like the Rust Arrow library that impose strict validation checks. How to handle higher precision in Arrow batches: To preserve BigDecimal values within Arrow batches, use WithHigherPrecision. This offers two main benefits: it helps avoid precision loss and defers the conversion to upstream services. Alternatively, without this setting, all non-zero scale numbers will be converted to float64, potentially resulting in loss of precision. Zero-scale numbers (DECIMAL256, DECIMAL128) will be converted to int64, which could lead to overflow. WHen using NUMBERs with non zero scale, the value is returned as an integer type and a scale is provided in record metadata. Example. When we have a 123.45 value that comes from NUMBER(9, 4), it will be represented as 1234500 with scale equal to 4. It is a client responsibility to interpret it correctly. Also - see limitations section above. Binding allows a SQL statement to use a value that is stored in a Golang variable. Without binding, a SQL statement specifies values by specifying literals inside the statement. For example, the following statement uses the literal value “42“ in an UPDATE statement: With binding, you can execute a SQL statement that uses a value that is inside a variable. For example: The “?“ inside the “VALUES“ clause specifies that the SQL statement uses the value from a variable. Binding data that involves time zones can require special handling. For details, see the section titled "Timestamps with Time Zones". Version 1.6.23 (and later) of the driver takes advantage of sql.Null types which enables the proper handling of null parameters inside function calls, i.e.: The timestamp nullability had to be achieved by wrapping the sql.NullTime type as the Snowflake provides several date and time types which are mapped to single Go time.Time type: Version 1.3.9 (and later) of the Go Snowflake Driver supports the ability to bind an array variable to a parameter in a SQL INSERT statement. You can use this technique to insert multiple rows in a single batch. As an example, the following code inserts rows into a table that contains integer, float, boolean, and string columns. The example binds arrays to the parameters in the INSERT statement. If the array contains SQL NULL values, use slice []interface{}, which allows Golang nil values. This feature is available in version 1.6.12 (and later) of the driver. For example, For slices []interface{} containing time.Time values, a binding parameter flag is required for the preceding array variable in the Array() function. This feature is available in version 1.6.13 (and later) of the driver. For example, Note: For alternative ways to load data into the Snowflake database (including bulk loading using the COPY command), see Loading Data into Snowflake (https://docs.snowflake.com/en/user-guide-data-load.html). When you use array binding to insert a large number of values, the driver can improve performance by streaming the data (without creating files on the local machine) to a temporary stage for ingestion. The driver automatically does this when the number of values exceeds a threshold (no changes are needed to user code). In order for the driver to send the data to a temporary stage, the user must have the following privilege on the schema: If the user does not have this privilege, the driver falls back to sending the data with the query to the Snowflake database. In addition, the current database and schema for the session must be set. If these are not set, the CREATE TEMPORARY STAGE command executed by the driver can fail with the following error: For alternative ways to load data into the Snowflake database (including bulk loading using the COPY command), see Loading Data into Snowflake (https://docs.snowflake.com/en/user-guide-data-load.html). Go's database/sql package supports the ability to bind a parameter in a SQL statement to a time.Time variable. However, when the client binds data to send to the server, the driver cannot determine the correct Snowflake date/timestamp data type to associate with the binding parameter. For example: To resolve this issue, a binding parameter flag is introduced that associates any subsequent time.Time type to the DATE, TIME, TIMESTAMP_LTZ, TIMESTAMP_NTZ or BINARY data type. The above example could be rewritten as follows: The driver fetches TIMESTAMP_TZ (timestamp with time zone) data using the offset-based Location types, which represent a collection of time offsets in use in a geographical area, such as CET (Central European Time) or UTC (Coordinated Universal Time). The offset-based Location data is generated and cached when a Go Snowflake Driver application starts, and if the given offset is not in the cache, it is generated dynamically. Currently, Snowflake does not support the name-based Location types (e.g. "America/Los_Angeles"). For more information about Location types, see the Go documentation for https://golang.org/pkg/time/#Location. Internally, this feature leverages the []byte data type. As a result, BINARY data cannot be bound without the binding parameter flag. In the following example, sf is an alias for the gosnowflake package: The driver directly downloads a result set from the cloud storage if the size is large. It is required to shift workloads from the Snowflake database to the clients for scale. The download takes place by goroutine named "Chunk Downloader" asynchronously so that the driver can fetch the next result set while the application can consume the current result set. The application may change the number of result set chunk downloader if required. Note this does not help reduce memory footprint by itself. Consider Custom JSON Decoder. Custom JSON Decoder for Parsing Result Set (Experimental) The application may have the driver use a custom JSON decoder that incrementally parses the result set as follows. This option will reduce the memory footprint to half or even quarter, but it can significantly degrade the performance depending on the environment. The test cases running on Travis Ubuntu box show five times less memory footprint while four times slower. Be cautious when using the option. The Go Snowflake Driver supports JWT (JSON Web Token) authentication. To enable this feature, construct the DSN with fields "authenticator=SNOWFLAKE_JWT&privateKey=<your_private_key>", or using a Config structure specifying: The <your_private_key> should be a base64 URL encoded PKCS8 rsa private key string. One way to encode a byte slice to URL base 64 URL format is through the base64.URLEncoding.EncodeToString() function. On the server side, you can alter the public key with the SQL command: The <your_public_key> should be a base64 Standard encoded PKI public key string. One way to encode a byte slice to base 64 Standard format is through the base64.StdEncoding.EncodeToString() function. To generate the valid key pair, you can execute the following commands in the shell: Note: As of February 2020, Golang's official library does not support passcode-encrypted PKCS8 private key. For security purposes, Snowflake highly recommends that you store the passcode-encrypted private key on the disk and decrypt the key in your application using a library you trust. JWT tokens are recreated on each retry and they are valid (`exp` claim) for `jwtTimeout` seconds. Each retry timeout is configured by `jwtClientTimeout`. Retries are limited by total time of `loginTimeout`. The driver allows to authenticate using the external browser. When a connection is created, the driver will open the browser window and ask the user to sign in. To enable this feature, construct the DSN with field "authenticator=EXTERNALBROWSER" or using a Config structure with following Authenticator specified: The external browser authentication implements timeout mechanism. This prevents the driver from hanging interminably when browser window was closed, or not responding. Timeout defaults to 120s and can be changed through setting DSN field "externalBrowserTimeout=240" (time in seconds) or using a Config structure with following ExternalBrowserTimeout specified: This feature is available in version 1.3.8 or later of the driver. By default, Snowflake returns an error for queries issued with multiple statements. This restriction helps protect against SQL Injection attacks (https://en.wikipedia.org/wiki/SQL_injection). The multi-statement feature allows users skip this restriction and execute multiple SQL statements through a single Golang function call. However, this opens up the possibility for SQL injection, so it should be used carefully. The risk can be reduced by specifying the exact number of statements to be executed, which makes it more difficult to inject a statement by appending it. More details are below. The Go Snowflake Driver provides two functions that can execute multiple SQL statements in a single call: To compose a multi-statement query, simply create a string that contains all the queries, separated by semicolons, in the order in which the statements should be executed. To protect against SQL Injection attacks while using the multi-statement feature, pass a Context that specifies the number of statements in the string. For example: When multiple queries are executed by a single call to QueryContext(), multiple result sets are returned. After you process the first result set, get the next result set (for the next SQL statement) by calling NextResultSet(). The following pseudo-code shows how to process multiple result sets: The function db.ExecContext() returns a single result, which is the sum of the number of rows changed by each individual statement. For example, if your multi-statement query executed two UPDATE statements, each of which updated 10 rows, then the result returned would be 20. Individual row counts for individual statements are not available. The following code shows how to retrieve the result of a multi-statement query executed through db.ExecContext(): Note: Because a multi-statement ExecContext() returns a single value, you cannot detect offsetting errors. For example, suppose you expected the return value to be 20 because you expected each UPDATE statement to update 10 rows. If one UPDATE statement updated 15 rows and the other UPDATE statement updated only 5 rows, the total would still be 20. You would see no indication that the UPDATES had not functioned as expected. The ExecContext() function does not return an error if passed a query (e.g. a SELECT statement). However, it still returns only a single value, not a result set, so using it to execute queries (or a mix of queries and non-query statements) is impractical. The QueryContext() function does not return an error if passed non-query statements (e.g. DML). The function returns a result set for each statement, whether or not the statement is a query. For each non-query statement, the result set contains a single row that contains a single column; the value is the number of rows changed by the statement. If you want to execute a mix of query and non-query statements (e.g. a mix of SELECT and DML statements) in a multi-statement query, use QueryContext(). You can retrieve the result sets for the queries, and you can retrieve or ignore the row counts for the non-query statements. Note: PUT statements are not supported for multi-statement queries. If a SQL statement passed to ExecQuery() or QueryContext() fails to compile or execute, that statement is aborted, and subsequent statements are not executed. Any statements prior to the aborted statement are unaffected. For example, if the statements below are run as one multi-statement query, the multi-statement query fails on the third statement, and an exception is thrown. If you then query the contents of the table named "test", the values 1 and 2 would be present. When using the QueryContext() and ExecContext() functions, golang code can check for errors the usual way. For example: Preparing statements and using bind variables are also not supported for multi-statement queries. The Go Snowflake Driver supports asynchronous execution of SQL statements. Asynchronous execution allows you to start executing a statement and then retrieve the result later without being blocked while waiting. While waiting for the result of a SQL statement, you can perform other tasks, including executing other SQL statements. Most of the steps to execute an asynchronous query are the same as the steps to execute a synchronous query. However, there is an additional step, which is that you must call the WithAsyncMode() function to update your Context object to specify that asynchronous mode is enabled. In the code below, the call to "WithAsyncMode()" is specific to asynchronous mode. The rest of the code is compatible with both asynchronous mode and synchronous mode. The function db.QueryContext() returns an object of type snowflakeRows regardless of whether the query is synchronous or asynchronous. However: The call to the Next() function of snowflakeRows is always synchronous (i.e. blocking). If the query has not yet completed and the snowflakeRows object (named "rows" in this example) has not been filled in yet, then rows.Next() waits until the result set has been filled in. More generally, calls to any Golang SQL API function implemented in snowflakeRows or snowflakeResult are blocking calls, and wait if results are not yet available. (Examples of other synchronous calls include: snowflakeRows.Err(), snowflakeRows.Columns(), snowflakeRows.columnTypes(), snowflakeRows.Scan(), and snowflakeResult.RowsAffected().) Because the example code above executes only one query and no other activity, there is no significant difference in behavior between asynchronous and synchronous behavior. The differences become significant if, for example, you want to perform some other activity after the query starts and before it completes. The example code below starts a query, which run in the background, and then retrieves the results later. This example uses small SELECT statements that do not retrieve enough data to require asynchronous handling. However, the technique works for larger data sets, and for situations where the programmer might want to do other work after starting the queries and before retrieving the results. For a more elaborative example please see cmd/async/async.go The Go Snowflake Driver supports the PUT and GET commands. The PUT command copies a file from a local computer (the computer where the Golang client is running) to a stage on the cloud platform. The GET command copies data files from a stage on the cloud platform to a local computer. See the following for information on the syntax and supported parameters: Using PUT: The following example shows how to run a PUT command by passing a string to the db.Query() function: "<local_file>" should include the file path as well as the name. Snowflake recommends using an absolute path rather than a relative path. For example: Different client platforms (e.g. linux, Windows) have different path name conventions. Ensure that you specify path names appropriately. This is particularly important on Windows, which uses the backslash character as both an escape character and as a separator in path names. To send information from a stream (rather than a file) use code similar to the code below. (The ReplaceAll() function is needed on Windows to handle backslashes in the path to the file.) Note: PUT statements are not supported for multi-statement queries. Using GET: The following example shows how to run a GET command by passing a string to the db.Query() function: "<local_file>" should include the file path as well as the name. Snowflake recommends using an absolute path rather than a relative path. For example: To download a file into an in-memory stream (rather than a file) use code similar to the code below. Note: GET statements are not supported for multi-statement queries. Specifying temporary directory for encryption and compression: Putting and getting requires compression and/or encryption, which is done in the OS temporary directory. If you cannot use default temporary directory for your OS or you want to specify it yourself, you can use "tmpDirPath" DSN parameter. Remember, to encode slashes. Example: Using custom configuration for PUT/GET: If you want to override some default configuration options, you can use `WithFileTransferOptions` context. There are multiple config parameters including progress bars or compression.

