Localization

Package resourceexplorer2 provides the API client, operations, and parameter types for AWS Resource Explorer. Amazon Web Services Resource Explorer is a resource search and discovery service. By using Resource Explorer, you can explore your resources using an internet search engine-like experience. Examples of resources include Amazon Relational Database Service (Amazon RDS) instances, Amazon Simple Storage Service (Amazon S3) buckets, or Amazon DynamoDB tables. You can search for your resources using resource metadata like names, tags, and IDs. Resource Explorer can search across all of the Amazon Web Services Regions in your account in which you turn the service on, to simplify your cross-Region workloads. Resource Explorer scans the resources in each of the Amazon Web Services Regions in your Amazon Web Services account in which you turn on Resource Explorer. Resource Explorer creates and maintains an indexin each Region, with the details of that Region's resources. You can search across all of the indexed Regions in your account by designating one of your Amazon Web Services Regions to contain the aggregator index for the account. When you promote a local index in a Region to become the aggregator index for the account, Resource Explorer automatically replicates the index information from all local indexes in the other Regions to the aggregator index. Therefore, the Region with the aggregator index has a copy of all resource information for all Regions in the account where you turned on Resource Explorer. As a result, views in the aggregator index Region include resources from all of the indexed Regions in your account. For more information about Amazon Web Services Resource Explorer, including how to enable and configure the service, see the Amazon Web Services Resource Explorer User Guide.

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 gcs provides an API for building and using a Golomb-coded set filter. A Golomb-Coded Set (GCS) is a space-efficient probabilistic data structure that is used to test set membership with a tunable false positive rate while simultaneously preventing false negatives. In other words, items that are in the set will always match, but items that are not in the set will also sometimes match with the chosen false positive rate. This package currently implements two different versions for backwards compatibility. Version 1 is deprecated and therefore should no longer be used. Version 2 is the GCS variation that follows the specification details in DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#golomb-coded-sets. Version 2 sets do not permit empty items (data of zero length) to be added and are parameterized by the following: * A parameter `B` that defines the remainder code bit size * A parameter `M` that defines the false positive rate as `1/M` * A key for the SipHash-2-4 function * The items to include in the set Errors returned by this package are of type gcs.Error. This allows the caller to programmatically determine the specific error by examining the ErrorCode field of the type asserted gcs.Error while still providing rich error messages with contextual information. A convenience function named IsErrorCode is also provided to allow callers to easily check for a specific error code. See ErrorCode in the package documentation for a full list. GCS is used as a mechanism for storing, transmitting, and committing to per-block filters. Consensus-validating full nodes commit to a single filter for every block and serve the filter to SPV clients that match against the filter locally to determine if the block is potentially relevant. The required parameters for Decred are defined by the blockcf2 package. For more details, see the the Block Filters section of DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#block-filters

Package safebrowsing implements a client for the Safe Browsing API v4. API v4 emphasizes efficient usage of the network for bandwidth-constrained applications such as mobile devices. It achieves this by maintaining a small portion of the server state locally such that some queries can be answered immediately without any network requests. Thus, fewer API calls made, means less bandwidth is used. At a high-level, the implementation does the following: Essentially the query is presented to three major components: The database, the cache, and the API. Each of these may satisfy the query immediately, or may say that it does not know and that the query should be satisfied by the next component. The goal of the database and cache is to satisfy as many queries as possible to avoid using the API. Starting with a user query, a hash of the query is performed to preserve privacy regarded the exact nature of the query. For example, if the query was for a URL, then this would be the SHA256 hash of the URL in question. Given a query hash, we first check the local database (which is periodically synced with the global Safe Browsing API servers). This database will either tell us that the query is definitely safe, or that it does not have enough information. If we are unsure about the query, we check the local cache, which can be used to satisfy queries immediately if the same query had been made recently. The cache will tell us that the query is either safe, unsafe, or unknown (because the it's not in the cache or the entry expired). If we are still unsure about the query, then we finally query the API server, which is guaranteed to return to us an authoritative answer, assuming no networking failures. For more information, see the API developer's guide:

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 gpgagent interacts with the local GPG Agent.

Package localconf record all the values of the local config options.

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!

esc embeds files into go programs and provides http.FileSystem interfaces to them. It adds all named files or files recursively under named directories at the path specified. The output file provides an http.FileSystem interface with zero dependencies on packages outside the standard library. Usage: The flags are: After producing an output file, the assets may be accessed with the FS() function, which takes a flag to use local assets instead (for local development). FS(Must)?(Byte|String) returns an asset as a (byte slice|string). FSMust(Byte|String) panics if the asset is not found. esc can be invoked by go generate: Embedded assets can be served with HTTP using the http.FileServer. Assuming you have a directory structure similar to the following: Where main.go contains:

Package globalaccelerator provides the API client, operations, and parameter types for AWS Global Accelerator. This is the Global Accelerator API Reference. This guide is for developers who need detailed information about Global Accelerator API actions, data types, and errors. For more information about Global Accelerator features, see the Global Accelerator Developer Guide. Global Accelerator is a service in which you create accelerators to improve the performance of your applications for local and global users. Depending on the type of accelerator you choose, you can gain additional benefits. By using a standard accelerator, you can improve availability of your internet applications that are used by a global audience. With a standard accelerator, Global Accelerator directs traffic to optimal endpoints over the Amazon Web Services global network. For other scenarios, you might choose a custom routing accelerator. With a custom routing accelerator, you can use application logic to directly map one or more users to a specific endpoint among many endpoints. Global Accelerator is a global service that supports endpoints in multiple Amazon Web Services Regions but you must specify the US West (Oregon) Region to create, update, or otherwise work with accelerators. That is, for example, specify --region us-west-2 on Amazon Web Services CLI commands. By default, Global Accelerator provides you with static IP addresses that you associate with your accelerator. The static IP addresses are anycast from the Amazon Web Services edge network. For IPv4, Global Accelerator provides two static IPv4 addresses. For dual-stack, Global Accelerator provides a total of four addresses: two static IPv4 addresses and two static IPv6 addresses. With a standard accelerator for IPv4, instead of using the addresses that Global Accelerator provides, you can configure these entry points to be IPv4 addresses from your own IP address ranges that you bring to Global Accelerator (BYOIP). For a standard accelerator, they distribute incoming application traffic across multiple endpoint resources in multiple Amazon Web Services Regions , which increases the availability of your applications. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses that are located in one Amazon Web Services Region or multiple Amazon Web Services Regions. For custom routing accelerators, you map traffic that arrives to the static IP addresses to specific Amazon EC2 servers in endpoints that are virtual private cloud (VPC) subnets. The static IP addresses remain assigned to your accelerator for as long as it exists, even if you disable the accelerator and it no longer accepts or routes traffic. However, when you delete an accelerator, you lose the static IP addresses that are assigned to it, so you can no longer route traffic by using them. You can use IAM policies like tag-based permissions with Global Accelerator to limit the users who have permissions to delete an accelerator. For more information, see Tag-based policies. For standard accelerators, Global Accelerator uses the Amazon Web Services global network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. The service reacts instantly to changes in health or configuration to ensure that internet traffic from clients is always directed to healthy endpoints. For more information about understanding and using Global Accelerator, see the Global Accelerator Developer Guide.

Package dht implements a Distributed Hash Table (DHT) part of the BitTorrent protocol, as specified by BEP 5: http://www.bittorrent.org/beps/bep_0005.html BitTorrent uses a "distributed hash table" (DHT) for storing peer contact information for "trackerless" torrents. In effect, each peer becomes a tracker. The protocol is based on Kademila DHT protocol and is implemented over UDP. Please note the terminology used to avoid confusion. A "peer" is a client/server listening on a TCP port that implements the BitTorrent protocol. A "node" is a client/server listening on a UDP port implementing the distributed hash table protocol. The DHT is composed of nodes and stores the location of peers. BitTorrent clients include a DHT node, which is used to contact other nodes in the DHT to get the location of peers to download from using the BitTorrent protocol. Standard use involves creating a Server, and calling Announce on it with the details of your local torrent client and infohash of interest.

