Query Builders

goqu an idiomatch SQL builder, and query package. Please see https://github.com/SkelatorIndy/goqu for an introduction to goqu.

Package query provides an extensible SQL query builder for PostgreSQL. It works by using first class functions to allow for queries to be built up. This does not support the entire dialect for PostgreSQL, only a subset that would be necessary for CRUD operations. Let's look at how a simple SELECT query can be built up using this library, we can then use the above to pass a query to our database driver, along with the arguments passed to the query, Calling Build on the query will build up the query string and correctly set the parameter arguments in the query. Args will return an interface slice containing the arguments given to the query via query.Arg. We can do even more complex SELECT queries too, This library makes use of the type Option which is a first class function, which takes the current Query an Option is being applied to and returns it. With this we can define our own Option functions to clean up some of the queries we want to build.

Package loukoum provides a simple SQL Query Builder. At the moment, only PostgreSQL is supported. If you have to generate complex queries, which rely on various contexts, loukoum is the right tool for you. It helps you generate SQL queries from composable parts. However, keep in mind it's not an ORM or a Mapper so you have to use a SQL connector (like "database/sql" or "sqlx", for example) to execute queries. If you're afraid to slip a tiny SQL injection manipulating fmt (or a byte buffer...) when you append conditions, loukoum is here to protect you against yourself. For further informations, you can read this documentation: https://github.com/ulule/loukoum/blob/master/README.md Or you can discover loukoum with these examples. An "insert" can be generated like that: Also, if you need an upsert, you can define a "on conflict" clause: Updating a news is also simple: You can remove a specific user: Or select a list of users...

sqlslog is a logger for Go SQL database drivers without modifying existing *sql.DB stdlib usage. sqlslog uses *slog.Logger to log SQL database driver operations. You can also use options to customize the logger's behavior. Open takes Option s to customize the logging behavior. Option is created by using functions like HandlerFunc, ConnPrepareContext, StmtQueryContext, etc. HandlerFunc sets the function to create a slog.Handler for the logger. slogslog provides NewTextHandler and NewJSONHandler to create a slog.Handler for sqlslog. You can also use your own slog.Handler by using Handler with your slog.Handler. But your own slog.Handler should know how to log LevelTrace and LevelVerbose log levels. So you should use sqlslog.ReplaceLevelAttr with your slog.Handler. sqlslog has 6 log levels: LevelVerbose, LevelTrace, LevelDebug, LevelInfo, LevelWarn, and LevelError. LevelDebug, LevelInfo, LevelWarn, and LevelError are the same as slog's log levels. LevelVerbose and LevelTrace are extra log levels for sqlslog. LevelVerbose is the lowest log level, and LevelTrace is the second lowest log level. A Step is a logical operation in the database driver, such as a query, a ping, a prepare, etc. An Event is an event that occurs during a Step, such as EventStart, EventError, and EventComplete. A StepOptions is a set of options for logging a Step and has EventOptions for each event. sqlslog provides a way to customize the log message and log Level for each step event. You can customize them by using functions that take StepOptions and return Option, like ConnPrepareContext or StmtQueryContext. The default step event message builder is StepEventMsgWithEventName. You can change the default step event message builder by calling SetStepEventMsgBuilder. sqlslog measures the duration of each step and logs it. You can change the duration unit by calling Duration function and can change the key name of the duration by calling DurationKey function. sqlslog provides a way to track connections, transactions and statements by using a tracking ID. Each tracking ID is a unique identifier for a connection, transaction or statement. Tracking ID key in logs is conn_id, tx_id or stmt_id. Tracking IDs are generated by the ID generator function. The default ID generator function is IDGeneratorDefault. You can change the ID generator function by calling IDGenerator with functions created by RandIntIDGenerator or RandReadIDGenerator with IDGenErrorSuppressor.

Package dbx provides a set of DB-agnostic and easy-to-use query building methods for relational databases. This example shows how to do CRUD operations. This example shows how to populate DB data in different ways. This example shows how to use query builder to build DB queries. This example shows how to use query builder in transactions.

openfigi: a client for the OpenFIGI API. 3 types of queries: Instructions: Construct a builder. - Search and Filter use BaseItemBuilder, then construct a BaseItem. - Mapping uses MappingItemBuilder, then construct a MappingItem. MappingRequest is []MappingItem. Set the properties through setters. (".Set[...](...)") Build the item: BaseItemBuilder.Build, MappingItemBuilder.Build. The package will validate the content of the item, reducing bad API calls. [optional] API Key, set with SetAPIKey. Use the client to make the request. - BaseItem.Search, BaseItem.Filter, returning SearchResponse or FilterResponse - MappingRequest.Fetch returning []SingleMappingResponse - SearchResponse.Next, FilterResponse.Next to fetch the next page.