Package capnp is a Cap'n Proto library for Go. https://capnproto.org/ Read the Getting Started guide for a tutorial on how to use this package. https://github.com/capnproto/go-capnproto2/wiki/Getting-Started capnpc-go provides the compiler backend for capnp. capnpc-go requires two annotations for all files: package and import. package is needed to know what package to place at the head of the generated file and what identifier to use when referring to the type from another package. import should be the fully qualified import path and is used to generate import statement from other packages and to detect when two types are in the same package. For example: For adding documentation comments to the generated code, there's the doc annotation. This annotation adds the comment to a struct, enum or field so that godoc will pick it up. For example: In Cap'n Proto, the unit of communication is a message. A message consists of one or more segments -- contiguous blocks of memory. This allows large messages to be split up and loaded independently or lazily. Typically you will use one segment per message. Logically, a message is organized in a tree of objects, with the root always being a struct (as opposed to a list or primitive). Messages can be read from and written to a stream. The Message and Segment types are the main types that application code will use from this package. The Message type has methods for marshaling and unmarshaling its segments to the wire format. If the application needs to read or write from a stream, it should use the Encoder and Decoder types. The type for a generic reference to a Cap'n Proto object is Ptr. A Ptr can refer to a struct, a list, or an interface. Ptr, Struct, List, and Interface (the pointer types) have value semantics and refer to data in a single segment. All of the pointer types have a notion of "valid". An invalid pointer will return the default value from any accessor and panic when any setter is called. In previous versions of this package, the Pointer interface was used instead of the Ptr struct. This interface and functions that use it are now deprecated. See https://github.com/capnproto/go-capnproto2/wiki/New-Ptr-Type for details about this API change. Data accessors and setters (i.e. struct primitive fields and list elements) do not return errors, but pointer accessors and setters do. There are a few reasons that a read or write of a pointer can fail, but the most common are bad pointers or allocation failures. For accessors, an invalid object will be returned in case of an error. Since Go doesn't have generics, wrapper types provide type safety on lists. This package provides lists of basic types, and capnpc-go generates list wrappers for named types. However, if you need to use deeper nesting of lists (e.g. List(List(UInt8))), you will need to use a PointerList and wrap the elements. For the following schema: capnpc-go will generate: For each group a typedef is created with a different method set for just the groups fields: generates the following: That way the following may be used to access a field in a group: Note that group accessors just convert the type and so have no overhead. Named unions are treated as a group with an inner unnamed union. Unnamed unions generate an enum Type_Which and a corresponding Which() function: generates the following: Which() should be checked before using the getters, and the default case must always be handled. Setters for single values will set the union discriminator as well as set the value. For voids in unions, there is a void setter that just sets the discriminator. For example: generates the following: Similarly, for groups in unions, there is a group setter that just sets the discriminator. This must be called before the group getter can be used to set values. For example: and in usage: capnpc-go generates enum values as constants. For example in the capnp file: In the generated capnp.go file: In addition an enum.String() function is generated that will convert the constants to a string for debugging or logging purposes. By default, the enum name is used as the tag value, but the tags can be customized with a $Go.tag or $Go.notag annotation. For example: In the generated go file: capnpc-go generates type-safe Client wrappers for interfaces. For parameter lists and result lists, structs are generated as described above with the names Interface_method_Params and Interface_method_Results, unless a single struct type is used. For example, for this interface: capnpc-go generates the following Go code (along with the structs Calculator_evaluate_Params and Calculator_evaluate_Results): capnpc-go also generates code to implement the interface: Since a single capability may want to implement many interfaces, you can use multiple *_Methods functions to build a single slice to send to NewServer. An example of combining the client/server code to communicate with a locally implemented Calculator: A note about message ordering: when implementing a server method, you are responsible for acknowledging delivery of a method call. Failure to do so can cause deadlocks. See the server.Ack function for more details.

Package cloud9 provides the API client, operations, and parameter types for AWS Cloud9. Cloud9 is a collection of tools that you can use to code, build, run, test, debug, and release software in the cloud. For more information about Cloud9, see the Cloud9 User Guide. Cloud9 supports these operations: CreateEnvironmentEC2 : Creates an Cloud9 development environment, launches an Amazon EC2 instance, and then connects from the instance to the environment. CreateEnvironmentMembership : Adds an environment member to an environment. DeleteEnvironment : Deletes an environment. If an Amazon EC2 instance is connected to the environment, also terminates the instance. DeleteEnvironmentMembership : Deletes an environment member from an environment. DescribeEnvironmentMemberships : Gets information about environment members for an environment. DescribeEnvironments : Gets information about environments. DescribeEnvironmentStatus : Gets status information for an environment. ListEnvironments : Gets a list of environment identifiers. ListTagsForResource : Gets the tags for an environment. TagResource : Adds tags to an environment. UntagResource : Removes tags from an environment. UpdateEnvironment : Changes the settings of an existing environment. UpdateEnvironmentMembership : Changes the settings of an existing environment member for an environment.

Package log is a modification of the log package included in the Go standard library, adding support for leveled logging, colorized output and JSON formatting. A predefined 'standard' logger which is accessible through helper functions Error[f|ln], Info[f|ln], Debug[f|ln], and Trace[f|ln]. The standard logger writes to standard error and prints the filename and linenumber of the call site of each logged message. Every log message is output on a separate line: if the message being printed does not end in a newline, the logger will add one.

Package q provides quick and dirty debugging output for tired programmers. q.Q() is a fast way to pretty-print variables. It's easier than typing fmt.Printf("%#v", whatever). The output will be colorized and nicely formatted. The output goes to $TMPDIR/q, away from the noise of stdout. q exports a single Q() function. This is how you use it:

This is the official Go SDK for Oracle Cloud Infrastructure Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#installing for installation instructions. Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring for configuration instructions. The following example shows how to get started with the SDK. The example belows creates an identityClient struct with the default configuration. It then utilizes the identityClient to list availability domains and prints them out to stdout More examples can be found in the SDK Github repo: https://github.com/oracle/oci-go-sdk/tree/master/example Optional fields are represented with the `mandatory:"false"` tag on input structs. The SDK will omit all optional fields that are nil when making requests. In the case of enum-type fields, the SDK will omit fields whose value is an empty string. The SDK uses pointers for primitive types in many input structs. To aid in the construction of such structs, the SDK provides functions that return a pointer for a given value. For example: The SDK exposes functionality that allows the user to customize any http request before is sent to the service. You can do so by setting the `Interceptor` field in any of the `Client` structs. For example: The Interceptor closure gets called before the signing process, thus any changes done to the request will be properly signed and submitted to the service. The SDK exposes a stand-alone signer that can be used to signing custom requests. Related code can be found here: https://github.com/oracle/oci-go-sdk/blob/master/common/http_signer.go. The example below shows how to create a default signer. The signer also allows more granular control on the headers used for signing. For example: You can combine a custom signer with the exposed clients in the SDK. This allows you to add custom signed headers to the request. Following is an example: Bear in mind that some services have a white list of headers that it expects to be signed. Therefore, adding an arbitrary header can result in authentications errors. To see a runnable example, see https://github.com/oracle/oci-go-sdk/blob/master/example/example_identity_test.go For more information on the signing algorithm refer to: https://docs.cloud.oracle.com/Content/API/Concepts/signingrequests.htm Some operations accept or return polymorphic JSON objects. The SDK models such objects as interfaces. Further the SDK provides structs that implement such interfaces. Thus, for all operations that expect interfaces as input, pass the struct in the SDK that satisfies such interface. For example: In the case of a polymorphic response you can type assert the interface to the expected type. For example: An example of polymorphic JSON request handling can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_test.go#L63 When calling a list operation, the operation will retrieve a page of results. To retrieve more data, call the list operation again, passing in the value of the most recent response's OpcNextPage as the value of Page in the next list operation call. When there is no more data the OpcNextPage field will be nil. An example of pagination using this logic can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_pagination_test.go The SDK has a built-in logging mechanism used internally. The internal logging logic is used to record the raw http requests, responses and potential errors when (un)marshalling request and responses. Built-in logging in the SDK is controlled via the environment variable "OCI_GO_SDK_DEBUG" and its contents. The below are possible values for the "OCI_GO_SDK_DEBUG" variable 1. "info" or "i" enables all info logging messages 2. "debug" or "d" enables all debug and info logging messages 3. "verbose" or "v" or "1" enables all verbose, debug and info logging messages 4. "null" turns all logging messages off. If the value of the environment variable does not match any of the above then default logging level is "info". If the environment variable is not present then no logging messages are emitted. The default destination for logging is Stderr and if you want to output log to a file you can set via environment variable "OCI_GO_SDK_LOG_OUTPUT_MODE". The below are possible values 1. "file" or "f" enables all logging output saved to file 2. "combine" or "c" enables all logging output to both stderr and file You can also customize the log file location and name via "OCI_GO_SDK_LOG_FILE" environment variable, the value should be the path to a specific file If this environment variable is not present, the default location will be the project root path Sometimes you may need to wait until an attribute of a resource, such as an instance or a VCN, reaches a certain state. An example of this would be launching an instance and then waiting for the instance to become available, or waiting until a subnet in a VCN has been terminated. You might also want to retry the same operation again if there's network issue etc... This can be accomplished by using the RequestMetadata.RetryPolicy. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_retry_test.go The GO SDK uses the net/http package to make calls to OCI services. If your environment requires you to use a proxy server for outgoing HTTP requests then you can set this up in the following ways: 1. Configuring environment variable as described here https://golang.org/pkg/net/http/#ProxyFromEnvironment 2. Modifying the underlying Transport struct for a service client In order to modify the underlying Transport struct in HttpClient, you can do something similar to (sample code for audit service client): The Object Storage service supports multipart uploads to make large object uploads easier by splitting the large object into parts. The Go SDK supports raw multipart upload operations for advanced use cases, as well as a higher level upload class that uses the multipart upload APIs. For links to the APIs used for multipart upload operations, see Managing Multipart Uploads (https://docs.cloud.oracle.com/iaas/Content/Object/Tasks/usingmultipartuploads.htm). Higher level multipart uploads are implemented using the UploadManager, which will: split a large object into parts for you, upload the parts in parallel, and then recombine and commit the parts as a single object in storage. This code sample shows how to use the UploadManager to automatically split an object into parts for upload to simplify interaction with the Object Storage service: https://github.com/oracle/oci-go-sdk/blob/master/example/example_objectstorage_test.go Some response fields are enum-typed. In the future, individual services may return values not covered by existing enums for that field. To address this possibility, every enum-type response field is a modeled as a type that supports any string. Thus if a service returns a value that is not recognized by your version of the SDK, then the response field will be set to this value. When individual services return a polymorphic JSON response not available as a concrete struct, the SDK will return an implementation that only satisfies the interface modeling the polymorphic JSON response. If you are using a version of the SDK released prior to the announcement of a new region, you may need to use a workaround to reach it, depending on whether the region is in the oraclecloud.com realm. A region is a localized geographic area. For more information on regions and how to identify them, see Regions and Availability Domains(https://docs.cloud.oracle.com/iaas/Content/General/Concepts/regions.htm). A realm is a set of regions that share entities. You can identify your realm by looking at the domain name at the end of the network address. For example, the realm for xyz.abc.123.oraclecloud.com is oraclecloud.com. oraclecloud.com Realm: For regions in the oraclecloud.com realm, even if common.Region does not contain the new region, the forward compatibility of the SDK can automatically handle it. You can pass new region names just as you would pass ones that are already defined. For more information on passing region names in the configuration, see Configuring (https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring). For details on common.Region, see (https://github.com/oracle/oci-go-sdk/blob/master/common/common.go). Other Realms: For regions in realms other than oraclecloud.com, you can use the following workarounds to reach new regions with earlier versions of the SDK. NOTE: Be sure to supply the appropriate endpoints for your region. You can overwrite the target host with client.Host: If you are authenticating via instance principals, you can set the authentication endpoint in an environment variable: Got a fix for a bug, or a new feature you'd like to contribute? The SDK is open source and accepting pull requests on GitHub https://github.com/oracle/oci-go-sdk Licensing information available at: https://github.com/oracle/oci-go-sdk/blob/master/LICENSE.txt To be notified when a new version of the Go SDK is released, subscribe to the following feed: https://github.com/oracle/oci-go-sdk/releases.atom Please refer to this link: https://github.com/oracle/oci-go-sdk#help

Package log4go provides level-based and highly configurable logging. This is inspired by the logging functionality in Java. Essentially, you create a Logger object and create output filters for it. You can send whatever you want to the Logger, and it will filter that based on your settings and send it to the outputs. This way, you can put as much debug code in your program as you want, and when you're done you can filter out the mundane messages so only the important ones show up. Utility functions are provided to make life easier. Here is some example code to get started: log := log4go.NewLogger() log.AddFilter("stdout", log4go.DEBUG, log4go.NewConsoleLogWriter()) log.AddFilter("log", log4go.FINE, log4go.NewFileLogWriter("example.log", true)) log.Info("The time is now: %s", time.LocalTime().Format("15:04:05 MST 2006/01/02")) The first two lines can be combined with the utility NewDefaultLogger: log := log4go.NewDefaultLogger(log4go.DEBUG) log.AddFilter("log", log4go.FINE, log4go.NewFileLogWriter("example.log", true)) log.Info("The time is now: %s", time.LocalTime().Format("15:04:05 MST 2006/01/02")) Usage notes: Changes from 2.0: Future work: (please let me know if you think I should work on any of these particularly)

Package cleanhttp offers convenience utilities for acquiring "clean" http.Transport and http.Client structs. Values set on http.DefaultClient and http.DefaultTransport affect all callers. This can have detrimental effects, esepcially in TLS contexts, where client or root certificates set to talk to multiple endpoints can end up displacing each other, leading to hard-to-debug issues. This package provides non-shared http.Client and http.Transport structs to ensure that the configuration will not be overwritten by other parts of the application or dependencies. The DefaultClient and DefaultTransport functions disable idle connections and keepalives. Without ensuring that idle connections are closed before garbage collection, short-term clients/transports can leak file descriptors, eventually leading to "too many open files" errors. If you will be connecting to the same hosts repeatedly from the same client, you can use DefaultPooledClient to receive a client that has connection pooling semantics similar to http.DefaultClient.