Package rpc is a foundation for RPC over HTTP services, providing access to the exported methods of an object through HTTP requests. This package derives from the standard net/rpc package but uses a single HTTP request per call instead of persistent connections. Other differences compared to net/rpc: Let's setup a server and register a codec and service: This server handles requests to the "/rpc" path using a JSON codec. A codec is tied to a content type. In the example above, the JSON codec is registered to serve requests with "application/json" as the value for the "Content-Type" header. If the header includes a charset definition, it is ignored; only the media-type part is taken into account. A service can be registered using a name. If the name is empty, like in the example above, it will be inferred from the service type. That's all about the server setup. Now let's define a simple service: The example above defines a service with a method "HelloService.Say" and the arguments and reply related to that method. The service must be exported (begin with an upper case letter) or local (defined in the package registering the service). When a service is registered, the server inspects the service methods and make available the ones that follow these rules: All other methods are ignored.

Package gcs provides an API for building and using a Golomb-coded set filter. A Golomb-Coded Set (GCS) is a space-efficient probabilistic data structure that is used to test set membership with a tunable false positive rate while simultaneously preventing false negatives. In other words, items that are in the set will always match, but items that are not in the set will also sometimes match with the chosen false positive rate. This package currently implements two different versions for backwards compatibility. Version 1 is deprecated and therefore should no longer be used. Version 2 is the GCS variation that follows the specification details in DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#golomb-coded-sets. Version 2 sets do not permit empty items (data of zero length) to be added and are parameterized by the following: * A parameter `B` that defines the remainder code bit size * A parameter `M` that defines the false positive rate as `1/M` * A key for the SipHash-2-4 function * The items to include in the set Errors returned by this package are of type gcs.Error. This allows the caller to programmatically determine the specific error by examining the ErrorKind field of the type asserted gcs.Error while still providing rich error messages with contextual information. See ErrorKind in the package documentation for a full list. GCS is used as a mechanism for storing, transmitting, and committing to per-block filters. Consensus-validating full nodes commit to a single filter for every block and serve the filter to SPV clients that match against the filter locally to determine if the block is potentially relevant. The required parameters for Decred are defined by the blockcf2 package. For more details, see the Block Filters section of DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#block-filters

Package outposts provides the API client, operations, and parameter types for AWS Outposts. Amazon Web Services Outposts is a fully managed service that extends Amazon Web Services infrastructure, APIs, and tools to customer premises. By providing local access to Amazon Web Services managed infrastructure, Amazon Web Services Outposts enables customers to build and run applications on premises using the same programming interfaces as in Amazon Web Services Regions, while using local compute and storage resources for lower latency and local data processing needs.

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 libtrust provides an interface for managing authentication and authorization using public key cryptography. Authentication is handled using the identity attached to the public key and verified through TLS x509 certificates, a key challenge, or signature. Authorization and access control is managed through a trust graph distributed between both remote trust servers and locally cached and managed data.

Package color is an ANSI color package to output colorized or SGR defined output to the standard output. The API can be used in several way, pick one that suits you. Use simple and default helper functions with predefined foreground colors: However there are times where custom color mixes are required. Below are some examples to create custom color objects and use the print functions of each separate color object. You can create PrintXxx functions to simplify even more: Or create SprintXxx functions to mix strings with other non-colorized strings: Windows support is enabled by default. All Print functions works as intended. However only for color.SprintXXX functions, user should use fmt.FprintXXX and set the output to color.Output: Using with existing code is possible. Just use the Set() method to set the standard output to the given parameters. That way a rewrite of an existing code is not required. There might be a case where you want to disable color output (for example to pipe the standard output of your app to somewhere else). `Color` has support to disable colors both globally and for single color definition. For example suppose you have a CLI app and a `--no-color` bool flag. You can easily disable the color output with: It also has support for single color definitions (local). You can disable/enable color output on the fly:

text is a repository of text-related packages related to internationalization (i18n) and localization (l10n), such as character encodings, text transformations, and locale-specific text handling.

Package github_flavored_markdown provides a GitHub Flavored Markdown renderer with fenced code block highlighting, clickable heading anchor links. The functionality should be equivalent to the GitHub Markdown API endpoint specified at https://developer.github.com/v3/markdown/#render-a-markdown-document-in-raw-mode, except the rendering is performed locally. See examples for how to generate a complete HTML page, including CSS styles.

ExampleCopyArtifactManifestRemoteToLocal gives an example of copying an artifact manifest from a remote repository into memory. ExampleExtendedCopyArtifactAndReferrersRemoteToLocal gives an example of copying an artifact along with its referrers from a remote repository into memory. ExamplePullFilesFromRemoteRepository gives an example of pulling files from a remote repository to the local file system. ExamplePullImageFromRemoteRepository gives an example of pulling an image from a remote repository to an OCI Image layout folder. ExamplePullImageUsingDockerCredentials gives an example of pulling an image from a remote repository to an OCI Image layout folder using Docker credentials. ExamplePushFilesToRemoteRepository gives an example of pushing local files to a remote repository.

Package skylark provides a Skylark interpreter. Skylark values are represented by the Value interface. The following built-in Value types are known to the evaluator: Client applications may define new data types that satisfy at least the Value interface. Such types may provide additional operations by implementing any of these optional interfaces: Client applications may also define domain-specific functions in Go and make them available to Skylark programs. Use NewBuiltin to construct a built-in value that wraps a Go function. The implementation of the Go function may use UnpackArgs to make sense of the positional and keyword arguments provided by the caller. Skylark's None value is not equal to Go's nil, but nil may be assigned to a Skylark Value. Be careful to avoid allowing Go nil values to leak into Skylark data structures. The Compare operation requires two arguments of the same type, but this constraint cannot be expressed in Go's type system. (This is the classic "binary method problem".) So, each Value type's CompareSameType method is a partial function that compares a value only against others of the same type. Use the package's standalone Compare (or Equal) function to compare an arbitrary pair of values. To parse and evaluate a Skylark source file, use ExecFile. The Eval function evaluates a single expression. All evaluator functions require a Thread parameter which defines the "thread-local storage" of a Skylark thread and may be used to plumb application state through Sklyark code and into callbacks. When evaluation fails it returns an EvalError from which the application may obtain a backtrace of active Skylark calls.

Package cadence and its subdirectories contain the Cadence client side framework. The Cadence service is a task orchestrator for your application’s tasks. Applications using Cadence can execute a logical flow of tasks, especially long-running business logic, asynchronously or synchronously. They can also scale at runtime on distributed systems. A quick example illustrates its use case. Consider Uber Eats where Cadence manages the entire business flow from placing an order, accepting it, handling shopping cart processes (adding, updating, and calculating cart items), entering the order in a pipeline (for preparing food and coordinating delivery), to scheduling delivery as well as handling payments. Cadence consists of a programming framework (or client library) and a managed service (or backend). The framework enables developers to author and coordinate tasks in Go code. The root cadence package contains common data structures. The subpackages are: The Cadence hosted service brokers and persists events generated during workflow execution. Worker nodes owned and operated by customers execute the coordination and task logic. To facilitate the implementation of worker nodes Cadence provides a client-side library for the Go language. In Cadence, you can code the logical flow of events separately as a workflow and code business logic as activities. The workflow identifies the activities and sequences them, while an activity executes the logic. Dynamic workflow execution graphs - Determine the workflow execution graphs at runtime based on the data you are processing. Cadence does not pre-compute the execution graphs at compile time or at workflow start time. Therefore, you have the ability to write workflows that can dynamically adjust to the amount of data they are processing. If you need to trigger 10 instances of an activity to efficiently process all the data in one run, but only 3 for a subsequent run, you can do that. Child Workflows - Orchestrate the execution of a workflow from within another workflow. Cadence will return the results of the child workflow execution to the parent workflow upon completion of the child workflow. No polling is required in the parent workflow to monitor status of the child workflow, making the process efficient and fault tolerant. Durable Timers - Implement delayed execution of tasks in your workflows that are robust to worker failures. Cadence provides two easy to use APIs, **workflow.Sleep** and **workflow.Timer**, for implementing time based events in your workflows. Cadence ensures that the timer settings are persisted and the events are generated even if workers executing the workflow crash. Signals - Modify/influence the execution path of a running workflow by pushing additional data directly to the workflow using a signal. Via the Signal facility, Cadence provides a mechanism to consume external events directly in workflow code. Task routing - Efficiently process large amounts of data using a Cadence workflow, by caching the data locally on a worker and executing all activities meant to process that data on that same worker. Cadence enables you to choose the worker you want to execute a certain activity by scheduling that activity execution in the worker's specific task-list. Unique workflow ID enforcement - Use business entity IDs for your workflows and let Cadence ensure that only one workflow is running for a particular entity at a time. Cadence implements an atomic "uniqueness check" and ensures that no race conditions are possible that would result in multiple workflow executions for the same workflow ID. Therefore, you can implement your code to attempt to start a workflow without checking if the ID is already in use, even in the cases where only one active execution per workflow ID is desired. Perpetual/ContinueAsNew workflows - Run periodic tasks as a single perpetually running workflow. With the "ContinueAsNew" facility, Cadence allows you to leverage the "unique workflow ID enforcement" feature for periodic workflows. Cadence will complete the current execution and start the new execution atomically, ensuring you get to keep your workflow ID. By starting a new execution Cadence also ensures that workflow execution history does not grow indefinitely for perpetual workflows. At-most once activity execution - Execute non-idempotent activities as part of your workflows. Cadence will not automatically retry activities on failure. For every activity execution Cadence will return a success result, a failure result, or a timeout to the workflow code and let the workflow code determine how each one of those result types should be handled. Asynch Activity Completion - Incorporate human input or thrid-party service asynchronous callbacks into your workflows. Cadence allows a workflow to pause execution on an activity and wait for an external actor to resume it with a callback. During this pause the activity does not have any actively executing code, such as a polling loop, and is merely an entry in the Cadence datastore. Therefore, the workflow is unaffected by any worker failures happening over the duration of the pause. Activity Heartbeating - Detect unexpected failures/crashes and track progress in long running activities early. By configuring your activity to report progress periodically to the Cadence server, you can detect a crash that occurs 10 minutes into an hour-long activity execution much sooner, instead of waiting for the 60-minute execution timeout. The recorded progress before the crash gives you sufficient information to determine whether to restart the activity from the beginning or resume it from the point of failure. Timeouts for activities and workflow executions - Protect against stuck and unresponsive activities and workflows with appropriate timeout values. Cadence requires that timeout values are provided for every activity or workflow invocation. There is no upper bound on the timeout values, so you can set timeouts that span days, weeks, or even months. Visibility - Get a list of all your active and/or completed workflow. Explore the execution history of a particular workflow execution. Cadence provides a set of visibility APIs that allow you, the workflow owner, to monitor past and current workflow executions. Debuggability - Replay any workflow execution history locally under a debugger. The Cadence client library provides an API to allow you to capture a stack trace from any failed workflow execution history.