Package builder is a simple and powerful sql builder for Go. Make sure you have installed Go 1.1+ and then: WARNNING: Currently, only query conditions are supported. Below is the supported conditions. 1. Eq is a redefine of a map, you can give one or more conditions to Eq 2. Neq is the same to Eq 3. Gt, Gte, Lt, Lte 4. Like 5. Expr you can customerize your sql with Expr 6. In and NotIn 7. IsNull and NotNull 8. And(conds ...Cond), And can connect one or more condtions via AND 9. Or(conds ...Cond), Or can connect one or more conditions via Or 10. Between 11. define yourself conditions Since Cond is a interface, you can define yourself conditions and compare with them

Package dbx provides a set of DB-agnostic and easy-to-use query building methods for relational databases. This example shows how to do CRUD operations. This example shows how to populate DB data in different ways. This example shows how to use query builder to build DB queries. This example shows how to use query builder in transactions.

Package rds provides the client and types for making API requests to Amazon Relational Database Service. Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, resizable capacity for an industry-standard relational database and manages common database administration tasks, freeing up developers to focus on what makes their applications and businesses unique. Amazon RDS gives you access to the capabilities of a MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle, or Amazon Aurora database server. These capabilities mean that the code, applications, and tools you already use today with your existing databases work with Amazon RDS without modification. Amazon RDS automatically backs up your database and maintains the database software that powers your DB instance. Amazon RDS is flexible: you can scale your DB instance's compute resources and storage capacity to meet your application's demand. As with all Amazon Web Services, there are no up-front investments, and you pay only for the resources you use. This interface reference for Amazon RDS contains documentation for a programming or command line interface you can use to manage Amazon RDS. Note that Amazon RDS is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide. Amazon RDS API Reference For the alphabetical list of API actions, see API Actions (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_Operations.html). For the alphabetical list of data types, see Data Types (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_Types.html). For a list of common query parameters, see Common Parameters (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/CommonParameters.html). For descriptions of the error codes, see Common Errors (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/CommonErrors.html). Amazon RDS User Guide For a summary of the Amazon RDS interfaces, see Available RDS Interfaces (http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html#Welcome.Interfaces). For more information about how to use the Query API, see Using the Query API (http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Using_the_Query_API.html). See https://docs.aws.amazon.com/goto/WebAPI/rds-2014-10-31 for more information on this service. See rds package documentation for more information. https://docs.aws.amazon.com/sdk-for-go/api/service/rds/ To Amazon Relational Database Service with the SDK use the New function to create a new service client. With that client you can make API requests to the service. These clients are safe to use concurrently. See the SDK's documentation for more information on how to use the SDK. https://docs.aws.amazon.com/sdk-for-go/api/ See aws.Config documentation for more information on configuring SDK clients. https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config See the Amazon Relational Database Service client RDS for more information on creating client for this service. https://docs.aws.amazon.com/sdk-for-go/api/service/rds/#New The rdsutil package's BuildAuthToken function provides a connection authentication token builder. Given an endpoint of the RDS database, AWS region, DB user, and AWS credentials the function will create an presigned URL to use as the authentication token for the database's connection. The following example shows how to use BuildAuthToken to create an authentication token for connecting to a MySQL database in RDS. See rdsutil package for more information. http://docs.aws.amazon.com/sdk-for-go/api/service/rds/rdsutils/

Package jet is a complete solution for efficient and high performance database access, consisting of type-safe SQL builder with code generation and automatic query result data mapping. Jet currently supports PostgreSQL, MySQL, MariaDB and SQLite. Future releases will add support for additional databases. Use the command bellow to add jet as a dependency into go.mod project: Jet generator can be installed in one of the following ways: (Go1.16+) Install jet generator using go install: go install github.com/go-jet/jet/v2/cmd/jet@latest Install jet generator to GOPATH/bin folder: cd $GOPATH/src/ && GO111MODULE=off go get -u github.com/go-jet/jet/cmd/jet Install jet generator into specific folder: git clone https://github.com/go-jet/jet.git cd jet && go build -o dir_path ./cmd/jet Make sure that the destination folder is added to the PATH environment variable. Jet requires already defined database schema(with tables, enums etc), so that jet generator can generate SQL Builder and Model files. File generation is very fast, and can be added as every pre-build step. Sample command: Before we can write SQL queries in Go, we need to import generated SQL builder and model types: To write postgres SQL queries we import: Then we can write the SQL query: Now we can run the statement and store the result into desired destination: We can print a statement to see SQL query and arguments sent to postgres server: Output: If we print destination as json, we'll get: Detail info about all statements, features and use cases can be found at project wiki page - https://github.com/go-jet/jet/wiki.