Package gnomock contains a framework to set up temporary docker containers for integration and end-to-end testing of other applications. It handles pulling images, starting containers, waiting for them to become available, setting up their initial state and cleaning up in the end. Its power is in a variety of Presets, each implementing a specific database, service or other tools. Each preset provides ways of setting up its initial state as easily as possible: SQL schema creation, test data upload into S3, sending test events to Splunk, etc. All containers created using Gnomock have a self-destruct mechanism that kicks-in right after the test execution completes. To debug cases where containers don't behave as expected, there are options like `WithDebugMode()` or `WithLogWriter()`. For the list of presets, please refer to https://pkg.go.dev/github.com/orlangure/gnomock/preset. Each preset can then be used in the following way:

Package capnp is a Cap'n Proto library for Go. https://capnproto.org/ Read the Getting Started guide for a tutorial on how to use this package. https://github.com/capnproto/go-capnproto2/wiki/Getting-Started capnpc-go provides the compiler backend for capnp. capnpc-go requires two annotations for all files: package and import. package is needed to know what package to place at the head of the generated file and what identifier to use when referring to the type from another package. import should be the fully qualified import path and is used to generate import statement from other packages and to detect when two types are in the same package. For example: For adding documentation comments to the generated code, there's the doc annotation. This annotation adds the comment to a struct, enum or field so that godoc will pick it up. For example: In Cap'n Proto, the unit of communication is a message. A message consists of one or more segments -- contiguous blocks of memory. This allows large messages to be split up and loaded independently or lazily. Typically you will use one segment per message. Logically, a message is organized in a tree of objects, with the root always being a struct (as opposed to a list or primitive). Messages can be read from and written to a stream. The Message and Segment types are the main types that application code will use from this package. The Message type has methods for marshaling and unmarshaling its segments to the wire format. If the application needs to read or write from a stream, it should use the Encoder and Decoder types. The type for a generic reference to a Cap'n Proto object is Ptr. A Ptr can refer to a struct, a list, or an interface. Ptr, Struct, List, and Interface (the pointer types) have value semantics and refer to data in a single segment. All of the pointer types have a notion of "valid". An invalid pointer will return the default value from any accessor and panic when any setter is called. In previous versions of this package, the Pointer interface was used instead of the Ptr struct. This interface and functions that use it are now deprecated. See https://github.com/capnproto/go-capnproto2/wiki/New-Ptr-Type for details about this API change. Data accessors and setters (i.e. struct primitive fields and list elements) do not return errors, but pointer accessors and setters do. There are a few reasons that a read or write of a pointer can fail, but the most common are bad pointers or allocation failures. For accessors, an invalid object will be returned in case of an error. Since Go doesn't have generics, wrapper types provide type safety on lists. This package provides lists of basic types, and capnpc-go generates list wrappers for named types. However, if you need to use deeper nesting of lists (e.g. List(List(UInt8))), you will need to use a PointerList and wrap the elements. For the following schema: capnpc-go will generate: For each group a typedef is created with a different method set for just the groups fields: generates the following: That way the following may be used to access a field in a group: Note that group accessors just convert the type and so have no overhead. Named unions are treated as a group with an inner unnamed union. Unnamed unions generate an enum Type_Which and a corresponding Which() function: generates the following: Which() should be checked before using the getters, and the default case must always be handled. Setters for single values will set the union discriminator as well as set the value. For voids in unions, there is a void setter that just sets the discriminator. For example: generates the following: Similarly, for groups in unions, there is a group setter that just sets the discriminator. This must be called before the group getter can be used to set values. For example: and in usage: capnpc-go generates enum values as constants. For example in the capnp file: In the generated capnp.go file: In addition an enum.String() function is generated that will convert the constants to a string for debugging or logging purposes. By default, the enum name is used as the tag value, but the tags can be customized with a $Go.tag or $Go.notag annotation. For example: In the generated go file: capnpc-go generates type-safe Client wrappers for interfaces. For parameter lists and result lists, structs are generated as described above with the names Interface_method_Params and Interface_method_Results, unless a single struct type is used. For example, for this interface: capnpc-go generates the following Go code (along with the structs Calculator_evaluate_Params and Calculator_evaluate_Results): capnpc-go also generates code to implement the interface: Since a single capability may want to implement many interfaces, you can use multiple *_Methods functions to build a single slice to send to NewServer. An example of combining the client/server code to communicate with a locally implemented Calculator: A note about message ordering: by default, only one method per server will be invoked at a time; when implementing a server method which blocks or takes a long time, you calling the server.Go function to unblock future calls.

Package raylib - Go bindings for raylib, a simple and easy-to-use library to enjoy videogames programming. raylib is highly inspired by Borland BGI graphics lib and by XNA framework. raylib could be useful for prototyping, tools development, graphic applications, embedded systems and education. NOTE for ADVENTURERS: raylib is a programming library to learn videogames programming; no fancy interface, no visual helpers, no auto-debugging... just coding in the most pure spartan-programmers way.

Package monkit is a flexible code instrumenting and data collection library. I'm going to try and sell you as fast as I can on this library. Example usage We've got tools that capture distribution information (including quantiles) about int64, float64, and bool types. We have tools that capture data about events (we've got meters for deltas, rates, etc). We have rich tools for capturing information about tasks and functions, and literally anything that can generate a name and a number. Almost just as importantly, the amount of boilerplate and code you have to write to get these features is very minimal. Data that's hard to measure probably won't get measured. This data can be collected and sent to Graphite (http://graphite.wikidot.com/) or any other time-series database. Here's a selection of live stats from one of our storage nodes: This library generates call graphs of your live process for you. These call graphs aren't created through sampling. They're full pictures of all of the interesting functions you've annotated, along with quantile information about their successes, failures, how often they panic, return an error (if so instrumented), how many are currently running, etc. The data can be returned in dot format, in json, in text, and can be about just the functions that are currently executing, or all the functions the monitoring system has ever seen. Here's another example of one of our production nodes: https://raw.githubusercontent.com/spacemonkeygo/monkit/master/images/callgraph2.png This library generates trace graphs of your live process for you directly, without requiring standing up some tracing system such as Zipkin (though you can do that too). Inspired by Google's Dapper (http://research.google.com/pubs/pub36356.html) and Twitter's Zipkin (http://zipkin.io), we have process-internal trace graphs, triggerable by a number of different methods. You get this trace information for free whenever you use Go contexts (https://blog.golang.org/context) and function monitoring. The output formats are svg and json. Additionally, the library supports trace observation plugins, and we've written a plugin that sends this data to Zipkin (http://github.com/spacemonkeygo/monkit-zipkin). https://raw.githubusercontent.com/spacemonkeygo/monkit/master/images/trace.png Before our crazy Go rewrite of everything (https://www.spacemonkey.com/blog/posts/go-space-monkey) (and before we had even seen Google's Dapper paper), we were a Python shop, and all of our "interesting" functions were decorated with a helper that collected timing information and sent it to Graphite. When we transliterated to Go, we wanted to preserve that functionality, so the first version of our monitoring package was born. Over time it started to get janky, especially as we found Zipkin and started adding tracing functionality to it. We rewrote all of our Go code to use Google contexts, and then realized we could get call graph information. We decided a refactor and then an all-out rethinking of our monitoring package was best, and so now we have this library. Sometimes you really want callstack contextual information without having to pass arguments through everything on the call stack. In other languages, many people implement this with thread-local storage. Example: let's say you have written a big system that responds to user requests. All of your libraries log using your log library. During initial development everything is easy to debug, since there's low user load, but now you've scaled and there's OVER TEN USERS and it's kind of hard to tell what log lines were caused by what. Wouldn't it be nice to add request ids to all of the log lines kicked off by that request? Then you could grep for all log lines caused by a specific request id. Geez, it would suck to have to pass all contextual debugging information through all of your callsites. Google solved this problem by always passing a context.Context interface through from call to call. A Context is basically just a mapping of arbitrary keys to arbitrary values that users can add new values for. This way if you decide to add a request context, you can add it to your Context and then all callsites that decend from that place will have the new data in their contexts. It is admittedly very verbose to add contexts to every function call. Painfully so. I hope to write more about it in the future, but Google also wrote up their thoughts about it (https://blog.golang.org/context), which you can go read. For now, just swallow your disgust and let's keep moving. Let's make a super simple Varnish (https://www.varnish-cache.org/) clone. Open up gedit! (Okay just kidding, open whatever text editor you want.) For this motivating program, we won't even add the caching, though there's comments for where to add it if you'd like. For now, let's just make a barebones system that will proxy HTTP requests. We'll call it VLite, but maybe we should call it VReallyLite. Run and build this and open localhost:8080 in your browser. If you use the default proxy target, it should inform you that the world hasn't been destroyed yet. The first thing you'll want to do is add the small amount of boilerplate to make the instrumentation we're going to add to your process observable later. Import the basic monkit packages: and then register environmental statistics and kick off a goroutine in your main method to serve debug requests: Rebuild, and then check out localhost:9000/stats (or localhost:9000/stats/json, if you prefer) in your browser! Remember what I said about Google's contexts (https://blog.golang.org/context)? It might seem a bit overkill for such a small project, but it's time to add them. To help out here, I've created a library that constructs contexts for you for incoming HTTP requests. Nothing that's about to happen requires my webhelp library (https://godoc.org/github.com/jtolds/webhelp), but here is the code now refactored to receive and pass contexts through our two per-request calls. You can create a new context for a request however you want. One reason to use something like webhelp is that the cancelation feature of Contexts is hooked up to the HTTP request getting canceled. Let's start to get statistics about how many requests we receive! First, this package (main) will need to get a monitoring Scope. Add this global definition right after all your imports, much like you'd create a logger with many logging libraries: Now, make the error return value of HandleHTTP named (so, (err error)), and add this defer line as the very first instruction of HandleHTTP: Let's also add the same line (albeit modified for the lack of error) to Proxy, replacing &err with nil: You should now have something like: We'll unpack what's going on here, but for now: For this new funcs dataset, if you want a graph, you can download a dot graph at localhost:9000/funcs/dot and json information from localhost:9000/funcs/json. You should see something like: with a similar report for the Proxy method, or a graph like: https://raw.githubusercontent.com/spacemonkeygo/monkit/master/images/handlehttp.png This data reports the overall callgraph of execution for known traces, along with how many of each function are currently running, the most running concurrently (the highwater), how many were successful along with quantile timing information, how many errors there were (with quantile timing information if applicable), and how many panics there were. Since the Proxy method isn't capturing a returned err value, and since HandleHTTP always returns nil, this example won't ever have failures. If you're wondering about the success count being higher than you expected, keep in mind your browser probably requested a favicon.ico. Cool, eh? How it works is an interesting line of code - there's three function calls. If you look at the Go spec, all of the function calls will run at the time the function starts except for the very last one. The first function call, mon.Task(), creates or looks up a wrapper around a Func. You could get this yourself by requesting mon.Func() inside of the appropriate function or mon.FuncNamed(). Both mon.Task() and mon.Func() are inspecting runtime.Caller to determine the name of the function. Because this is a heavy operation, you can actually store the result of mon.Task() and reuse it somehow else if you prefer, so instead of you could instead use which is more performant every time after the first time. runtime.Caller only gets called once. Careful! Don't use the same myFuncMon in different functions unless you want to screw up your statistics! The second function call starts all the various stop watches and bookkeeping to keep track of the function. It also mutates the context pointer it's given to extend the context with information about what current span (in Zipkin parlance) is active. Notably, you *can* pass nil for the context if you really don't want a context. You just lose callgraph information. The last function call stops all the stop watches ad makes a note of any observed errors or panics (it repanics after observing them). Turns out, we don't even need to change our program anymore to get rich tracing information! Open your browser and go to localhost:9000/trace/svg?regex=HandleHTTP. It won't load, and in fact, it's waiting for you to open another tab and refresh localhost:8080 again. Once you retrigger the actual application behavior, the trace regex will capture a trace starting on the first function that matches the supplied regex, and return an svg. Go back to your first tab, and you should see a relatively uninteresting but super promising svg. Let's make the trace more interesting. Add a to your HandleHTTP method, rebuild, and restart. Load localhost:8080, then start a new request to your trace URL, then reload localhost:8080 again. Flip back to your trace, and you should see that the Proxy method only takes a portion of the time of HandleHTTP! https://cdn.rawgit.com/spacemonkeygo/monkit/master/images/trace.svg There's multiple ways to select a trace. You can select by regex using the preselect method (default), which first evaluates the regex on all known functions for sanity checking. Sometimes, however, the function you want to trace may not yet be known to monkit, in which case you'll want to turn preselection off. You may have a bad regex, or you may be in this case if you get the error "Bad Request: regex preselect matches 0 functions." Another way to select a trace is by providing a trace id, which we'll get to next! Make sure to check out what the addition of the time.Sleep call did to the other reports. It's easy to write plugins for monkit! Check out our first one that exports data to Zipkin (http://zipkin.io/)'s Scribe API: https://github.com/spacemonkeygo/monkit-zipkin We plan to have more (for HTrace, OpenTracing, etc, etc), soon!