Package dht implements a Distributed Hash Table (DHT) part of the BitTorrent protocol, as specified by BEP 5: http://www.bittorrent.org/beps/bep_0005.html BitTorrent uses a "distributed hash table" (DHT) for storing peer contact information for "trackerless" torrents. In effect, each peer becomes a tracker. The protocol is based on Kademila DHT protocol and is implemented over UDP. Please note the terminology used to avoid confusion. A "peer" is a client/server listening on a TCP port that implements the BitTorrent protocol. A "node" is a client/server listening on a UDP port implementing the distributed hash table protocol. The DHT is composed of nodes and stores the location of peers. BitTorrent clients include a DHT node, which is used to contact other nodes in the DHT to get the location of peers to download from using the BitTorrent protocol. Standard use involves creating a Server, and calling Announce on it with the details of your local torrent client and infohash of interest.

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

Ivy is an interpreter for an APL-like language. It is a plaything and a work in progress. Unlike APL, the input is ASCII and the results are exact (but see the next paragraph). It uses exact rational arithmetic so it can handle arbitrary precision. Values to be input may be integers (3, -1), rationals (1/3, -45/67) or floating point values (1e3, -1.5 (representing 1000 and -3/2)). Some functions such as sqrt are irrational. When ivy evaluates an irrational function, the result is stored in a high-precision floating-point number (default 256 bits of mantissa). Thus when using irrational functions, the values have high precision but are not exact. Unlike in most other languages, operators always have the same precedence and expressions are evaluated in right-associative order. That is, unary operators apply to everything to the right, and binary operators apply to the operand immediately to the left and to everything to the right. Thus, 3*4+5 is 27 (it groups as 3*(4+5)) and iota 3+2 is 1 2 3 4 5 while 3+iota 2 is 4 5. A vector is a single operand, so 1 2 3 + 3 + 3 4 5 is (1 2 3) + 3 + (3 4 5), or 7 9 11. As a special but important case, note that 1/3, with no intervening spaces, is a single rational number, not the expression 1 divided by 3. This can affect precedence: 3/6*4 is 2 while 3 / 6*4 is 1/8 since the spacing turns the / into a division operator. Use parentheses or spaces to disambiguate: 3/(6*4) or 3 /6*4. Ivy has complex numbers, which are constructed using the unary or binary j operator. As with rationals, the token 1j2 (the representation of 1+2i) is a single token. The individual parts can be rational, so 1/2j-3/2 is the complex number 0.5-1.5i and scans as a single value. Indexing uses [] notation: x[1], x[1; 2], and so on. Indexing by a vector selects multiple elements: x[1 2] creates a new item from x[1] and x[2]. An empty index slot is a shorthand for all the elements along that dimension, so x[] is equivalent to x, and x[;3] gives the third column of two-dimensional array x. Only a subset of APL's functionality is implemented, but all numerical operations are supported. Semicolons separate multiple statements on a line. Variables are alphanumeric and are assigned with the = operator. Assignment is an expression. After each successful expression evaluation, the result is stored in the variable called _ (underscore) so it can be used in the next expression. The APL operators, adapted from https://en.wikipedia.org/wiki/APL_syntax_and_symbols, and their correspondence are listed here. The correspondence is incomplete and inexact. Unary operators Binary operators Operators and axis indicator Type-converting operations The constants e (base of natural logarithms) and pi (π) are pre-defined to high precision, about 3000 decimal digits truncated according to the floating point precision setting. Strings are vectors of "chars", which are Unicode code points (not bytes). Syntactically, string literals are very similar to those in Go, with back-quoted raw strings and double-quoted interpreted strings. Unlike Go, single-quoted strings are equivalent to double-quoted, a nod to APL syntax. A string with a single char is just a singleton char value; all others are vectors. Thus “, "", and ” are empty vectors, `a`, "a", and 'a' are equivalent representations of a single char, and `ab`, `a` `b`, "ab", "a" "b", 'ab', and 'a' 'b' are equivalent representations of a two-char vector. Unlike in Go, a string in ivy comprises code points, not bytes; as such it can contain only valid Unicode values. Thus in ivy "\x80" is illegal, although it is a legal one-byte string in Go. Strings can be printed. If a vector contains only chars, it is printed without spaces between them. Chars have restricted operations. Printing, comparison, indexing and so on are legal but arithmetic is not, and chars cannot be converted automatically into other singleton values (ints, floats, and so on). The unary operators char and code enable transcoding between integer and char values. Users can define unary and binary operators, which then behave just like built-in operators. Both a unary and a binary operator may be defined for the same name. The syntax of a definition is the 'op' keyword, the operator and formal arguments, an equals sign, and then the body. The names of the operator and its arguments must be identifiers. For unary operators, write "op name arg"; for binary write "op leftarg name rightarg". The final expression in the body is the return value. Operators may have recursive definitions; see the paragraph about conditional execution for an example. The body may be a single line (possibly containing semicolons) on the same line as the 'op', or it can be multiple lines. For a multiline entry, there is a newline after the '=' and the definition ends at the first blank line (ignoring spaces). Conditional execution is done with the ":" binary conditional return operator, which is valid only within the code for a user-defined operator. The left operand must be a scalar. If it is non-zero, the right operand is returned as the value of the function. Otherwise, execution continues normally. The ":" operator has a lower precedence than any other operator; in effect it breaks the line into two separate expressions. Example: average of a vector (unary): Example: n largest entries in a vector (binary): Example: multiline operator definition (binary): Example: primes less than N (unary): Example: greatest common divisor (binary): On mobile platforms only, due to I/O restrictions, user-defined operators must be presented on a single line. Use semicolons to separate expressions: To declare an operator but not define it, omit the equals sign and what follows. Within a user-defined operator body, identifiers are local to the invocation if they are assigned before being read, and global if read before being written. To write to a global without reading it first, insert an unused read. To remove the definition of a unary or binary user-defined operator, Ivy accepts a number of special commands, introduced by a right paren at the beginning of the line. Most report the current value if a new value is not specified. For these commands, numbers are always read and printed base 10 and must be non-negative on input.

