Routing

Package evidence implements a Cosmos SDK module, per ADR 009, that allows for the submission and handling of arbitrary evidence of misbehavior. All concrete evidence types must implement the Evidence interface contract. Submitted evidence is first routed through the evidence module's Router in which it attempts to find a corresponding Handler for that specific evidence type. Each evidence type must have a Handler registered with the evidence module's keeper in order for it to be successfully executed. Each corresponding handler must also fulfill the Handler interface contract. The Handler for a given Evidence type can perform any arbitrary state transitions such as slashing, jailing, and tombstoning. This provides developers with great flexibility in designing evidence handling. A full setup of the evidence module may look something as follows:

Package fault provides standard http middleware for fault injection in go. Use the fault package to inject faults into the http request path of your service. Faults work by modifying and/or delaying your service's http responses. Place the Fault middleware high enough in the chain that it can act quickly, but after any other middlewares that should complete before fault injection (auth, redirects, etc...). The type and severity of injected faults is controlled by options passed to NewFault(Injector, Options). NewFault must be passed an Injector, which is an interface that holds the actual fault injection code in Injector.Handler. The Fault wraps Injector.Handler in another Fault.Handler that applies generic Fault logic (such as what % of requests to run the Injector on) to the Injector. Make sure you use the NewFault() and NewTypeInjector() constructors to create valid Faults and Injectors. There are three main Injectors provided by the fault package: Use fault.RejectInjector to immediately return an empty response. For example, a curl for a rejected response will produce: Use fault.ErrorInjector to immediately return a valid http status code of your choosing along with the standard HTTP response body for that code. For example, you can return a 200, 301, 418, 500, or any other valid status code to test how your clients respond to different statuses. Pass the WithStatusText() option to customize the response text. Use fault.SlowInjector to wait a configured time.Duration before proceeding with the request. For example, you can use the SlowInjector to add a 10ms delay to your requests. Use fault.RandomInjector to randomly choose one of the above faults to inject. Pass a list of Injector to fault.NewRandomInjector and when RandomInjector is evaluated it will randomly run one of the injectors that you passed. It is easy to combine any of the Injectors into a chained action. There are two ways you might want to combine Injectors. First, you can create separate Faults for each Injector that are sequential but independent of each other. For example, you can chain Faults such that 1% of requests will return a 500 error and another 1% of requests will be rejected. Second, you might want to combine Faults such that 1% of requests will be slowed for 10ms and then rejected. You want these Faults to depend on each other. For this use the special ChainInjector, which consolidates any number of Injectors into a single Injector that runs each of the provided Injectors sequentially. When you add the ChainInjector to a Fault the entire chain will always execute together. The NewFault() constructor has WithPathBlocklist() and WithPathAllowlist() options. Any path you include in the PathBlocklist will never have faults run against it. With PathAllowlist, if you provide a non-empty list then faults will not be run against any paths except those specified in PathAllowlist. The PathBlocklist take priority over the PathAllowlist, a path in both lists will never have a fault run against it. The paths that you include must match exactly the path in req.URL.Path, including leading and trailing slashes. Simmilarly, you may also use WithHeaderBlocklist() and WithHeaderAllowlist() to block or allow faults based on a map of header keys to values. These lists behave in the same way as the path allowlists and blocklists except that they operate on headers. Header equality is determined using http.Header.Get(key) which automatically canonicalizes your keys and does not support multi-value headers. Keep these limitations in mind when working with header allowlists and blocklists. Specifying very large lists of paths or headers may cause memory or performance issues. If you're running into these problems you should instead consider using your http router to enable the middleware on only a subset of your routes. The fault package provides an Injector interface and you can satisfy that interface to provide your own Injector. Use custom injectors to add additional logic to the package-provided injectors or to create your own completely new Injector that can still be managed by a Fault. The package provides a Reporter interface that can be added to Faults and Injectors using the WithReporter option. A Reporter will receive events when the state of the Injector changes. For example, Reporter.Report(InjectorName, StateStarted) is run at the beginning of all Injectors. The Reporter is meant to be provided by the consumer of the package and integrate with services like stats and logging. The default Reporter throws away all events. By default all randomness is seeded with defaultRandSeed(1), the same default as math/rand. This helps you reproduce any errors you see when running an Injector. If you prefer, you can also customize the seed passing WithRandSeed() to NewFault and NewRandomInjector. Some Injectors support customizing the functions they use to run their injections. You can take advantage of these options to add your own logic to an existing Injector instead of creating your own. For example, modify the SlowInjector function to slow in a rancom distribution instead of for a fixed duration. Be careful when you use these options that your return values fall within the same range of values expected by the default functions to avoid panics or other undesirable begavior. Customize the function a Fault uses to determine participation (default: rand.Float32) by passing WithRandFloat32Func() to NewFault(). Customize the function a RandomInjector uses to choose which injector to run (default: rand.Intn) by passing WithRandIntFunc() to NewRandomInjector(). Customize the function a SlowInjector uses to wait (default: time.Sleep) by passing WithSlowFunc() to NewSlowInjector(). Configuration for the fault package is done through options passed to NewFault and NewInjector. Once a Fault is created its enabled state and participation percentage can be updated with SetEnabled() and SetParticipation(). There is no other way to manage configuration for the package. It is up to the user of the fault package to manage how the options are generated. Common options are feature flags, environment variables, or code changes in deploys. Example is a package-level documentation example.

Package route provides http package-compatible routing library. It can route http requests by hostname, method, path and headers. Route defines simple language for matching requests based on Go syntax. Route provides series of matchers that follow the syntax: Host matcher: Path matcher: Method matcher: Header matcher: Matchers can be combined using && operator: Route library will join the trie-based matchers into one trie matcher when possible, for example: Will be combined into one trie for performance. If you add a third route: It wont be joined ito the trie, and would be matched separately instead.

Radix tree implementation below is a based on the original work by Armon Dadgar in https://github.com/armon/go-radix/blob/master/radix.go (MIT licensed). It's been heavily modified for use as a HTTP routing tree.

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/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 atreugo is a micro-framework to make simple the use of routing and middlewares with all optimizations of fasthttp This micro-framework is build on top valyala's fasthttp fork.

Package routing provides high performance and powerful HTTP routing capabilities.

Package gin provides functions to trace the gin-gonic/gin package (https://github.com/gin-gonic/gin). Currently there are two ways the code can be instrumented. One is instrumenting the routing of a received message (the Middleware function) and instrumenting the response generation through template evaluation (the HTML function).

Package routing provides high performance and powerful HTTP routing capabilities.

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