Package log15 provides an opinionated, simple toolkit for best-practice logging that is both human and machine readable. It is modeled after the standard library's io and net/http packages. This package enforces you to only log key/value pairs. Keys must be strings. Values may be any type that you like. The default output format is logfmt, but you may also choose to use JSON instead if that suits you. Here's how you log: This will output a line that looks like: To get started, you'll want to import the library: Now you're ready to start logging: Because recording a human-meaningful message is common and good practice, the first argument to every logging method is the value to the *implicit* key 'msg'. Additionally, the level you choose for a message will be automatically added with the key 'lvl', and so will the current timestamp with key 't'. You may supply any additional context as a set of key/value pairs to the logging function. log15 allows you to favor terseness, ordering, and speed over safety. This is a reasonable tradeoff for logging functions. You don't need to explicitly state keys/values, log15 understands that they alternate in the variadic argument list: If you really do favor your type-safety, you may choose to pass a log.Ctx instead: Frequently, you want to add context to a logger so that you can track actions associated with it. An http request is a good example. You can easily create new loggers that have context that is automatically included with each log line: This will output a log line that includes the path context that is attached to the logger: The Handler interface defines where log lines are printed to and how they are formated. Handler is a single interface that is inspired by net/http's handler interface: Handlers can filter records, format them, or dispatch to multiple other Handlers. This package implements a number of Handlers for common logging patterns that are easily composed to create flexible, custom logging structures. Here's an example handler that prints logfmt output to Stdout: Here's an example handler that defers to two other handlers. One handler only prints records from the rpc package in logfmt to standard out. The other prints records at Error level or above in JSON formatted output to the file /var/log/service.json This package implements three Handlers that add debugging information to the context, CallerFileHandler, CallerFuncHandler and CallerStackHandler. Here's an example that adds the source file and line number of each logging call to the context. This will output a line that looks like: Here's an example that logs the call stack rather than just the call site. This will output a line that looks like: The "%+v" format instructs the handler to include the path of the source file relative to the compile time GOPATH. The github.com/go-stack/stack package documents the full list of formatting verbs and modifiers available. The Handler interface is so simple that it's also trivial to write your own. Let's create an example handler which tries to write to one handler, but if that fails it falls back to writing to another handler and includes the error that it encountered when trying to write to the primary. This might be useful when trying to log over a network socket, but if that fails you want to log those records to a file on disk. This pattern is so useful that a generic version that handles an arbitrary number of Handlers is included as part of this library called FailoverHandler. Sometimes, you want to log values that are extremely expensive to compute, but you don't want to pay the price of computing them if you haven't turned up your logging level to a high level of detail. This package provides a simple type to annotate a logging operation that you want to be evaluated lazily, just when it is about to be logged, so that it would not be evaluated if an upstream Handler filters it out. Just wrap any function which takes no arguments with the log.Lazy type. For example: If this message is not logged for any reason (like logging at the Error level), then factorRSAKey is never evaluated. The same log.Lazy mechanism can be used to attach context to a logger which you want to be evaluated when the message is logged, but not when the logger is created. For example, let's imagine a game where you have Player objects: You always want to log a player's name and whether they're alive or dead, so when you create the player object, you might do: Only now, even after a player has died, the logger will still report they are alive because the logging context is evaluated when the logger was created. By using the Lazy wrapper, we can defer the evaluation of whether the player is alive or not to each log message, so that the log records will reflect the player's current state no matter when the log message is written: If log15 detects that stdout is a terminal, it will configure the default handler for it (which is log.StdoutHandler) to use TerminalFormat. This format logs records nicely for your terminal, including color-coded output based on log level. Becasuse log15 allows you to step around the type system, there are a few ways you can specify invalid arguments to the logging functions. You could, for example, wrap something that is not a zero-argument function with log.Lazy or pass a context key that is not a string. Since logging libraries are typically the mechanism by which errors are reported, it would be onerous for the logging functions to return errors. Instead, log15 handles errors by making these guarantees to you: - Any log record containing an error will still be printed with the error explained to you as part of the log record. - Any log record containing an error will include the context key LOG15_ERROR, enabling you to easily (and if you like, automatically) detect if any of your logging calls are passing bad values. Understanding this, you might wonder why the Handler interface can return an error value in its Log method. Handlers are encouraged to return errors only if they fail to write their log records out to an external source like if the syslog daemon is not responding. This allows the construction of useful handlers which cope with those failures like the FailoverHandler. log15 is intended to be useful for library authors as a way to provide configurable logging to users of their library. Best practice for use in a library is to always disable all output for your logger by default and to provide a public Logger instance that consumers of your library can configure. Like so: Users of your library may then enable it if they like: The ability to attach context to a logger is a powerful one. Where should you do it and why? I favor embedding a Logger directly into any persistent object in my application and adding unique, tracing context keys to it. For instance, imagine I am writing a web browser: When a new tab is created, I assign a logger to it with the url of the tab as context so it can easily be traced through the logs. Now, whenever we perform any operation with the tab, we'll log with its embedded logger and it will include the tab title automatically: There's only one problem. What if the tab url changes? We could use log.Lazy to make sure the current url is always written, but that would mean that we couldn't trace a tab's full lifetime through our logs after the user navigate to a new URL. Instead, think about what values to attach to your loggers the same way you think about what to use as a key in a SQL database schema. If it's possible to use a natural key that is unique for the lifetime of the object, do so. But otherwise, log15's ext package has a handy RandId function to let you generate what you might call "surrogate keys" They're just random hex identifiers to use for tracing. Back to our Tab example, we would prefer to set up our Logger like so: Now we'll have a unique traceable identifier even across loading new urls, but we'll still be able to see the tab's current url in the log messages. For all Handler functions which can return an error, there is a version of that function which will return no error but panics on failure. They are all available on the Must object. For example: All of the following excellent projects inspired the design of this library: code.google.com/p/log4go github.com/op/go-logging github.com/technoweenie/grohl github.com/Sirupsen/logrus github.com/kr/logfmt github.com/spacemonkeygo/spacelog golang's stdlib, notably io and net/http https://xkcd.com/927/

This is the official Go SDK for Oracle Cloud Infrastructure Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#installing for installation instructions. Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring for configuration instructions. The following example shows how to get started with the SDK. The example belows creates an identityClient struct with the default configuration. It then utilizes the identityClient to list availability domains and prints them out to stdout More examples can be found in the SDK Github repo: https://github.com/oracle/oci-go-sdk/tree/master/example Optional fields are represented with the `mandatory:"false"` tag on input structs. The SDK will omit all optional fields that are nil when making requests. In the case of enum-type fields, the SDK will omit fields whose value is an empty string. The SDK uses pointers for primitive types in many input structs. To aid in the construction of such structs, the SDK provides functions that return a pointer for a given value. For example: The SDK exposes functionality that allows the user to customize any http request before is sent to the service. You can do so by setting the `Interceptor` field in any of the `Client` structs. For example: The Interceptor closure gets called before the signing process, thus any changes done to the request will be properly signed and submitted to the service. The SDK exposes a stand-alone signer that can be used to signing custom requests. Related code can be found here: https://github.com/oracle/oci-go-sdk/blob/master/common/http_signer.go. The example below shows how to create a default signer. The signer also allows more granular control on the headers used for signing. For example: You can combine a custom signer with the exposed clients in the SDK. This allows you to add custom signed headers to the request. Following is an example: Bear in mind that some services have a white list of headers that it expects to be signed. Therefore, adding an arbitrary header can result in authentications errors. To see a runnable example, see https://github.com/oracle/oci-go-sdk/blob/master/example/example_identity_test.go For more information on the signing algorithm refer to: https://docs.cloud.oracle.com/Content/API/Concepts/signingrequests.htm Some operations accept or return polymorphic JSON objects. The SDK models such objects as interfaces. Further the SDK provides structs that implement such interfaces. Thus, for all operations that expect interfaces as input, pass the struct in the SDK that satisfies such interface. For example: In the case of a polymorphic response you can type assert the interface to the expected type. For example: An example of polymorphic JSON request handling can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_test.go#L63 When calling a list operation, the operation will retrieve a page of results. To retrieve more data, call the list operation again, passing in the value of the most recent response's OpcNextPage as the value of Page in the next list operation call. When there is no more data the OpcNextPage field will be nil. An example of pagination using this logic can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_pagination_test.go The SDK has a built-in logging mechanism used internally. The internal logging logic is used to record the raw http requests, responses and potential errors when (un)marshalling request and responses. Built-in logging in the SDK is controlled via the environment variable "OCI_GO_SDK_DEBUG" and its contents. The below are possible values for the "OCI_GO_SDK_DEBUG" variable 1. "info" or "i" enables all info logging messages 2. "debug" or "d" enables all debug and info logging messages 3. "verbose" or "v" or "1" enables all verbose, debug and info logging messages 4. "null" turns all logging messages off. If the value of the environment variable does not match any of the above then default logging level is "info". If the environment variable is not present then no logging messages are emitted. The default destination for logging is Stderr and if you want to output log to a file you can set via environment variable "OCI_GO_SDK_LOG_OUTPUT_MODE". The below are possible values 1. "file" or "f" enables all logging output saved to file 2. "combine" or "c" enables all logging output to both stderr and file You can also customize the log file location and name via "OCI_GO_SDK_LOG_FILE" environment variable, the value should be the path to a specific file If this environment variable is not present, the default location will be the project root path Sometimes you may need to wait until an attribute of a resource, such as an instance or a VCN, reaches a certain state. An example of this would be launching an instance and then waiting for the instance to become available, or waiting until a subnet in a VCN has been terminated. You might also want to retry the same operation again if there's network issue etc... This can be accomplished by using the RequestMetadata.RetryPolicy(request level configuration), alternatively, global(all services) or client level RetryPolicy configration is also possible. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_retry_test.go If you are trying to make a PUT/POST API call with binary request body, please make sure the binary request body is resettable, which means the request body should inherit Seeker interface. The Retry behavior Precedence (Highest to lowest) is defined as below:- The OCI Go SDK defines a default retry policy that retries on the errors suitable for retries (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm), for a recommended period of time (up to 7 attempts spread out over at most approximately 1.5 minutes). The default retry policy is defined by : Default Retry-able Errors Below is the list of default retry-able errors for which retry attempts should be made. The following errors should be retried (with backoff). HTTP Code Customer-facing Error Code Apart from the above errors, retries should also be attempted in the following Client Side errors : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) The above errors can be avoided through retrying and hence, are classified as the default retry-able errors. Additionally, retries should also be made for Circuit Breaker exceptions (Exceptions raised by Circuit Breaker in an open state) Default Termination Strategy The termination strategy defines when SDKs should stop attempting to retry. In other words, it's the deadline for retries. The OCI SDKs should stop retrying the operation after 7 retry attempts. This means the SDKs will have retried for ~98 seconds or ~1.5 minutes have elapsed due to total delays. SDKs will make a total of 8 attempts. (1 initial request + 7 retries) Default Delay Strategy Default Delay Strategy - The delay strategy defines the amount of time to wait between each of the retry attempts. The default delay strategy chosen for the SDK – Exponential backoff with jitter, using: 1. The base time to use in retry calculations will be 1 second 2. An exponent of 2. When calculating the next retry time, the SDK will raise this to the power of the number of attempts 3. A maximum wait time between calls of 30 seconds (Capped) 4. Added jitter value between 0-1000 milliseconds to spread out the requests Configure and use default retry policy You can set this retry policy for a single request: or for all requests made by a client: or for all requests made by all clients: or setting default retry via environment varaible, which is a global switch for all services: Some services enable retry for operations by default, this can be overridden using any alternatives mentioned above. To know which service operations have retries enabled by default, look at the operation's description in the SDK - it will say whether that it has retries enabled by default Some resources may have to be replicated across regions and are only eventually consistent. That means the request to create, update, or delete the resource succeeded, but the resource is not available everywhere immediately. Creating, updating, or deleting any resource in the Identity service is affected by eventual consistency, and doing so may cause other operations in other services to fail until the Identity resource has been replicated. For example, the request to CreateTag in the Identity service in the home region succeeds, but immediately using that created tag in another region in a request to LaunchInstance in the Compute service may fail. If you are creating, updating, or deleting resources in the Identity service, we recommend using an eventually consistent retry policy for any service you access. The default retry policy already deals with eventual consistency. Example: This retry policy will use a different strategy if an eventually consistent change was made in the recent past (called the "eventually consistent window", currently defined to be 4 minutes after the eventually consistent change). This special retry policy for eventual consistency will: 1. make up to 9 attempts (including the initial attempt); if an attempt is successful, no more attempts will be made 2. retry at most until (a) approximately the end of the eventually consistent window or (b) the end of the default retry period of about 1.5 minutes, whichever is farther in the future; if an attempt is successful, no more attempts will be made, and the OCI Go SDK will not wait any longer 3. retry on the error codes 400-RelatedResourceNotAuthorizedOrNotFound, 404-NotAuthorizedOrNotFound, and 409-NotAuthorizedOrResourceAlreadyExists, for which the default retry policy does not retry, in addition to the errors the default retry policy retries on (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm) If there were no eventually consistent actions within the recent past, then this special retry strategy is not used. If you want a retry policy that does not handle eventual consistency in a special way, for example because you retry on all error responses, you can use DefaultRetryPolicyWithoutEventualConsistency or NewRetryPolicyWithOptions with the common.ReplaceWithValuesFromRetryPolicy(common.DefaultRetryPolicyWithoutEventualConsistency()) option: The NewRetryPolicy function also creates a retry policy without eventual consistency. Circuit Breaker can prevent an application repeatedly trying to execute an operation that is likely to fail, allowing it to continue without waiting for the fault to be rectified or wasting CPU cycles, of course, it also enables an application to detect whether the fault has been resolved. If the problem appears to have been rectified, the application can attempt to invoke the operation. Go SDK intergrates sony/gobreaker solution, wraps in a circuit breaker object, which monitors for failures. Once the failures reach a certain threshold, the circuit breaker trips, and all further calls to the circuit breaker return with an error, this also saves the service from being overwhelmed with network calls in case of an outage. Circuit Breaker Configuration Definitions 1. Failure Rate Threshold - The state of the CircuitBreaker changes from CLOSED to OPEN when the failure rate is equal or greater than a configurable threshold. For example when more than 50% of the recorded calls have failed. 2. Reset Timeout - The timeout after which an open circuit breaker will attempt a request if a request is made 3. Failure Exceptions - The list of Exceptions that will be regarded as failures for the circuit. 4. Minimum number of calls/ Volume threshold - Configures the minimum number of calls which are required (per sliding window period) before the CircuitBreaker can calculate the error rate. 1. Failure Rate Threshold - 80% - This means when 80% of the requests calculated for a time window of 120 seconds have failed then the circuit will transition from closed to open. 2. Minimum number of calls/ Volume threshold - A value of 10, for the above defined time window of 120 seconds. 3. Reset Timeout - 30 seconds to wait before setting the breaker to halfOpen state, and trying the action again. 4. Failure Exceptions - The failures for the circuit will only be recorded for the retryable/transient exceptions. This means only the following exceptions will be regarded as failure for the circuit. HTTP Code Customer-facing Error Code Apart from the above, the following client side exceptions will also be treated as a failure for the circuit : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) Go SDK enable circuit breaker with default configuration for most of the service clients, if you don't want to enable the solution, can disable the functionality before your application running Go SDK also supports customize Circuit Breaker with specified configurations. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_circuitbreaker_test.go To know which service clients have circuit breakers enabled, look at the service client's description in the SDK - it will say whether that it has circuit breakers enabled by default The GO SDK uses the net/http package to make calls to OCI services. If your environment requires you to use a proxy server for outgoing HTTP requests then you can set this up in the following ways: 1. Configuring environment variable as described here https://golang.org/pkg/net/http/#ProxyFromEnvironment 2. Modifying the underlying Transport struct for a service client In order to modify the underlying Transport struct in HttpClient, you can do something similar to (sample code for audit service client): The Object Storage service supports multipart uploads to make large object uploads easier by splitting the large object into parts. The Go SDK supports raw multipart upload operations for advanced use cases, as well as a higher level upload class that uses the multipart upload APIs. For links to the APIs used for multipart upload operations, see Managing Multipart Uploads (https://docs.cloud.oracle.com/iaas/Content/Object/Tasks/usingmultipartuploads.htm). Higher level multipart uploads are implemented using the UploadManager, which will: split a large object into parts for you, upload the parts in parallel, and then recombine and commit the parts as a single object in storage. This code sample shows how to use the UploadManager to automatically split an object into parts for upload to simplify interaction with the Object Storage service: https://github.com/oracle/oci-go-sdk/blob/master/example/example_objectstorage_test.go Some response fields are enum-typed. In the future, individual services may return values not covered by existing enums for that field. To address this possibility, every enum-type response field is a modeled as a type that supports any string. Thus if a service returns a value that is not recognized by your version of the SDK, then the response field will be set to this value. When individual services return a polymorphic JSON response not available as a concrete struct, the SDK will return an implementation that only satisfies the interface modeling the polymorphic JSON response. If you are using a version of the SDK released prior to the announcement of a new region, you may need to use a workaround to reach it, depending on whether the region is in the oraclecloud.com realm. A region is a localized geographic area. For more information on regions and how to identify them, see Regions and Availability Domains(https://docs.cloud.oracle.com/iaas/Content/General/Concepts/regions.htm). A realm is a set of regions that share entities. You can identify your realm by looking at the domain name at the end of the network address. For example, the realm for xyz.abc.123.oraclecloud.com is oraclecloud.com. oraclecloud.com Realm: For regions in the oraclecloud.com realm, even if common.Region does not contain the new region, the forward compatibility of the SDK can automatically handle it. You can pass new region names just as you would pass ones that are already defined. For more information on passing region names in the configuration, see Configuring (https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring). For details on common.Region, see (https://github.com/oracle/oci-go-sdk/blob/master/common/common.go). Other Realms: For regions in realms other than oraclecloud.com, you can use the following workarounds to reach new regions with earlier versions of the SDK. NOTE: Be sure to supply the appropriate endpoints for your region. You can overwrite the target host with client.Host: If you are authenticating via instance principals, you can set the authentication endpoint in an environment variable: Got a fix for a bug, or a new feature you'd like to contribute? The SDK is open source and accepting pull requests on GitHub https://github.com/oracle/oci-go-sdk Licensing information available at: https://github.com/oracle/oci-go-sdk/blob/master/LICENSE.txt To be notified when a new version of the Go SDK is released, subscribe to the following feed: https://github.com/oracle/oci-go-sdk/releases.atom Please refer to this link: https://github.com/oracle/oci-go-sdk#help