Package arikawa contains a set of modular packages that allows you to make a Discord bot or any type of session (OAuth unsupported). Package session is the most simple abstraction, which combines the API package and the Gateway websocket package together into one. This could be used for minimal bots that only use gateway events and such. Package state abstracts on top of session and provides a local cache of API calls and events. Bots that either don't need a command router or already has its own should use this package. Package bot abstracts on top of state and provides a command router based on Go code. This is similar to discord.py's API, only it's Go and there's no optional arguments (yet, although it could be worked around). Most bots are recommended to use this package, as it's the easiest way to make a bot. Package voice provides an abstraction on top of State and adds voice support. This allows bots to join voice channels and talk. The package uses an io.Writer approach rather than a channel, contrary to other Discord libraries.

Package groupcache provides a data loading mechanism with caching and de-duplication that works across a set of peer processes. Each data Get first consults its local cache, otherwise delegates to the requested key's canonical owner, which then checks its cache or finally gets the data. In the common case, many concurrent cache misses across a set of peers for the same key result in just one cache fill.

Package log provides a structured logger. Structured logging produces logs easily consumed later by humans or machines. Humans might be interested in debugging errors, or tracing specific requests. Machines might be interested in counting interesting events, or aggregating information for off-line processing. In both cases, it is important that the log messages are structured and actionable. Package log is designed to encourage both of these best practices. The fundamental interface is Logger. Loggers create log events from key/value data. The Logger interface has a single method, Log, which accepts a sequence of alternating key/value pairs, which this package names keyvals. Here is an example of a function using a Logger to create log events. The keys in the above example are "taskID" and "event". The values are task.ID, "starting task", and "task complete". Every key is followed immediately by its value. Keys are usually plain strings. Values may be any type that has a sensible encoding in the chosen log format. With structured logging it is a good idea to log simple values without formatting them. This practice allows the chosen logger to encode values in the most appropriate way. A contextual logger stores keyvals that it includes in all log events. Building appropriate contextual loggers reduces repetition and aids consistency in the resulting log output. With, WithPrefix, and WithSuffix add context to a logger. We can use With to improve the RunTask example. The improved version emits the same log events as the original for the first and last calls to Log. Passing the contextual logger to taskHelper enables each log event created by taskHelper to include the task.ID even though taskHelper does not have access to that value. Using contextual loggers this way simplifies producing log output that enables tracing the life cycle of individual tasks. (See the Contextual example for the full code of the above snippet.) A Valuer function stored in a contextual logger generates a new value each time an event is logged. The Valuer example demonstrates how this feature works. Valuers provide the basis for consistently logging timestamps and source code location. The log package defines several valuers for that purpose. See Timestamp, DefaultTimestamp, DefaultTimestampUTC, Caller, and DefaultCaller. A common logger initialization sequence that ensures all log entries contain a timestamp and source location looks like this: Applications with multiple goroutines want each log event written to the same logger to remain separate from other log events. Package log provides two simple solutions for concurrent safe logging. NewSyncWriter wraps an io.Writer and serializes each call to its Write method. Using a SyncWriter has the benefit that the smallest practical portion of the logging logic is performed within a mutex, but it requires the formatting Logger to make only one call to Write per log event. NewSyncLogger wraps any Logger and serializes each call to its Log method. Using a SyncLogger has the benefit that it guarantees each log event is handled atomically within the wrapped logger, but it typically serializes both the formatting and output logic. Use a SyncLogger if the formatting logger may perform multiple writes per log event. This package relies on the practice of wrapping or decorating loggers with other loggers to provide composable pieces of functionality. It also means that Logger.Log must return an error because some implementations—especially those that output log data to an io.Writer—may encounter errors that cannot be handled locally. This in turn means that Loggers that wrap other loggers should return errors from the wrapped logger up the stack. Fortunately, the decorator pattern also provides a way to avoid the necessity to check for errors every time an application calls Logger.Log. An application required to panic whenever its Logger encounters an error could initialize its logger as follows.

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 temporal and its subdirectories contain the Temporal client side framework. The Temporal service is a task orchestrator for your application’s tasks. Applications using Temporal can execute a logical flow of tasks, especially long-running business logic, asynchronously or synchronously. They can also scale at runtime on distributed systems. A quick example illustrates its use case. Consider Uber Eats where Temporal manages the entire business flow from placing an order, accepting it, handling shopping cart processes (adding, updating, and calculating cart items), entering the order in a pipeline (for preparing food and coordinating delivery), to scheduling delivery as well as handling payments. Temporal consists of a programming framework (or client library) and a managed service (or backend). The framework enables developers to author and coordinate tasks in Go code. The root temporal package contains common data structures. The subpackages are: The Temporal hosted service brokers and persists events generated during workflow execution. Worker nodes owned and operated by customers execute the coordination and task logic. To facilitate the implementation of worker nodes Temporal provides a client-side library for the Go language. In Temporal, you can code the logical flow of events separately as a workflow and code business logic as activities. The workflow identifies the activities and sequences them, while an activity executes the logic. Dynamic workflow execution graphs - Determine the workflow execution graphs at runtime based on the data you are processing. Temporal does not pre-compute the execution graphs at compile time or at workflow start time. Therefore, you have the ability to write workflows that can dynamically adjust to the amount of data they are processing. If you need to trigger 10 instances of an activity to efficiently process all the data in one run, but only 3 for a subsequent run, you can do that. Child Workflows - Orchestrate the execution of a workflow from within another workflow. Temporal will return the results of the child workflow execution to the parent workflow upon completion of the child workflow. No polling is required in the parent workflow to monitor status of the child workflow, making the process efficient and fault tolerant. Durable Timers - Implement delayed execution of tasks in your workflows that are robust to worker failures. Temporal provides two easy to use APIs, **workflow.Sleep** and **workflow.Timer**, for implementing time based events in your workflows. Temporal ensures that the timer settings are persisted and the events are generated even if workers executing the workflow crash. Signals - Modify/influence the execution path of a running workflow by pushing additional data directly to the workflow using a signal. Via the Signal facility, Temporal provides a mechanism to consume external events directly in workflow code. Task routing - Efficiently process large amounts of data using a Temporal workflow, by caching the data locally on a worker and executing all activities meant to process that data on that same worker. Temporal enables you to choose the worker you want to execute a certain activity by scheduling that activity execution in the worker's specific task queue. Unique workflow ID enforcement - Use business entity IDs for your workflows and let Temporal ensure that only one workflow is running for a particular entity at a time. Temporal implements an atomic "uniqueness check" and ensures that no race conditions are possible that would result in multiple workflow executions for the same workflow ID. Therefore, you can implement your code to attempt to start a workflow without checking if the ID is already in use, even in the cases where only one active execution per workflow ID is desired. Perpetual/ContinueAsNew workflows - Run periodic tasks as a single perpetually running workflow. With the "ContinueAsNew" facility, Temporal allows you to leverage the "unique workflow ID enforcement" feature for periodic workflows. Temporal will complete the current execution and start the new execution atomically, ensuring you get to keep your workflow ID. By starting a new execution Temporal also ensures that workflow execution history does not grow indefinitely for perpetual workflows. At-most once activity execution - Execute non-idempotent activities as part of your workflows. Temporal will not automatically retry activities on failure. For every activity execution Temporal will return a success result, a failure result, or a timeout to the workflow code and let the workflow code determine how each one of those result types should be handled. Asynch Activity Completion - Incorporate human input or thrid-party service asynchronous callbacks into your workflows. Temporal allows a workflow to pause execution on an activity and wait for an external actor to resume it with a callback. During this pause the activity does not have any actively executing code, such as a polling loop, and is merely an entry in the Temporal datastore. Therefore, the workflow is unaffected by any worker failures happening over the duration of the pause. Activity Heartbeating - Detect unexpected failures/crashes and track progress in long running activities early. By configuring your activity to report progress periodically to the Temporal server, you can detect a crash that occurs 10 minutes into an hour-long activity execution much sooner, instead of waiting for the 60-minute execution timeout. The recorded progress before the crash gives you sufficient information to determine whether to restart the activity from the beginning or resume it from the point of failure. Timeouts for activities and workflow executions - Protect against stuck and unresponsive activities and workflows with appropriate timeout values. Temporal requires that timeout values are provided for every activity or workflow invocation. There is no upper bound on the timeout values, so you can set timeouts that span days, weeks, or even months. Visibility - Get a list of all your active and/or completed workflow. Explore the execution history of a particular workflow execution. Temporal provides a set of visibility APIs that allow you, the workflow owner, to monitor past and current workflow executions. Debuggability - Replay any workflow execution history locally under a debugger. The Temporal client library provides an API to allow you to capture a stack trace from any failed workflow execution history.