This is the official Go SDK for Oracle Cloud Infrastructure Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#installing for installation instructions. Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring for configuration instructions. The following example shows how to get started with the SDK. The example belows creates an identityClient struct with the default configuration. It then utilizes the identityClient to list availability domains and prints them out to stdout More examples can be found in the SDK Github repo: https://github.com/oracle/oci-go-sdk/tree/master/example Optional fields are represented with the `mandatory:"false"` tag on input structs. The SDK will omit all optional fields that are nil when making requests. In the case of enum-type fields, the SDK will omit fields whose value is an empty string. The SDK uses pointers for primitive types in many input structs. To aid in the construction of such structs, the SDK provides functions that return a pointer for a given value. For example: Dedicated endpoints are the endpoint templates defined by the service for a specific realm at client level. OCI Go SDK allows you to enable the use of these realm-specific endpoint templates feature at application level and at client level. The value set at client level takes precedence over the value set at the application level. This feature is disabled by default. For reference, please refer https://github.com/oracle/oci-go-sdk/blob/master/example/example_objectstorage_test.go#L222-L251 The SDK exposes functionality that allows the user to customize any http request before is sent to the service. You can do so by setting the `Interceptor` field in any of the `Client` structs. For example: The Interceptor closure gets called before the signing process, thus any changes done to the request will be properly signed and submitted to the service. The SDK exposes a stand-alone signer that can be used to signing custom requests. Related code can be found here: https://github.com/oracle/oci-go-sdk/blob/master/common/http_signer.go. The example below shows how to create a default signer. The signer also allows more granular control on the headers used for signing. For example: You can combine a custom signer with the exposed clients in the SDK. This allows you to add custom signed headers to the request. Following is an example: Bear in mind that some services have a white list of headers that it expects to be signed. Therefore, adding an arbitrary header can result in authentications errors. To see a runnable example, see https://github.com/oracle/oci-go-sdk/blob/master/example/example_identity_test.go For more information on the signing algorithm refer to: https://docs.cloud.oracle.com/Content/API/Concepts/signingrequests.htm Some operations accept or return polymorphic JSON objects. The SDK models such objects as interfaces. Further the SDK provides structs that implement such interfaces. Thus, for all operations that expect interfaces as input, pass the struct in the SDK that satisfies such interface. For example: In the case of a polymorphic response you can type assert the interface to the expected type. For example: An example of polymorphic JSON request handling can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_test.go#L63 When calling a list operation, the operation will retrieve a page of results. To retrieve more data, call the list operation again, passing in the value of the most recent response's OpcNextPage as the value of Page in the next list operation call. When there is no more data the OpcNextPage field will be nil. An example of pagination using this logic can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_pagination_test.go The SDK has a built-in logging mechanism used internally. The internal logging logic is used to record the raw http requests, responses and potential errors when (un)marshalling request and responses. Built-in logging in the SDK is controlled via the environment variable "OCI_GO_SDK_DEBUG" and its contents. The below are possible values for the "OCI_GO_SDK_DEBUG" variable 1. "info" or "i" enables all info logging messages 2. "debug" or "d" enables all debug and info logging messages 3. "verbose" or "v" or "1" enables all verbose, debug and info logging messages 4. "null" turns all logging messages off. If the value of the environment variable does not match any of the above then default logging level is "info". If the environment variable is not present then no logging messages are emitted. You can also enable logs by code. For example This way you enable debug logs by code. The default destination for logging is Stderr and if you want to output log to a file you can set via environment variable "OCI_GO_SDK_LOG_OUTPUT_MODE". The below are possible values 1. "file" or "f" enables all logging output saved to file 2. "combine" or "c" enables all logging output to both stderr and file You can also customize the log file location and name via "OCI_GO_SDK_LOG_FILE" environment variable, the value should be the path to a specific file If this environment variable is not present, the default location will be the project root path Sometimes you may need to wait until an attribute of a resource, such as an instance or a VCN, reaches a certain state. An example of this would be launching an instance and then waiting for the instance to become available, or waiting until a subnet in a VCN has been terminated. You might also want to retry the same operation again if there's network issue etc... This can be accomplished by using the RequestMetadata.RetryPolicy(request level configuration), alternatively, global(all services) or client level RetryPolicy configration is also possible. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_retry_test.go If you are trying to make a PUT/POST API call with binary request body, please make sure the binary request body is resettable, which means the request body should inherit Seeker interface. The Retry behavior Precedence (Highest to lowest) is defined as below:- The OCI Go SDK defines a default retry policy that retries on the errors suitable for retries (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm), for a recommended period of time (up to 7 attempts spread out over at most approximately 1.5 minutes). The default retry policy is defined by : Default Retry-able Errors Below is the list of default retry-able errors for which retry attempts should be made. The following errors should be retried (with backoff). HTTP Code Customer-facing Error Code Apart from the above errors, retries should also be attempted in the following Client Side errors : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) The above errors can be avoided through retrying and hence, are classified as the default retry-able errors. Additionally, retries should also be made for Circuit Breaker exceptions (Exceptions raised by Circuit Breaker in an open state) Default Termination Strategy The termination strategy defines when SDKs should stop attempting to retry. In other words, it's the deadline for retries. The OCI SDKs should stop retrying the operation after 7 retry attempts. This means the SDKs will have retried for ~98 seconds or ~1.5 minutes have elapsed due to total delays. SDKs will make a total of 8 attempts. (1 initial request + 7 retries) Default Delay Strategy Default Delay Strategy - The delay strategy defines the amount of time to wait between each of the retry attempts. The default delay strategy chosen for the SDK – Exponential backoff with jitter, using: 1. The base time to use in retry calculations will be 1 second 2. An exponent of 2. When calculating the next retry time, the SDK will raise this to the power of the number of attempts 3. A maximum wait time between calls of 30 seconds (Capped) 4. Added jitter value between 0-1000 milliseconds to spread out the requests Configure and use default retry policy You can set this retry policy for a single request: or for all requests made by a client: or for all requests made by all clients: or setting default retry via environment variable, which is a global switch for all services: Some services enable retry for operations by default, this can be overridden using any alternatives mentioned above. To know which service operations have retries enabled by default, look at the operation's description in the SDK - it will say whether that it has retries enabled by default Some resources may have to be replicated across regions and are only eventually consistent. That means the request to create, update, or delete the resource succeeded, but the resource is not available everywhere immediately. Creating, updating, or deleting any resource in the Identity service is affected by eventual consistency, and doing so may cause other operations in other services to fail until the Identity resource has been replicated. For example, the request to CreateTag in the Identity service in the home region succeeds, but immediately using that created tag in another region in a request to LaunchInstance in the Compute service may fail. If you are creating, updating, or deleting resources in the Identity service, we recommend using an eventually consistent retry policy for any service you access. The default retry policy already deals with eventual consistency. Example: This retry policy will use a different strategy if an eventually consistent change was made in the recent past (called the "eventually consistent window", currently defined to be 4 minutes after the eventually consistent change). This special retry policy for eventual consistency will: 1. make up to 9 attempts (including the initial attempt); if an attempt is successful, no more attempts will be made 2. retry at most until (a) approximately the end of the eventually consistent window or (b) the end of the default retry period of about 1.5 minutes, whichever is farther in the future; if an attempt is successful, no more attempts will be made, and the OCI Go SDK will not wait any longer 3. retry on the error codes 400-RelatedResourceNotAuthorizedOrNotFound, 404-NotAuthorizedOrNotFound, and 409-NotAuthorizedOrResourceAlreadyExists, for which the default retry policy does not retry, in addition to the errors the default retry policy retries on (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm) If there were no eventually consistent actions within the recent past, then this special retry strategy is not used. If you want a retry policy that does not handle eventual consistency in a special way, for example because you retry on all error responses, you can use DefaultRetryPolicyWithoutEventualConsistency or NewRetryPolicyWithOptions with the common.ReplaceWithValuesFromRetryPolicy(common.DefaultRetryPolicyWithoutEventualConsistency()) option: The NewRetryPolicy function also creates a retry policy without eventual consistency. Circuit Breaker can prevent an application repeatedly trying to execute an operation that is likely to fail, allowing it to continue without waiting for the fault to be rectified or wasting CPU cycles, of course, it also enables an application to detect whether the fault has been resolved. If the problem appears to have been rectified, the application can attempt to invoke the operation. Go SDK intergrates sony/gobreaker solution, wraps in a circuit breaker object, which monitors for failures. Once the failures reach a certain threshold, the circuit breaker trips, and all further calls to the circuit breaker return with an error, this also saves the service from being overwhelmed with network calls in case of an outage. Circuit Breaker Configuration Definitions 1. Failure Rate Threshold - The state of the CircuitBreaker changes from CLOSED to OPEN when the failure rate is equal or greater than a configurable threshold. For example when more than 50% of the recorded calls have failed. 2. Reset Timeout - The timeout after which an open circuit breaker will attempt a request if a request is made 3. Failure Exceptions - The list of Exceptions that will be regarded as failures for the circuit. 4. Minimum number of calls/ Volume threshold - Configures the minimum number of calls which are required (per sliding window period) before the CircuitBreaker can calculate the error rate. 1. Failure Rate Threshold - 80% - This means when 80% of the requests calculated for a time window of 120 seconds have failed then the circuit will transition from closed to open. 2. Minimum number of calls/ Volume threshold - A value of 10, for the above defined time window of 120 seconds. 3. Reset Timeout - 30 seconds to wait before setting the breaker to halfOpen state, and trying the action again. 4. Failure Exceptions - The failures for the circuit will only be recorded for the retryable/transient exceptions. This means only the following exceptions will be regarded as failure for the circuit. HTTP Code Customer-facing Error Code Apart from the above, the following client side exceptions will also be treated as a failure for the circuit : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) Go SDK enable circuit breaker with default configuration for most of the service clients, if you don't want to enable the solution, can disable the functionality before your application running Go SDK also supports customize Circuit Breaker with specified configurations. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_circuitbreaker_test.go To know which service clients have circuit breakers enabled, look at the service client's description in the SDK - it will say whether that it has circuit breakers enabled by default As a result of the SDK treating responses with a non-2xx HTTP status code as an error, the SDK will produce an error on 3xx responses. This can impact operations which support conditional GETs, such as GetObject() and HeadObject() methods as these can return responses with an HTTP status code of 304 if passed an 'IfNoneMatch' that corresponds to the current etag of the object / bucket. In order to account for this, you should check for status code 304 when an error is produced. For example: The GO SDK uses the net/http package to make calls to OCI services. If your environment requires you to use a proxy server for outgoing HTTP requests then you can set this up in the following ways: 1. Configuring environment variable as described here https://golang.org/pkg/net/http/#ProxyFromEnvironment 2. Modifying the underlying Transport struct for a service client In order to modify the underlying Transport struct in HttpClient, you can do something similar to (sample code for audit service client): The Object Storage service supports multipart uploads to make large object uploads easier by splitting the large object into parts. The Go SDK supports raw multipart upload operations for advanced use cases, as well as a higher level upload class that uses the multipart upload APIs. For links to the APIs used for multipart upload operations, see Managing Multipart Uploads (https://docs.cloud.oracle.com/iaas/Content/Object/Tasks/usingmultipartuploads.htm). Higher level multipart uploads are implemented using the UploadManager, which will: split a large object into parts for you, upload the parts in parallel, and then recombine and commit the parts as a single object in storage. This code sample shows how to use the UploadManager to automatically split an object into parts for upload to simplify interaction with the Object Storage service: https://github.com/oracle/oci-go-sdk/blob/master/example/example_objectstorage_test.go Some response fields are enum-typed. In the future, individual services may return values not covered by existing enums for that field. To address this possibility, every enum-type response field is a modeled as a type that supports any string. Thus if a service returns a value that is not recognized by your version of the SDK, then the response field will be set to this value. When individual services return a polymorphic JSON response not available as a concrete struct, the SDK will return an implementation that only satisfies the interface modeling the polymorphic JSON response. If you are using a version of the SDK released prior to the announcement of a new region, you may need to use a workaround to reach it, depending on whether the region is in the oraclecloud.com realm. A region is a localized geographic area. For more information on regions and how to identify them, see Regions and Availability Domains(https://docs.cloud.oracle.com/iaas/Content/General/Concepts/regions.htm). A realm is a set of regions that share entities. You can identify your realm by looking at the domain name at the end of the network address. For example, the realm for xyz.abc.123.oraclecloud.com is oraclecloud.com. oraclecloud.com Realm: For regions in the oraclecloud.com realm, even if common.Region does not contain the new region, the forward compatibility of the SDK can automatically handle it. You can pass new region names just as you would pass ones that are already defined. For more information on passing region names in the configuration, see Configuring (https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring). For details on common.Region, see (https://github.com/oracle/oci-go-sdk/blob/master/common/common.go). Other Realms: For regions in realms other than oraclecloud.com, you can use the following workarounds to reach new regions with earlier versions of the SDK. NOTE: Be sure to supply the appropriate endpoints for your region. You can overwrite the target host with client.Host: If you are authenticating via instance principals, you can set the authentication endpoint in an environment variable: In order to use a custom CA bundle, you can set the environment variable OCI_DEFAULT_CERTS_PATH to point to the path of custom CA Bundle you want the OCI GO SDK to use while making API calls to the OCI services If you additionally want to set custom leaf/client certs, then you can use the the environment variables OCI_DEFAULT_CLIENT_CERTS_PATH and OCI_DEFAULT_CLIENT_CERTS_PRIVATE_KEY_PATH to set the path of the custom client/leaf cert and the private key respectively. The default refresh interval for custom CA bundle or client certs is 30 minutes. If you want to modify this, then you can configure the refresh interval in minutes by using either the Global property OciGlobalRefreshIntervalForCustomCerts defined in the common package or set the environment variable OCI_DEFAULT_REFRESH_INTERVAL_FOR_CUSTOM_CERTS to set it instead. Please note, that the property OciGlobalRefreshIntervalForCustomCerts has a higher precedence than the environment variable OCI_DEFAULT_REFRESH_INTERVAL_FOR_CUSTOM_CERTS. If this value is negative, then it would be assumed that it is unset. If it is set to 0, then the SDK would disable the custom ca bundle and client cert refresh Got a fix for a bug, or a new feature you'd like to contribute? The SDK is open source and accepting pull requests on GitHub https://github.com/oracle/oci-go-sdk Licensing information available at: https://github.com/oracle/oci-go-sdk/blob/master/LICENSE.txt To be notified when a new version of the Go SDK is released, subscribe to the following feed: https://github.com/oracle/oci-go-sdk/releases.atom Please refer to this link: https://github.com/oracle/oci-go-sdk#help