Package arikawa contains a set of modular packages that allows you to make a Discord bot or any type of session (OAuth unsupported). Package session is the most simple abstraction, which combines the API package and the Gateway websocket package together into one. This could be used for minimal bots that only use gateway events and such. Package state abstracts on top of session and provides a local cache of API calls and events. Bots that either don't need a command router or already has its own should use this package. Package bot abstracts on top of state and provides a command router based on Go code. This is similar to discord.py's API, only it's Go and there's no optional arguments (yet, although it could be worked around). Most bots are recommended to use this package, as it's the easiest way to make a bot. Package voice provides an abstraction on top of State and adds voice support. This allows bots to join voice channels and talk. The package uses an io.Writer approach rather than a channel, contrary to other Discord libraries.

Package gcs provides an API for building and using a Golomb-coded set filter. A Golomb-Coded Set (GCS) is a space-efficient probabilistic data structure that is used to test set membership with a tunable false positive rate while simultaneously preventing false negatives. In other words, items that are in the set will always match, but items that are not in the set will also sometimes match with the chosen false positive rate. This package currently implements two different versions for backwards compatibility. Version 1 is deprecated and therefore should no longer be used. Version 2 is the GCS variation that follows the specification details in DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#golomb-coded-sets. Version 2 sets do not permit empty items (data of zero length) to be added and are parameterized by the following: * A parameter `B` that defines the remainder code bit size * A parameter `M` that defines the false positive rate as `1/M` * A key for the SipHash-2-4 function * The items to include in the set The errors returned by this package are of type gcs.Error. This allows the caller to programmatically determine the specific error by examining the ErrorKind field of the type asserted gcs.Error while still providing rich error messages with contextual information. See ErrorKind in the package documentation for a full list. GCS is used as a mechanism for storing, transmitting, and committing to per-block filters. Consensus-validating full nodes commit to a single filter for every block and serve the filter to SPV clients that match against the filter locally to determine if the block is potentially relevant. The required parameters for Decred are defined by the blockcf2 package. For more details, see the Block Filters section of DCP0005: https://github.com/decred/dcps/blob/master/dcp-0005/dcp-0005.mediawiki#block-filters

Package snowball provides the API client, operations, and parameter types for Amazon Import/Export Snowball. The Amazon Web Services Snow Family provides a petabyte-scale data transport solution that uses secure devices to transfer large amounts of data between your on-premises data centers and Amazon Simple Storage Service (Amazon S3). The Snow Family commands described here provide access to the same functionality that is available in the Amazon Web Services Snow Family Management Console, which enables you to create and manage jobs for a Snow Family device. To transfer data locally with a Snow Family device, you'll need to use the Snowball Edge client or the Amazon S3 API Interface for Snowball or OpsHub for Snow Family. For more information, see the User Guide.

Package arikawa contains a set of modular packages that allows you to make a Discord bot or any type of session (OAuth unsupported). Package session is the most simple abstraction, which combines the API package and the Gateway websocket package together into one. This could be used for minimal bots that only use gateway events and such. Package state abstracts on top of session and provides a local cache of API calls and events. Bots that either don't need a command router or already has its own should use this package. Package bot abstracts on top of state and provides a command router based on Go code. This is similar to discord.py's API, only it's Go and there's no optional arguments (yet, although it could be worked around). Most bots are recommended to use this package, as it's the easiest way to make a bot. Package voice provides an abstraction on top of State and adds voice support. This allows bots to join voice channels and talk. The package uses an io.Writer approach rather than a channel, contrary to other Discord libraries.