This is the official Go SDK for Oracle Cloud Infrastructure Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#installing for installation instructions. Refer to https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring for configuration instructions. The following example shows how to get started with the SDK. The example belows creates an identityClient struct with the default configuration. It then utilizes the identityClient to list availability domains and prints them out to stdout More examples can be found in the SDK Github repo: https://github.com/oracle/oci-go-sdk/tree/master/example Optional fields are represented with the `mandatory:"false"` tag on input structs. The SDK will omit all optional fields that are nil when making requests. In the case of enum-type fields, the SDK will omit fields whose value is an empty string. The SDK uses pointers for primitive types in many input structs. To aid in the construction of such structs, the SDK provides functions that return a pointer for a given value. For example: The SDK exposes functionality that allows the user to customize any http request before is sent to the service. You can do so by setting the `Interceptor` field in any of the `Client` structs. For example: The Interceptor closure gets called before the signing process, thus any changes done to the request will be properly signed and submitted to the service. The SDK exposes a stand-alone signer that can be used to signing custom requests. Related code can be found here: https://github.com/oracle/oci-go-sdk/blob/master/common/http_signer.go. The example below shows how to create a default signer. The signer also allows more granular control on the headers used for signing. For example: You can combine a custom signer with the exposed clients in the SDK. This allows you to add custom signed headers to the request. Following is an example: Bear in mind that some services have a white list of headers that it expects to be signed. Therefore, adding an arbitrary header can result in authentications errors. To see a runnable example, see https://github.com/oracle/oci-go-sdk/blob/master/example/example_identity_test.go For more information on the signing algorithm refer to: https://docs.cloud.oracle.com/Content/API/Concepts/signingrequests.htm Some operations accept or return polymorphic JSON objects. The SDK models such objects as interfaces. Further the SDK provides structs that implement such interfaces. Thus, for all operations that expect interfaces as input, pass the struct in the SDK that satisfies such interface. For example: In the case of a polymorphic response you can type assert the interface to the expected type. For example: An example of polymorphic JSON request handling can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_test.go#L63 When calling a list operation, the operation will retrieve a page of results. To retrieve more data, call the list operation again, passing in the value of the most recent response's OpcNextPage as the value of Page in the next list operation call. When there is no more data the OpcNextPage field will be nil. An example of pagination using this logic can be found here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_core_pagination_test.go The SDK has a built-in logging mechanism used internally. The internal logging logic is used to record the raw http requests, responses and potential errors when (un)marshalling request and responses. Built-in logging in the SDK is controlled via the environment variable "OCI_GO_SDK_DEBUG" and its contents. The below are possible values for the "OCI_GO_SDK_DEBUG" variable 1. "info" or "i" enables all info logging messages 2. "debug" or "d" enables all debug and info logging messages 3. "verbose" or "v" or "1" enables all verbose, debug and info logging messages 4. "null" turns all logging messages off. If the value of the environment variable does not match any of the above then default logging level is "info". If the environment variable is not present then no logging messages are emitted. The default destination for logging is Stderr and if you want to output log to a file you can set via environment variable "OCI_GO_SDK_LOG_OUTPUT_MODE". The below are possible values 1. "file" or "f" enables all logging output saved to file 2. "combine" or "c" enables all logging output to both stderr and file You can also customize the log file location and name via "OCI_GO_SDK_LOG_FILE" environment variable, the value should be the path to a specific file If this environment variable is not present, the default location will be the project root path Sometimes you may need to wait until an attribute of a resource, such as an instance or a VCN, reaches a certain state. An example of this would be launching an instance and then waiting for the instance to become available, or waiting until a subnet in a VCN has been terminated. You might also want to retry the same operation again if there's network issue etc... This can be accomplished by using the RequestMetadata.RetryPolicy(request level configuration), alternatively, global(all services) or client level RetryPolicy configration is also possible. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_retry_test.go If you are trying to make a PUT/POST API call with binary request body, please make sure the binary request body is resettable, which means the request body should inherit Seeker interface. The Retry behavior Precedence (Highest to lowest) is defined as below:- The OCI Go SDK defines a default retry policy that retries on the errors suitable for retries (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm), for a recommended period of time (up to 7 attempts spread out over at most approximately 1.5 minutes). The default retry policy is defined by : Default Retry-able Errors Below is the list of default retry-able errors for which retry attempts should be made. The following errors should be retried (with backoff). HTTP Code Customer-facing Error Code Apart from the above errors, retries should also be attempted in the following Client Side errors : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) The above errors can be avoided through retrying and hence, are classified as the default retry-able errors. Additionally, retries should also be made for Circuit Breaker exceptions (Exceptions raised by Circuit Breaker in an open state) Default Termination Strategy The termination strategy defines when SDKs should stop attempting to retry. In other words, it's the deadline for retries. The OCI SDKs should stop retrying the operation after 7 retry attempts. This means the SDKs will have retried for ~98 seconds or ~1.5 minutes have elapsed due to total delays. SDKs will make a total of 8 attempts. (1 initial request + 7 retries) Default Delay Strategy Default Delay Strategy - The delay strategy defines the amount of time to wait between each of the retry attempts. The default delay strategy chosen for the SDK – Exponential backoff with jitter, using: 1. The base time to use in retry calculations will be 1 second 2. An exponent of 2. When calculating the next retry time, the SDK will raise this to the power of the number of attempts 3. A maximum wait time between calls of 30 seconds (Capped) 4. Added jitter value between 0-1000 milliseconds to spread out the requests Configure and use default retry policy You can set this retry policy for a single request: or for all requests made by a client: or for all requests made by all clients: or setting default retry via environment varaible, which is a global switch for all services: Some services enable retry for operations by default, this can be overridden using any alternatives mentioned above. To know which service operations have retries enabled by default, look at the operation's description in the SDK - it will say whether that it has retries enabled by default Some resources may have to be replicated across regions and are only eventually consistent. That means the request to create, update, or delete the resource succeeded, but the resource is not available everywhere immediately. Creating, updating, or deleting any resource in the Identity service is affected by eventual consistency, and doing so may cause other operations in other services to fail until the Identity resource has been replicated. For example, the request to CreateTag in the Identity service in the home region succeeds, but immediately using that created tag in another region in a request to LaunchInstance in the Compute service may fail. If you are creating, updating, or deleting resources in the Identity service, we recommend using an eventually consistent retry policy for any service you access. The default retry policy already deals with eventual consistency. Example: This retry policy will use a different strategy if an eventually consistent change was made in the recent past (called the "eventually consistent window", currently defined to be 4 minutes after the eventually consistent change). This special retry policy for eventual consistency will: 1. make up to 9 attempts (including the initial attempt); if an attempt is successful, no more attempts will be made 2. retry at most until (a) approximately the end of the eventually consistent window or (b) the end of the default retry period of about 1.5 minutes, whichever is farther in the future; if an attempt is successful, no more attempts will be made, and the OCI Go SDK will not wait any longer 3. retry on the error codes 400-RelatedResourceNotAuthorizedOrNotFound, 404-NotAuthorizedOrNotFound, and 409-NotAuthorizedOrResourceAlreadyExists, for which the default retry policy does not retry, in addition to the errors the default retry policy retries on (see https://docs.oracle.com/en-us/iaas/Content/API/References/apierrors.htm) If there were no eventually consistent actions within the recent past, then this special retry strategy is not used. If you want a retry policy that does not handle eventual consistency in a special way, for example because you retry on all error responses, you can use DefaultRetryPolicyWithoutEventualConsistency or NewRetryPolicyWithOptions with the common.ReplaceWithValuesFromRetryPolicy(common.DefaultRetryPolicyWithoutEventualConsistency()) option: The NewRetryPolicy function also creates a retry policy without eventual consistency. Circuit Breaker can prevent an application repeatedly trying to execute an operation that is likely to fail, allowing it to continue without waiting for the fault to be rectified or wasting CPU cycles, of course, it also enables an application to detect whether the fault has been resolved. If the problem appears to have been rectified, the application can attempt to invoke the operation. Go SDK intergrates sony/gobreaker solution, wraps in a circuit breaker object, which monitors for failures. Once the failures reach a certain threshold, the circuit breaker trips, and all further calls to the circuit breaker return with an error, this also saves the service from being overwhelmed with network calls in case of an outage. Circuit Breaker Configuration Definitions 1. Failure Rate Threshold - The state of the CircuitBreaker changes from CLOSED to OPEN when the failure rate is equal or greater than a configurable threshold. For example when more than 50% of the recorded calls have failed. 2. Reset Timeout - The timeout after which an open circuit breaker will attempt a request if a request is made 3. Failure Exceptions - The list of Exceptions that will be regarded as failures for the circuit. 4. Minimum number of calls/ Volume threshold - Configures the minimum number of calls which are required (per sliding window period) before the CircuitBreaker can calculate the error rate. 1. Failure Rate Threshold - 80% - This means when 80% of the requests calculated for a time window of 120 seconds have failed then the circuit will transition from closed to open. 2. Minimum number of calls/ Volume threshold - A value of 10, for the above defined time window of 120 seconds. 3. Reset Timeout - 30 seconds to wait before setting the breaker to halfOpen state, and trying the action again. 4. Failure Exceptions - The failures for the circuit will only be recorded for the retryable/transient exceptions. This means only the following exceptions will be regarded as failure for the circuit. HTTP Code Customer-facing Error Code Apart from the above, the following client side exceptions will also be treated as a failure for the circuit : 1. HTTP Connection timeout 2. Request Connection Errors 3. Request Exceptions 4. Other timeouts (like Read Timeout) Go SDK enable circuit breaker with default configuration for most of the service clients, if you don't want to enable the solution, can disable the functionality before your application running Go SDK also supports customize Circuit Breaker with specified configurations. You can find the examples here: https://github.com/oracle/oci-go-sdk/blob/master/example/example_circuitbreaker_test.go To know which service clients have circuit breakers enabled, look at the service client's description in the SDK - it will say whether that it has circuit breakers enabled by default The GO SDK uses the net/http package to make calls to OCI services. If your environment requires you to use a proxy server for outgoing HTTP requests then you can set this up in the following ways: 1. Configuring environment variable as described here https://golang.org/pkg/net/http/#ProxyFromEnvironment 2. Modifying the underlying Transport struct for a service client In order to modify the underlying Transport struct in HttpClient, you can do something similar to (sample code for audit service client): The Object Storage service supports multipart uploads to make large object uploads easier by splitting the large object into parts. The Go SDK supports raw multipart upload operations for advanced use cases, as well as a higher level upload class that uses the multipart upload APIs. For links to the APIs used for multipart upload operations, see Managing Multipart Uploads (https://docs.cloud.oracle.com/iaas/Content/Object/Tasks/usingmultipartuploads.htm). Higher level multipart uploads are implemented using the UploadManager, which will: split a large object into parts for you, upload the parts in parallel, and then recombine and commit the parts as a single object in storage. This code sample shows how to use the UploadManager to automatically split an object into parts for upload to simplify interaction with the Object Storage service: https://github.com/oracle/oci-go-sdk/blob/master/example/example_objectstorage_test.go Some response fields are enum-typed. In the future, individual services may return values not covered by existing enums for that field. To address this possibility, every enum-type response field is a modeled as a type that supports any string. Thus if a service returns a value that is not recognized by your version of the SDK, then the response field will be set to this value. When individual services return a polymorphic JSON response not available as a concrete struct, the SDK will return an implementation that only satisfies the interface modeling the polymorphic JSON response. If you are using a version of the SDK released prior to the announcement of a new region, you may need to use a workaround to reach it, depending on whether the region is in the oraclecloud.com realm. A region is a localized geographic area. For more information on regions and how to identify them, see Regions and Availability Domains(https://docs.cloud.oracle.com/iaas/Content/General/Concepts/regions.htm). A realm is a set of regions that share entities. You can identify your realm by looking at the domain name at the end of the network address. For example, the realm for xyz.abc.123.oraclecloud.com is oraclecloud.com. oraclecloud.com Realm: For regions in the oraclecloud.com realm, even if common.Region does not contain the new region, the forward compatibility of the SDK can automatically handle it. You can pass new region names just as you would pass ones that are already defined. For more information on passing region names in the configuration, see Configuring (https://github.com/oracle/oci-go-sdk/blob/master/README.md#configuring). For details on common.Region, see (https://github.com/oracle/oci-go-sdk/blob/master/common/common.go). Other Realms: For regions in realms other than oraclecloud.com, you can use the following workarounds to reach new regions with earlier versions of the SDK. NOTE: Be sure to supply the appropriate endpoints for your region. You can overwrite the target host with client.Host: If you are authenticating via instance principals, you can set the authentication endpoint in an environment variable: Got a fix for a bug, or a new feature you'd like to contribute? The SDK is open source and accepting pull requests on GitHub https://github.com/oracle/oci-go-sdk Licensing information available at: https://github.com/oracle/oci-go-sdk/blob/master/LICENSE.txt To be notified when a new version of the Go SDK is released, subscribe to the following feed: https://github.com/oracle/oci-go-sdk/releases.atom Please refer to this link: https://github.com/oracle/oci-go-sdk#help