Package ora implements an Oracle database driver. ### Golang Oracle Database Driver ### #### TL;DR; just use it #### Call stored procedure with OUT parameters: An Oracle database may be accessed through the database/sql(http://golang.org/pkg/database/sql) package or through the ora package directly. database/sql offers connection pooling, thread safety, a consistent API to multiple database technologies and a common set of Go types. The ora package offers additional features including pointers, slices, nullable types, numerics of various sizes, Oracle-specific types, Go return type configuration, and Oracle abstractions such as environment, server and session. The ora package is written with the Oracle Call Interface (OCI) C-language libraries provided by Oracle. The OCI libraries are a standard for client application communication and driver communication with Oracle databases. The ora package has been verified to work with: * Oracle Standard 11g (11.2.0.4.0), Linux x86_64 (RHEL6) * Oracle Enterprise 12c (12.1.0.1.0), Windows 8.1 and AMD64. --- * [Installation](https://github.com/rana/ora#installation) * [Data Types](https://github.com/rana/ora#data-types) * [SQL Placeholder Syntax](https://github.com/rana/ora#sql-placeholder-syntax) * [Working With The Sql Package](https://github.com/rana/ora#working-with-the-sql-package) * [Working With The Oracle Package Directly](https://github.com/rana/ora#working-with-the-oracle-package-directly) * [Logging](https://github.com/rana/ora#logging) * [Test Database Setup](https://github.com/rana/ora#test-database-setup) * [Limitations](https://github.com/rana/ora#limitations) * [License](https://github.com/rana/ora#license) * [API Reference](http://godoc.org/github.com/rana/ora#pkg-index) * [Examples](./examples) --- Minimum requirements are Go 1.3 with CGO enabled, a GCC C compiler, and Oracle 11g (11.2.0.4.0) or Oracle Instant Client (11.2.0.4.0). Install Oracle or Oracle Instant Client. Copy the [oci8.pc](contrib/oci8.pc) from the `contrib` folder (or the one for your system, maybe tailored to your specific locations) to a folder in `$PKG_CONFIG_PATH` or a system folder, such as The ora package has no external Go dependencies and is available on GitHub and gopkg.in: *WARNING*: If you have Oracle Instant Client 11.2, you'll need to add "=lnnz11" to the list of linked libs! Otherwise, you may encounter "undefined reference to `nzosSCSP_SetCertSelectionParams' " errors. Oracle Instant Client 12.1 does not need this. The ora package supports all built-in Oracle data types. The supported Oracle built-in data types are NUMBER, BINARY_DOUBLE, BINARY_FLOAT, FLOAT, DATE, TIMESTAMP, TIMESTAMP WITH TIME ZONE, TIMESTAMP WITH LOCAL TIME ZONE, INTERVAL YEAR TO MONTH, INTERVAL DAY TO SECOND, CHAR, NCHAR, VARCHAR, VARCHAR2, NVARCHAR2, LONG, CLOB, NCLOB, BLOB, LONG RAW, RAW, ROWID and BFILE. SYS_REFCURSOR is also supported. Oracle does not provide a built-in boolean type. Oracle provides a single-byte character type. A common practice is to define two single-byte characters which represent true and false. The ora package adopts this approach. The oracle package associates a Go bool value to a Go rune and sends and receives the rune to a CHAR(1 BYTE) column or CHAR(1 CHAR) column. The default false rune is zero '0'. The default true rune is one '1'. The bool rune association may be configured or disabled when directly using the ora package but not with the database/sql package. Within a SQL string a placeholder may be specified to indicate where a Go variable is placed. The SQL placeholder is an Oracle identifier, from 1 to 30 characters, prefixed with a colon (:). For example: Placeholders within a SQL statement are bound by position. The actual name is not used by the ora package driver e.g., placeholder names :c1, :1, or :xyz are treated equally. The `database/sql` package provides a LastInsertId method to return the last inserted row's id. Oracle does not provide such functionality, but if you append `... RETURNING col /*LastInsertId*/` to your SQL, then it will be presented as LastInsertId. Note that you have to mark with a `/*LastInsertId*/` (case insensitive) your `RETURNING` part, to allow ora to return the last column as `LastInsertId()`. That column must fit in `int64`, though! You may access an Oracle database through the database/sql package. The database/sql package offers a consistent API across different databases, connection pooling, thread safety and a set of common Go types. database/sql makes working with Oracle straight-forward. The ora package implements interfaces in the database/sql/driver package enabling database/sql to communicate with an Oracle database. Using database/sql ensures you never have to call the ora package directly. When using database/sql, the mapping between Go types and Oracle types may be changed slightly. The database/sql package has strict expectations on Go return types. The Go-to-Oracle type mapping for database/sql is: The "ora" driver is automatically registered for use with sql.Open, but you can call ora.SetCfg to set the used configuration options including statement configuration and Rset configuration. When configuring the driver for use with database/sql, keep in mind that database/sql has strict Go type-to-Oracle type mapping expectations. The ora package allows programming with pointers, slices, nullable types, numerics of various sizes, Oracle-specific types, Go return type configuration, and Oracle abstractions such as environment, server and session. When working with the ora package directly, the API is slightly different than database/sql. When using the ora package directly, the mapping between Go types and Oracle types may be changed. The Go-to-Oracle type mapping for the ora package is: An example of using the ora package directly: Pointers may be used to capture out-bound values from a SQL statement such as an insert or stored procedure call. For example, a numeric pointer captures an identity value: A string pointer captures an out parameter from a stored procedure: Slices may be used to insert multiple records with a single insert statement: The ora package provides nullable Go types to support DML operations such as insert and select. The nullable Go types provided by the ora package are Int64, Int32, Int16, Int8, Uint64, Uint32, Uint16, Uint8, Float64, Float32, Time, IntervalYM, IntervalDS, String, Bool, Binary and Bfile. For example, you may insert nullable Strings and select nullable Strings: The `Stmt.Prep` method is variadic accepting zero or more `GoColumnType` which define a Go return type for a select-list column. For example, a Prep call can be configured to return an int64 and a nullable Int64 from the same column: Go numerics of various sizes are supported in DML operations. The ora package supports int64, int32, int16, int8, uint64, uint32, uint16, uint8, float64 and float32. For example, you may insert a uint16 and select numerics of various sizes: If a non-nullable type is defined for a nullable column returning null, the Go type's zero value is returned. GoColumnTypes defined by the ora package are: When Stmt.Prep doesn't receive a GoColumnType, or receives an incorrect GoColumnType, the default value defined in RsetCfg is used. EnvCfg, SrvCfg, SesCfg, StmtCfg and RsetCfg are the main configuration structs. EnvCfg configures aspects of an Env. SrvCfg configures aspects of a Srv. SesCfg configures aspects of a Ses. StmtCfg configures aspects of a Stmt. RsetCfg configures aspects of Rset. StmtCfg and RsetCfg have the most options to configure. RsetCfg defines the default mapping between an Oracle select-list column and a Go type. StmtCfg may be set in an EnvCfg, SrvCfg, SesCfg and StmtCfg. RsetCfg may be set in a Stmt. EnvCfg.StmtCfg, SrvCfg.StmtCfg, SesCfg.StmtCfg may optionally be specified to configure a statement. If StmtCfg isn't specified default values are applied. EnvCfg.StmtCfg, SrvCfg.StmtCfg, SesCfg.StmtCfg cascade to new descendent structs. When ora.OpenEnv() is called a specified EnvCfg is used or a default EnvCfg is created. Creating a Srv with env.OpenSrv() will use SrvCfg.StmtCfg if it is specified; otherwise, EnvCfg.StmtCfg is copied by value to SrvCfg.StmtCfg. Creating a Ses with srv.OpenSes() will use SesCfg.StmtCfg if it is specified; otherwise, SrvCfg.StmtCfg is copied by value to SesCfg.StmtCfg. Creating a Stmt with ses.Prep() will use SesCfg.StmtCfg if it is specified; otherwise, a new StmtCfg with default values is set on the Stmt. Call Stmt.Cfg() to change a Stmt's configuration. An Env may contain multiple Srv. A Srv may contain multiple Ses. A Ses may contain multiple Stmt. A Stmt may contain multiple Rset. Setting a RsetCfg on a StmtCfg does not cascade through descendent structs. Configuration of Stmt.Cfg takes effect prior to calls to Stmt.Exe and Stmt.Qry; consequently, any updates to Stmt.Cfg after a call to Stmt.Exe or Stmt.Qry are not observed. One configuration scenario may be to set a server's select statements to return nullable Go types by default: Another scenario may be to configure the runes mapped to bool values: Oracle-specific types offered by the ora package are ora.Rset, ora.IntervalYM, ora.IntervalDS, ora.Raw, ora.Lob and ora.Bfile. ora.Rset represents an Oracle SYS_REFCURSOR. ora.IntervalYM represents an Oracle INTERVAL YEAR TO MONTH. ora.IntervalDS represents an Oracle INTERVAL DAY TO SECOND. ora.Raw represents an Oracle RAW or LONG RAW. ora.Lob may represent an Oracle BLOB or Oracle CLOB. And ora.Bfile represents an Oracle BFILE. ROWID columns are returned as strings and don't have a unique Go type. #### LOBs The default for SELECTing [BC]LOB columns is a safe Bin or S, which means all the contents of the LOB is slurped into memory and returned as a []byte or string. The DefaultLOBFetchLen says LOBs are prefetched only a minimal way, to minimize extra memory usage - you can override this using `stmt.SetCfg(stmt.Cfg().SetLOBFetchLen(100))`. If you want more control, you can use ora.L in Prep, Qry or `ses.SetCfg(ses.Cfg().SetBlob(ora.L))`. But keep in mind that Oracle restricts the use of LOBs: it is forbidden to do ANYTHING while reading the LOB! No another query, no exec, no close of the Rset - even *advance* to the next record in the result set is forbidden! Failing to adhere these rules results in "Invalid handle" and ORA-03127 errors. You cannot start reading another LOB till you haven't finished reading the previous LOB, not even in the same row! Failing this results in ORA-24804! For examples, see [z_lob_test.go](z_lob_test.go). #### Rset Rset is used to obtain Go values from a SQL select statement. Methods Rset.Next, Rset.NextRow, and Rset.Len are available. Fields Rset.Row, Rset.Err, Rset.Index, and Rset.ColumnNames are also available. The Next method attempts to load data from an Oracle buffer into Row, returning true when successful. When no data is available, or if an error occurs, Next returns false setting Row to nil. Any error in Next is assigned to Err. Calling Next increments Index and method Len returns the total number of rows processed. The NextRow method is convenient for returning a single row. NextRow calls Next and returns Row. ColumnNames returns the names of columns defined by the SQL select statement. Rset has two usages. Rset may be returned from Stmt.Qry when prepared with a SQL select statement: Or, *Rset may be passed to Stmt.Exe when prepared with a stored procedure accepting an OUT SYS_REFCURSOR parameter: Stored procedures with multiple OUT SYS_REFCURSOR parameters enable a single Exe call to obtain multiple Rsets: The types of values assigned to Row may be configured in StmtCfg.Rset. For configuration to take effect, assign StmtCfg.Rset prior to calling Stmt.Qry or Stmt.Exe. Rset prefetching may be controlled by StmtCfg.PrefetchRowCount and StmtCfg.PrefetchMemorySize. PrefetchRowCount works in coordination with PrefetchMemorySize. When PrefetchRowCount is set to zero only PrefetchMemorySize is used; otherwise, the minimum of PrefetchRowCount and PrefetchMemorySize is used. The default uses a PrefetchMemorySize of 134MB. Opening and closing Rsets is managed internally. Rset does not have an Open method or Close method. IntervalYM may be be inserted and selected: IntervalDS may be be inserted and selected: Transactions on an Oracle server are supported. DML statements auto-commit unless a transaction has started: Ses.PrepAndExe, Ses.PrepAndQry, Ses.Ins, Ses.Upd, and Ses.Sel are convenient one-line methods. Ses.PrepAndExe offers a convenient one-line call to Ses.Prep and Stmt.Exe. Ses.PrepAndQry offers a convenient one-line call to Ses.Prep and Stmt.Qry. Ses.Ins composes, prepares and executes a sql INSERT statement. Ses.Ins is useful when you have to create and maintain a simple INSERT statement with a long list of columns. As table columns are added and dropped over the lifetime of a table Ses.Ins is easy to read and revise. Ses.Upd composes, prepares and executes a sql UPDATE statement. Ses.Upd is useful when you have to create and maintain a simple UPDATE statement with a long list of columns. As table columns are added and dropped over the lifetime of a table Ses.Upd is easy to read and revise. Ses.Sel composes, prepares and queries a sql SELECT statement. Ses.Sel is useful when you have to create and maintain a simple SELECT statement with a long list of columns that have non-default GoColumnTypes. As table columns are added and dropped over the lifetime of a table Ses.Sel is easy to read and revise. The Ses.Ping method checks whether the client's connection to an Oracle server is valid. A call to Ping requires an open Ses. Ping will return a nil error when the connection is fine: The Srv.Version method is available to obtain the Oracle server version. A call to Version requires an open Ses: Further code examples are available in the [example file](https://github.com/rana/ora/blob/master/z_example_test.go), test files and [samples folder](https://github.com/rana/ora/tree/master/samples). The ora package provides a simple ora.Logger interface for logging. Logging is disabled by default. Specify one of three optional built-in logging packages to enable logging; or, use your own logging package. ora.Cfg().Log offers various options to enable or disable logging of specific ora driver methods. For example: To use the standard Go log package: which produces a sample log of: Messages are prefixed with 'ORA I' for information or 'ORA E' for an error. The log package is configured to write to os.Stderr by default. Use the ora/lg.Std type to configure an alternative io.Writer. To use the glog package: which produces a sample log of: To use the log15 package: which produces a sample log of: See https://github.com/rana/ora/tree/master/samples/lg15/main.go for sample code which uses the log15 package. Tests are available and require some setup. Setup varies depending on whether the Oracle server is configured as a container database or non-container database. It's simpler to setup a non-container database. An example for each setup is explained. Non-container test database setup steps: Container test database setup steps: Some helpful SQL maintenance statements: Run the tests. database/sql method Stmt.QueryRow is not supported. Go 1.6 introduced stricter cgo (call C from Go) rules, and introduced runtime checks. This is good, as the possibility of C code corrupting Go code is almost completely eliminated, but it also means a severe call overhead grow. [Sometimes](https://groups.google.com/forum/#!topic/golang-nuts/ccMkPG6Bi5k) this can be 22x the go 1.5.3 call time! So if you need performance more than correctness, start your programs with "GODEBUG=cgocheck=0" environment setting. Copyright 2017 Rana Ian, Tamás Gulácsi. All rights reserved. Use of this source code is governed by The MIT License found in the accompanying LICENSE file.