Package yarpc provides the YARPC service framework. With hundreds to thousands of services communicating with RPC, transport protocols (like HTTP and TChannel), encoding protocols (like JSON or Thrift), and peer choosers are the concepts that vary year over year. Separating these concerns allows services to change transports and wire protocols without changing call sites or request handlers, build proxies and wire protocol bridges, or experiment with load balancing strategies. YARPC is a toolkit for services and proxies. YARPC breaks RPC into interchangeable encodings, transports, and peer choosers. YARPC for Go provides reference implementations for HTTP/1.1, TChannel and gRPC transports, and also raw, JSON, Thrift, and Protobuf encodings. YARPC for Go provides a round robin peer chooser and experimental implementations for debug pages and rate limiting. YARPC for Go plans to provide a load balancer that uses a least-pending-requests strategy. Peer choosers can implement any strategy, including load balancing or sharding, in turn bound to any peer list updater. Regardless of transport, every RPC has some common properties: caller name, service name, procedure name, encoding name, deadline or TTL, headers, baggage (multi-hop headers), and tracing. Each RPC can also have an optional shard key, routing key, or routing delegate for advanced routing. YARPC transports use a shared API for capturing RPC metadata, so middleware can apply to requests over any transport. Each YARPC transport protocol can implement inbound handlers and outbound callers. Each of these can support different RPC types, like unary (request and response) or oneway (request and receipt) RPC. A future release of YARPC will add support for other RPC types including variations on streaming and pubsub.

Package pointer implements Andersen's analysis, an inclusion-based pointer analysis algorithm first described in (Andersen, 1994). A pointer analysis relates every pointer expression in a whole program to the set of memory locations to which it might point. This information can be used to construct a call graph of the program that precisely represents the destinations of dynamic function and method calls. It can also be used to determine, for example, which pairs of channel operations operate on the same channel. The package allows the client to request a set of expressions of interest for which the points-to information will be returned once the analysis is complete. In addition, the client may request that a callgraph is constructed. The example program in example_test.go demonstrates both of these features. Clients should not request more information than they need since it may increase the cost of the analysis significantly. Our algorithm is INCLUSION-BASED: the points-to sets for x and y will be related by pts(y) ⊇ pts(x) if the program contains the statement y = x. It is FLOW-INSENSITIVE: it ignores all control flow constructs and the order of statements in a program. It is therefore a "MAY ALIAS" analysis: its facts are of the form "P may/may not point to L", not "P must point to L". It is FIELD-SENSITIVE: it builds separate points-to sets for distinct fields, such as x and y in struct { x, y *int }. It is mostly CONTEXT-INSENSITIVE: most functions are analyzed once, so values can flow in at one call to the function and return out at another. Only some smaller functions are analyzed with consideration of their calling context. It has a CONTEXT-SENSITIVE HEAP: objects are named by both allocation site and context, so the objects returned by two distinct calls to f: are distinguished up to the limits of the calling context. It is a WHOLE PROGRAM analysis: it requires SSA-form IR for the complete Go program and summaries for native code. See the (Hind, PASTE'01) survey paper for an explanation of these terms. The analysis is fully sound when invoked on pure Go programs that do not use reflection or unsafe.Pointer conversions. In other words, if there is any possible execution of the program in which pointer P may point to object O, the analysis will report that fact. By default, the "reflect" library is ignored by the analysis, as if all its functions were no-ops, but if the client enables the Reflection flag, the analysis will make a reasonable attempt to model the effects of calls into this library. However, this comes at a significant performance cost, and not all features of that library are yet implemented. In addition, some simplifying approximations must be made to ensure that the analysis terminates; for example, reflection can be used to construct an infinite set of types and values of those types, but the analysis arbitrarily bounds the depth of such types. Most but not all reflection operations are supported. In particular, addressable reflect.Values are not yet implemented, so operations such as (reflect.Value).Set have no analytic effect. The pointer analysis makes no attempt to understand aliasing between the operand x and result y of an unsafe.Pointer conversion: It is as if the conversion allocated an entirely new object: The analysis cannot model the aliasing effects of functions written in languages other than Go, such as runtime intrinsics in C or assembly, or code accessed via cgo. The result is as if such functions are no-ops. However, various important intrinsics are understood by the analysis, along with built-ins such as append. The analysis currently provides no way for users to specify the aliasing effects of native code. ------------------------------------------------------------------------ The remaining documentation is intended for package maintainers and pointer analysis specialists. Maintainers should have a solid understanding of the referenced papers (especially those by H&L and PKH) before making making significant changes. The implementation is similar to that described in (Pearce et al, PASTE'04). Unlike many algorithms which interleave constraint generation and solving, constructing the callgraph as they go, this implementation for the most part observes a phase ordering (generation before solving), with only simple (copy) constraints being generated during solving. (The exception is reflection, which creates various constraints during solving as new types flow to reflect.Value operations.) This improves the traction of presolver optimisations, but imposes certain restrictions, e.g. potential context sensitivity is limited since all variants must be created a priori. A type is said to be "pointer-like" if it is a reference to an object. Pointer-like types include pointers and also interfaces, maps, channels, functions and slices. We occasionally use C's x->f notation to distinguish the case where x is a struct pointer from x.f where is a struct value. Pointer analysis literature (and our comments) often uses the notation dst=*src+offset to mean something different than what it means in Go. It means: for each node index p in pts(src), the node index p+offset is in pts(dst). Similarly *dst+offset=src is used for store constraints and dst=src+offset for offset-address constraints. Nodes are the key datastructure of the analysis, and have a dual role: they represent both constraint variables (equivalence classes of pointers) and members of points-to sets (things that can be pointed at, i.e. "labels"). Nodes are naturally numbered. The numbering enables compact representations of sets of nodes such as bitvectors (or BDDs); and the ordering enables a very cheap way to group related nodes together. For example, passing n parameters consists of generating n parallel constraints from caller+i to callee+i for 0<=i<n. The zero nodeid means "not a pointer". For simplicity, we generate flow constraints even for non-pointer types such as int. The pointer equivalence (PE) presolver optimization detects which variables cannot point to anything; this includes not only all variables of non-pointer types (such as int) but also variables of pointer-like types if they are always nil, or are parameters to a function that is never called. Each node represents a scalar part of a value or object. Aggregate types (structs, tuples, arrays) are recursively flattened out into a sequential list of scalar component types, and all the elements of an array are represented by a single node. (The flattening of a basic type is a list containing a single node.) Nodes are connected into a graph with various kinds of labelled edges: simple edges (or copy constraints) represent value flow. Complex edges (load, store, etc) trigger the creation of new simple edges during the solving phase. Conceptually, an "object" is a contiguous sequence of nodes denoting an addressable location: something that a pointer can point to. The first node of an object has a non-nil obj field containing information about the allocation: its size, context, and ssa.Value. Objects include: Many objects have no Go types. For example, the func, map and chan type kinds in Go are all varieties of pointers, but their respective objects are actual functions (executable code), maps (hash tables), and channels (synchronized queues). Given the way we model interfaces, they too are pointers to "tagged" objects with no Go type. And an *ssa.Global denotes the address of a global variable, but the object for a Global is the actual data. So, the types of an ssa.Value that creates an object is "off by one indirection": a pointer to the object. The individual nodes of an object are sometimes referred to as "labels". For uniformity, all objects have a non-zero number of fields, even those of the empty type struct{}. (All arrays are treated as if of length 1, so there are no empty arrays. The empty tuple is never address-taken, so is never an object.) An tagged object has the following layout: The T node's typ field is the dynamic type of the "payload": the value v which follows, flattened out. The T node's obj has the otTagged flag. Tagged objects are needed when generalizing across types: interfaces, reflect.Values, reflect.Types. Each of these three types is modelled as a pointer that exclusively points to tagged objects. Tagged objects may be indirect (obj.flags ⊇ {otIndirect}) meaning that the value v is not of type T but *T; this is used only for reflect.Values that represent lvalues. (These are not implemented yet.) Variables of the following "scalar" types may be represented by a single node: basic types, pointers, channels, maps, slices, 'func' pointers, interfaces. Pointers: Nothing to say here, oddly. Basic types (bool, string, numbers, unsafe.Pointer): Currently all fields in the flattening of a type, including non-pointer basic types such as int, are represented in objects and values. Though non-pointer nodes within values are uninteresting, non-pointer nodes in objects may be useful (if address-taken) because they permit the analysis to deduce, in this example, that p points to s.x. If we ignored such object fields, we could only say that p points somewhere within s. All other basic types are ignored. Expressions of these types have zero nodeid, and fields of these types within aggregate other types are omitted. unsafe.Pointers are not modelled as pointers, so a conversion of an unsafe.Pointer to *T is (unsoundly) treated equivalent to new(T). Channels: An expression of type 'chan T' is a kind of pointer that points exclusively to channel objects, i.e. objects created by MakeChan (or reflection). 'chan T' is treated like *T. *ssa.MakeChan is treated as equivalent to new(T). *ssa.Send and receive (*ssa.UnOp(ARROW)) and are equivalent to store Maps: An expression of type 'map[K]V' is a kind of pointer that points exclusively to map objects, i.e. objects created by MakeMap (or reflection). map K[V] is treated like *M where M = struct{k K; v V}. *ssa.MakeMap is equivalent to new(M). *ssa.MapUpdate is equivalent to *y=x where *y and x have type M. *ssa.Lookup is equivalent to y=x.v where x has type *M. Slices: A slice []T, which dynamically resembles a struct{array *T, len, cap int}, is treated as if it were just a *T pointer; the len and cap fields are ignored. *ssa.MakeSlice is treated like new([1]T): an allocation of a *ssa.Index on a slice is equivalent to a load. *ssa.IndexAddr on a slice returns the address of the sole element of the slice, i.e. the same address. *ssa.Slice is treated as a simple copy. Functions: An expression of type 'func...' is a kind of pointer that points exclusively to function objects. A function object has the following layout: There may be multiple function objects for the same *ssa.Function due to context-sensitive treatment of some functions. The first node is the function's identity node. Associated with every callsite is a special "targets" variable, whose pts() contains the identity node of each function to which the call may dispatch. Identity words are not otherwise used during the analysis, but we construct the call graph from the pts() solution for such nodes. The following block of contiguous nodes represents the flattened-out types of the parameters ("P-block") and results ("R-block") of the function object. The treatment of free variables of closures (*ssa.FreeVar) is like that of global variables; it is not context-sensitive. *ssa.MakeClosure instructions create copy edges to Captures. A Go value of type 'func' (i.e. a pointer to one or more functions) is a pointer whose pts() contains function objects. The valueNode() for an *ssa.Function returns a singleton for that function. Interfaces: An expression of type 'interface{...}' is a kind of pointer that points exclusively to tagged objects. All tagged objects pointed to by an interface are direct (the otIndirect flag is clear) and concrete (the tag type T is not itself an interface type). The associated ssa.Value for an interface's tagged objects may be an *ssa.MakeInterface instruction, or nil if the tagged object was created by an instrinsic (e.g. reflection). Constructing an interface value causes generation of constraints for all of the concrete type's methods; we can't tell a priori which ones may be called. TypeAssert y = x.(T) is implemented by a dynamic constraint triggered by each tagged object O added to pts(x): a typeFilter constraint if T is an interface type, or an untag constraint if T is a concrete type. A typeFilter tests whether O.typ implements T; if so, O is added to pts(y). An untagFilter tests whether O.typ is assignable to T,and if so, a copy edge O.v -> y is added. ChangeInterface is a simple copy because the representation of tagged objects is independent of the interface type (in contrast to the "method tables" approach used by the gc runtime). y := Invoke x.m(...) is implemented by allocating contiguous P/R blocks for the callsite and adding a dynamic rule triggered by each tagged object added to pts(x). The rule adds param/results copy edges to/from each discovered concrete method. (Q. Why do we model an interface as a pointer to a pair of type and value, rather than as a pair of a pointer to type and a pointer to value? A. Control-flow joins would merge interfaces ({T1}, {V1}) and ({T2}, {V2}) to make ({T1,T2}, {V1,V2}), leading to the infeasible and type-unsafe combination (T1,V2). Treating the value and its concrete type as inseparable makes the analysis type-safe.) Type parameters: Type parameters are not directly supported by the analysis. Calls to generic functions will be left as if they had empty bodies. Users of the package are expected to use the ssa.InstantiateGenerics builder mode when building code that uses or depends on code containing generics. reflect.Value: A reflect.Value is modelled very similar to an interface{}, i.e. as a pointer exclusively to tagged objects, but with two generalizations. 1. a reflect.Value that represents an lvalue points to an indirect (obj.flags ⊇ {otIndirect}) tagged object, which has a similar layout to an tagged object except that the value is a pointer to the dynamic type. Indirect tagged objects preserve the correct aliasing so that mutations made by (reflect.Value).Set can be observed. Indirect objects only arise when an lvalue is derived from an rvalue by indirection, e.g. the following code: Whether indirect or not, the concrete type of the tagged object corresponds to the user-visible dynamic type, and the existence of a pointer is an implementation detail. (NB: indirect tagged objects are not yet implemented) 2. The dynamic type tag of a tagged object pointed to by a reflect.Value may be an interface type; it need not be concrete. This arises in code such as this: pts(eface) is a singleton containing an interface{}-tagged object. That tagged object's payload is an interface{} value, i.e. the pts of the payload contains only concrete-tagged objects, although in this example it's the zero interface{} value, so its pts is empty. reflect.Type: Just as in the real "reflect" library, we represent a reflect.Type as an interface whose sole implementation is the concrete type, *reflect.rtype. (This choice is forced on us by go/types: clients cannot fabricate types with arbitrary method sets.) rtype instances are canonical: there is at most one per dynamic type. (rtypes are in fact large structs but since identity is all that matters, we represent them by a single node.) The payload of each *rtype-tagged object is an *rtype pointer that points to exactly one such canonical rtype object. We exploit this by setting the node.typ of the payload to the dynamic type, not '*rtype'. This saves us an indirection in each resolution rule. As an optimisation, *rtype-tagged objects are canonicalized too. Aggregate types: Aggregate types are treated as if all directly contained aggregates are recursively flattened out. Structs: *ssa.Field y = x.f creates a simple edge to y from x's node at f's offset. *ssa.FieldAddr y = &x->f requires a dynamic closure rule to create The nodes of a struct consist of a special 'identity' node (whose type is that of the struct itself), followed by the nodes for all the struct's fields, recursively flattened out. A pointer to the struct is a pointer to its identity node. That node allows us to distinguish a pointer to a struct from a pointer to its first field. Field offsets are logical field offsets (plus one for the identity node), so the sizes of the fields can be ignored by the analysis. (The identity node is non-traditional but enables the distinction described above, which is valuable for code comprehension tools. Typical pointer analyses for C, whose purpose is compiler optimization, must soundly model unsafe.Pointer (void*) conversions, and this requires fidelity to the actual memory layout using physical field offsets.) *ssa.Field y = x.f creates a simple edge to y from x's node at f's offset. *ssa.FieldAddr y = &x->f requires a dynamic closure rule to create Arrays: We model an array by an identity node (whose type is that of the array itself) followed by a node representing all the elements of the array; the analysis does not distinguish elements with different indices. Effectively, an array is treated like struct{elem T}, a load y=x[i] like y=x.elem, and a store x[i]=y like x.elem=y; the index i is ignored. A pointer to an array is pointer to its identity node. (A slice is also a pointer to an array's identity node.) The identity node allows us to distinguish a pointer to an array from a pointer to one of its elements, but it is rather costly because it introduces more offset constraints into the system. Furthermore, sound treatment of unsafe.Pointer would require us to dispense with this node. Arrays may be allocated by Alloc, by make([]T), by calls to append, and via reflection. Tuples (T, ...): Tuples are treated like structs with naturally numbered fields. *ssa.Extract is analogous to *ssa.Field. However, tuples have no identity field since by construction, they cannot be address-taken. There are three kinds of function call: Cases 1 and 2 apply equally to methods and standalone functions. Static calls: A static call consists three steps: A static function call is little more than two struct value copies between the P/R blocks of caller and callee: Context sensitivity: Static calls (alone) may be treated context sensitively, i.e. each callsite may cause a distinct re-analysis of the callee, improving precision. Our current context-sensitivity policy treats all intrinsics and getter/setter methods in this manner since such functions are small and seem like an obvious source of spurious confluences, though this has not yet been evaluated. Dynamic function calls: Dynamic calls work in a similar manner except that the creation of copy edges occurs dynamically, in a similar fashion to a pair of struct copies in which the callee is indirect: (Recall that the function object's P- and R-blocks are contiguous.) Interface method invocation: For invoke-mode calls, we create a params/results block for the callsite and attach a dynamic closure rule to the interface. For each new tagged object that flows to the interface, we look up the concrete method, find its function object, and connect its P/R blocks to the callsite's P/R blocks, adding copy edges to the graph during solving. Recording call targets: The analysis notifies its clients of each callsite it encounters, passing a CallSite interface. Among other things, the CallSite contains a synthetic constraint variable ("targets") whose points-to solution includes the set of all function objects to which the call may dispatch. It is via this mechanism that the callgraph is made available. Clients may also elect to be notified of callgraph edges directly; internally this just iterates all "targets" variables' pts(·)s. We implement Hash-Value Numbering (HVN), a pre-solver constraint optimization described in Hardekopf & Lin, SAS'07. This is documented in more detail in hvn.go. We intend to add its cousins HR and HU in future. The solver is currently a naive Andersen-style implementation; it does not perform online cycle detection, though we plan to add solver optimisations such as Hybrid- and Lazy- Cycle Detection from (Hardekopf & Lin, PLDI'07). It uses difference propagation (Pearce et al, SQC'04) to avoid redundant re-triggering of closure rules for values already seen. Points-to sets are represented using sparse bit vectors (similar to those used in LLVM and gcc), which are more space- and time-efficient than sets based on Go's built-in map type or dense bit vectors. Nodes are permuted prior to solving so that object nodes (which may appear in points-to sets) are lower numbered than non-object (var) nodes. This improves the density of the set over which the PTSs range, and thus the efficiency of the representation. Partly thanks to avoiding map iteration, the execution of the solver is 100% deterministic, a great help during debugging. Andersen, L. O. 1994. Program analysis and specialization for the C programming language. Ph.D. dissertation. DIKU, University of Copenhagen. David J. Pearce, Paul H. J. Kelly, and Chris Hankin. 2004. Efficient field-sensitive pointer analysis for C. In Proceedings of the 5th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (PASTE '04). ACM, New York, NY, USA, 37-42. http://doi.acm.org/10.1145/996821.996835 David J. Pearce, Paul H. J. Kelly, and Chris Hankin. 2004. Online Cycle Detection and Difference Propagation: Applications to Pointer Analysis. Software Quality Control 12, 4 (December 2004), 311-337. http://dx.doi.org/10.1023/B:SQJO.0000039791.93071.a2 David Grove and Craig Chambers. 2001. A framework for call graph construction algorithms. ACM Trans. Program. Lang. Syst. 23, 6 (November 2001), 685-746. http://doi.acm.org/10.1145/506315.506316 Ben Hardekopf and Calvin Lin. 2007. The ant and the grasshopper: fast and accurate pointer analysis for millions of lines of code. In Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation (PLDI '07). ACM, New York, NY, USA, 290-299. http://doi.acm.org/10.1145/1250734.1250767 Ben Hardekopf and Calvin Lin. 2007. Exploiting pointer and location equivalence to optimize pointer analysis. In Proceedings of the 14th international conference on Static Analysis (SAS'07), Hanne Riis Nielson and Gilberto Filé (Eds.). Springer-Verlag, Berlin, Heidelberg, 265-280. Atanas Rountev and Satish Chandra. 2000. Off-line variable substitution for scaling points-to analysis. In Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation (PLDI '00). ACM, New York, NY, USA, 47-56. DOI=10.1145/349299.349310 http://doi.acm.org/10.1145/349299.349310 This program demonstrates how to use the pointer analysis to obtain a conservative call-graph of a Go program. It also shows how to compute the points-to set of a variable, in this case, (C).f's ch parameter.

Package rss is a small library for simplifying the parsing of RSS and Atom feeds. The package could do with more testing, but it conforms to the RSS 1.0, 2.0, and Atom 1.0 specifications, to the best of my ability. I've tested it with about 15 different feeds, and it seems to work fine with them. If anyone has any problems with feeds being parsed incorrectly, please let me know so that I can debug and improve the package. Example usage: The output structure is pretty much as you'd expect: The library does its best to follow the appropriate specifications and not to set the Refresh time too soon. It currently follows all update time management methods in the RSS 1.0, 2.0, and Atom 1.0 specifications. If one is not provided, it defaults to 12 hour intervals (see DefaultRefreshInterval). If you are having issues with feed providors dropping connections, please let me know and I can increase this default, or you can increase the Refresh time manually. The Feed.Update method uses this Refresh time, so if Update seems to be returning very quickly with no new items, it's likely not making a request due to the provider's Refresh interval.