Package monday is a minimalistic translator for month and day of week names in time.Date objects Monday is not an alternative to standard time package. It is a temporary solution to use while the internationalization features are not ready. That's why monday doesn't create any additional parsing algorithms, layout identifiers. It is just a wrapper for time.Format and time.ParseInLocation and uses all the same layout IDs, constants, etc. Format usage: Parse usage: Monday initializes all its data once in the init func and then uses only func calls and local vars. Thus, it's thread-safe and doesn't need any mutexes to be used with.

Package gomarkdoc formats documentation for one or more packages as markdown for usage outside of the main https://pkg.go.dev site. It supports custom templates for tweaking representation of documentation at fine-grained levels, exporting both exported and unexported symbols, and custom formatters for different backends. If you want to use this package as a command-line tool, you can install the command by running the following on go 1.16+: For older versions of go, you can install using the following method instead: The command line tool supports configuration for all of the features of the importable package: The gomarkdoc command processes each of the provided packages, generating documentation for the package in markdown format and writing it to console. For example, if you have a package in your current directory and want to send it to a documentation markdown file, you might do something like this: The gomarkdoc tool supports generating documentation for both local packages and remote ones. To specify a local package, start the name of the package with a period (.) or specify an absolute path on the filesystem. All other package signifiers are assumed to be remote packages. You may specify both local and remote packages in the same command invocation as separate arguments. If you have a project with many packages but you want to skip documentation generation for some, you can use the --exclude-dirs option. This will remove any matching directories from the list of directories to process. Excluded directories are specified using the same pathing syntax as the packages to process. Multiple expressions may be comma-separated or specified by using the --exclude-dirs flag multiple times. For example, in this repository we generate documentation for the entire project while excluding our test packages by running: By default, the documentation generated by the gomarkdoc command is sent to standard output, where it can be redirected to a file. This can be useful if you want to perform additional modifications to the documentation or send it somewhere other than a file. However, keep in mind that there are some inconsistencies in how various shells/platforms handle redirected command output (for example, Powershell encodes in UTF-16, not UTF-8). As a result, the --output option described below is recommended for most use cases. If you want to redirect output for each processed package to a file, you can provide the --output/-o option, which accepts a template specifying how to generate the path of the output file. A common usage of this option is when generating README documentation for a package with subpackages (which are supported via the ... signifier as in other parts of the golang toolchain). In addition, this option provides consistent behavior across platforms and shells: You can see all of the data available to the output template in the PackageSpec struct in the github.com/princjef/gomarkdoc/cmd/gomarkdoc package. The documentation information that is output is formatted using a series of text templates for the various components of the overall documentation which get generated. Higher level templates contain lower level templates, but any template may be replaced with an override template using the --template/-t option. The full list of templates that may be overridden are: file: generates documentation for a file containing one or more packages, depending on how the tool is configured. This is the root template for documentation generation. package: generates documentation for an entire package. type: generates documentation for a single type declaration, as well as any related functions/methods. func: generates documentation for a single function or method. It may be referenced from within a type, or directly in the package, depending on nesting. value: generates documentation for a single variable or constant declaration block within a package. index: generates an index of symbols within a package, similar to what is seen for godoc.org. The index links to types, funcs, variables, and constants generated by other templates, so it may need to be overridden as well if any of those templates are changed in a material way. example: generates documentation for a single example for a package or one of its symbols. The example is generated alongside whichever symbol it represents, based on the standard naming conventions outlined in https://blog.golang.org/examples#TOC_4. doc: generates the freeform documentation block for any of the above structures that can contain a documentation section. import: generates the import code used to pull in a package. Overriding with the --template-file option uses a key-value pair mapping a template name to the file containing the contents of the override template to use. Specified template files must exist: As with the godoc tool itself, only exported symbols will be shown in documentation. This can be expanded to include all symbols in a package by adding the --include-unexported/-u flag. If you want to blend the documentation generated by gomarkdoc with your own hand-written markdown, you can use the --embed/-e flag to change the gomarkdoc tool into an append/embed mode. When documentation is generated, gomarkdoc looks for a file in the location where the documentation is to be written and embeds the documentation if present. Otherwise, the documentation is appended to the end of the file. When running with embed mode enabled, gomarkdoc will look for either this single comment: Or the following pair of comments (in which case all content in between is replaced): If you would like to include files that are part of a build tag, you can specify build tags with the --tags flag. Tags are also supported through GOFLAGS, though command line and configuration file definitions override tags specified through GOFLAGS. You can also run gomarkdoc in a verification mode with the --check/-c flag. This is particularly useful for continuous integration when you want to make sure that a commit correctly updated the generated documentation. This flag is only supported when the --output/-o flag is specified, as the file provided there is what the tool is checking: If you're experiencing difficulty with gomarkdoc or just want to get more information about how it's executing underneath, you can add -v to show more logs. This can be chained a second time to show even more verbose logs: Some features of gomarkdoc rely on being able to detect information from the git repository containing the project. Since individual local git repositories may be configured differently from person to person, you may want to manually specify the information for the repository to remove any inconsistencies. This can be achieved with the --repository.url, --repository.default-branch and --repository.path options. For example, this repository would be configured with: If you want to reuse configuration options across multiple invocations, you can specify a file in the folder where you invoke gomarkdoc containing configuration information that you would otherwise provide on the command line. This file may be a JSON, TOML, YAML, HCL, env, or Java properties file, but the name is expected to start with .gomarkdoc (e.g. .gomarkdoc.yml). All configuration options are available with the camel-cased form of their long name (e.g. --include-unexported becomes includeUnexported). Template overrides are specified as a map, rather than a set of key-value pairs separated by =. Options provided on the command line override those provided in the configuration file if an option is present in both. While most users will find the command line utility sufficient for their needs, this package may also be used programmatically by installing it directly, rather than its command subpackage. The programmatic usage provides more flexibility when selecting what packages to work with and what components to generate documentation for. A common usage will look something like this: This project uses itself to generate the README files in github.com/princjef/gomarkdoc and its subdirectories. To see the commands that are run to generate documentation for this repository, take a look at the Doc() and DocVerify() functions in magefile.go and the .gomarkdoc.yml file in the root of this repository. To run these commands in your own project, simply replace `go run ./cmd/gomarkdoc` with `gomarkdoc`. Know of another project that is using gomarkdoc? Open an issue with a description of the project and link to the repository and it might be featured here!

Fully featured and highly configurable SFTP server with optional FTP/S and WebDAV support. It can serve local filesystem, S3 or Google Cloud Storage. For more details about features, installation, configuration and usage please refer to the README inside the source tree: https://github.com/drakkan/sftpgo/blob/master/README.md

Package cmds helps building both standalone and client-server applications. The basic building blocks are requests, commands, emitters and responses. A command consists of a description of the parameters and a function. The function is passed the request as well as an emitter as arguments. It does operations on the inputs and sends the results to the user by emitting them. There are a number of emitters in this package and subpackages, but the user is free to create their own. A command is a struct containing the commands help text, a description of the arguments and options, the command's processing function and a type to let the caller know what type will be emitted. Optionally one of the functions PostRun and Encoder may be defined that consumes the function's emitted values and generates a visual representation for e.g. the terminal. Encoders work on a value-by-value basis, while PostRun operates on the value stream. An emitter has the Emit method, that takes the command's function's output as an argument and passes it to the user. The command's function does not know what kind of emitter it works with, so the same function may run locally or on a server, using an rpc interface. Emitters can also send errors using the SetError method. The user-facing emitter usually is the cli emitter. Values emitter here will be printed to the terminal using either the Encoders or the PostRun function. A response is a value that the user can read emitted values from. Responses have a method Next() that returns the next emitted value and an error value. If the last element has been received, the returned error value is io.EOF. If the application code has sent an error using SetError, the error ErrRcvdError is returned on next, indicating that the caller should call Error(). Depending on the reponse type, other errors may also occur. Pipes are pairs (emitter, response), such that a value emitted on the emitter can be received in the response value. Most builtin emitters are "pipe" emitters. The most prominent examples are the channel pipe and the http pipe. The channel pipe is backed by a channel. The only error value returned by the response is io.EOF, which happens when the channel is closed. The http pipe is backed by an http connection. The response can also return other errors, e.g. if there are errors on the network. To get a better idea of what's going on, take a look at the examples at https://github.com/ipfs/go-ipfs-cmds/tree/master/examples.

Pact Go enables consumer driven contract testing, providing a mock service and DSL for the consumer project, and interaction playback and verification for the service provider project. Consumer side Pact testing is an isolated test that ensures a given component is able to collaborate with another (remote) component. Pact will automatically start a Mock server in the background that will act as the collaborators' test double. This implies that any interactions expected on the Mock server will be validated, meaning a test will fail if all interactions were not completed, or if unexpected interactions were found: A typical consumer-side test would look something like this: If this test completed successfully, a Pact file should have been written to ./pacts/my_consumer-my_provider.json containing all of the interactions expected to occur between the Consumer and Provider. In addition to verbatim value matching, you have 3 useful matching functions in the `dsl` package that can increase expressiveness and reduce brittle test cases. Here is a complex example that shows how all 3 terms can be used together: This example will result in a response body from the mock server that looks like: See the examples in the dsl package and the matcher tests (https://github.com/pact-foundation/pact-go/v2/blob/master/dsl/matcher_test.go) for more matching examples. NOTE: You will need to use valid Ruby regular expressions (http://ruby-doc.org/core-2.1.5/Regexp.html) and double escape backslashes. Read more about flexible matching (https://github.com/pact-foundation/pact-ruby/wiki/Regular-expressions-and-type-matching-with-Pact. Provider side Pact testing, involves verifying that the contract - the Pact file - can be satisfied by the Provider. A typical Provider side test would like something like: The `VerifyProvider` will handle all verifications, treating them as subtests and giving you granular test reporting. If you don't like this behaviour, you may call `VerifyProviderRaw` directly and handle the errors manually. Note that `PactURLs` may be a list of local pact files or remote based urls (possibly from a Pact Broker - http://docs.pact.io/documentation/sharings_pacts.html). Pact reads the specified pact files (from remote or local sources) and replays the interactions against a running Provider. If all of the interactions are met we can say that both sides of the contract are satisfied and the test passes. When validating a Provider, you have 3 options to provide the Pact files: 1. Use "PactURLs" to specify the exact set of pacts to be replayed: Options 2 and 3 are particularly useful when you want to validate that your Provider is able to meet the contracts of what's in Production and also the latest in development. See this [article](http://rea.tech/enter-the-pact-matrix-or-how-to-decouple-the-release-cycles-of-your-microservices/) for more on this strategy. Each interaction in a pact should be verified in isolation, with no context maintained from the previous interactions. So how do you test a request that requires data to exist on the provider? Provider states are how you achieve this using Pact. Provider states also allow the consumer to make the same request with different expected responses (e.g. different response codes, or the same resource with a different subset of data). States are configured on the consumer side when you issue a dsl.Given() clause with a corresponding request/response pair. Configuring the provider is a little more involved, and (currently) requires running an API endpoint to configure any [provider states](http://docs.pact.io/documentation/provider_states.html) during the verification process. The option you must provide to the dsl.VerifyRequest is: An example route using the standard Go http package might look like this: See the examples or read more at http://docs.pact.io/documentation/provider_states.html. See the Pact Broker (http://docs.pact.io/documentation/sharings_pacts.html) documentation for more details on the Broker and this article (http://rea.tech/enter-the-pact-matrix-or-how-to-decouple-the-release-cycles-of-your-microservices/) on how to make it work for you. Publishing using Go code: Publishing from the CLI: Use a cURL request like the following to PUT the pact to the right location, specifying your consumer name, provider name and consumer version. The following flags are required to use basic authentication when publishing or retrieving Pact files to/from a Pact Broker: Pact Go uses a simple log utility (logutils - https://github.com/hashicorp/logutils) to filter log messages. The CLI already contains flags to manage this, should you want to control log level in your tests, you can set it like so:

Package greengrass provides the API client, operations, and parameter types for AWS Greengrass. AWS IoT Greengrass seamlessly extends AWS onto physical devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. AWS IoT Greengrass ensures your devices can respond quickly to local events and operate with intermittent connectivity. AWS IoT Greengrass minimizes the cost of transmitting data to the cloud by allowing you to author AWS Lambda functions that execute locally.

Package rdns implements a variety of functionality to make DNS resulution configurable and extensible. It offers DNS resolvers as well as listeners with a number of protcols such as DNS-over-TLS, DNS-over-HTTP, and plain wire format DNS. In addition it is possible to route queries based on the query name or type. There are 4 fundamental types of objects available in this library. Resolvers implement name resolution with upstream resolvers. All of them implement connection reuse as well as pipelining (sending multiple queries and receiving them out-of-order). Groups typically wrap multiple resolvers and implement failover or load-balancing algorithms accross all resolvers in the group. Groups too are resolvers and can therefore be nested into other groups for more complex query routing. Routers are used to send DNS queries to resolvers, groups, or even other routers based on the query content. As with groups, routers too are resolvers that can be combined to form more advanced configurations. While resolvers handle outgoing queries to upstream servers, listeners are the receivers of queries. Multiple listeners can be started for different protocols and on different ports. Each listener forwards received queries to one resolver, group, or router. This example starts a stub resolver on the local machine which will forward all queries via DNS-over-TLS to provide privacy.

Package loads provides document loading methods for swagger (OAI) specifications. It is used by other go-openapi packages to load and run analysis on local or remote spec documents.

Package gls implements goroutine-local storage.

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 gostub is used for stubbing variables in tests, and resetting the original value once the test has been run. This can be used to stub static variables as well as static functions. To stub a static variable, use the Stub function: gostub can also stub static functions in a test by using a variable to reference the static function, and using that local variable to call the static function: You can test this by using gostub to stub the timeNow variable: If you are stubbing a function to return a constant value like in the above test, you can use StubFunc instead: StubFunc can also be used to stub functions that return multiple values: StubEnv can be used to setup environment variables for tests, and the environment values are reset to their original values upon Reset: The Reset method should be deferred to run at the end of the test to reset all stubbed variables back to their original values. You can set up multiple stubs by calling Stub again: For simple cases where you are only setting up simple stubs, you can condense the setup and cleanup into a single line: This sets up the stubs and then defers the Reset call. You should keep the return argument from the Stub call if you need to change stubs or add more stubs during test execution: The Stub call must be passed a pointer to the variable that should be stubbed, and a value which can be assigned to the variable. Test code Test code