Package dnscore provides a DNS resolver, a DNS transport, a query builder, and a DNS response parser. This package is designed to facilitate DNS measurements and queries by providing both high-level and low-level APIs. It aims to be flexible, extensible, and easy to integrate with existing Go code. The high-level *Resolver API provides a DNS resolver that is compatible with the *net.Resolver struct from the net package. The low-level *Transport API allows users to send and receive DNS messages using different protocols and dialers. The package also includes utilities for creating and validating DNS messages. - High-level *Resolver API compatible with *net.Resolver for easy integration. - Low-level *Transport API allowing granular control over DNS requests and responses. - Support for multiple DNS protocols, including UDP, TCP, DoT, DoH, and DoQ. - Utilities for creating and validating DNS messages. - Optional logging for structured diagnostic events through log/slog. - Handling of duplicate responses for DNS over UDP to measure censorship. The package is structured to allow users to compose their own workflows by providing building blocks for DNS queries and responses. It uses the widely-used github.com/miekg/dns library for DNS message parsing and serialization. The dd-000-dnscore.md document describes the design of this package. The df-000-dns.md document describes the data format generated by this package when using log/slog to emit structured diagnostic events.

Package forest has functions for REST Api testing in Go This package provides a few simple helper types and functions to create functional tests that call HTTP services. A test uses a forest Client which encapsulates a standard http.Client and a base url. Such a client can be created inside a function or by initializing a package variable for shared access. Using a client, you can send http requests and call multiple expectation functions on each response. Most functions of the forest package take the *testing.T variable as an argument to report any error. Example To compose http requests, you create a RequestConfig value which as a Builder interface for setting the path,query,header and body parameters. The ProcessTemplate function can be useful to create textual payloads. To inspect http responses, you use the Expect functions that perform the unmarshalling or use XMLPath or JSONPath functions directly on the response. If needed, implement the standard TestMain to do global setup and teardown. In contrast to the standard behavior, the Body of a http.Response is made re-readable. This means one can apply expectations to a response as well as dump the full contents. The function XMLPath provides XPath expression support. It uses the [https://godoc.org/launchpad.net/xmlpath] package. The similar function JSONPath can be used on JSON documents. Colorizes error output (can be configured using package vars). All functions can also be used in a setup and teardown as part of TestMain. (c) 2015, http://ernestmicklei.com. MIT License

Package osquery provides a non-obtrusive, idiomatic and easy-to-use query and aggregation builder for the official Go client (https://github.com/elastic/go-elasticsearch) for the ElasticSearch database (https://www.elastic.co/products/elasticsearch). osquery alleviates the need to use extremely nested maps (map[string]interface{}) and serializing queries to JSON manually. It also helps eliminating common mistakes such as misspelling query types, as everything is statically typed. Using `osquery` can make your code much easier to write, read and maintain, and significantly reduce the amount of code you write. osquery provides a method chaining-style API for building and executing queries and aggregations. It does not wrap the official Go client nor does it require you to change your existing code in order to integrate the library. Queries can be directly built with `osquery`, and executed by passing an `*elasticsearch.Client` instance (with optional search parameters). Results are returned as-is from the official client (e.g. `*esapi.Response` objects). Getting started is extremely simple: osquery currently supports version 7 of the ElasticSearch Go client. The library cannot currently generate "short queries". For example, whereas ElasticSearch can accept this: { "query": { "term": { "user": "Kimchy" } } } The library will always generate this: This is also true for queries such as "bool", where fields like "must" can either receive one query object, or an array of query objects. `osquery` will generate an array even if there's only one query object.

Package jet is a complete solution for efficient and high performance database access, consisting of type-safe SQL builder with code generation and automatic query result data mapping. Jet currently supports PostgreSQL, MySQL, MariaDB and SQLite. Future releases will add support for additional databases. Use the command bellow to add jet as a dependency into go.mod project: Jet generator can be installed in one of the following ways: (Go1.16+) Install jet generator using go install: go install github.com/amantuladhar/jet/v2/cmd/jet@latest Install jet generator to GOPATH/bin folder: cd $GOPATH/src/ && GO111MODULE=off go get -u github.com/go-jet/jet/cmd/jet Install jet generator into specific folder: git clone https://github.com/go-jet/jet.git cd jet && go build -o dir_path ./cmd/jet Make sure that the destination folder is added to the PATH environment variable. Jet requires already defined database schema(with tables, enums etc), so that jet generator can generate SQL Builder and Model files. File generation is very fast, and can be added as every pre-build step. Sample command: Before we can write SQL queries in Go, we need to import generated SQL builder and model types: To write postgres SQL queries we import: Then we can write the SQL query: Now we can run the statement and store the result into desired destination: We can print a statement to see SQL query and arguments sent to postgres server: Output: If we print destination as json, we'll get: Detail info about all statements, features and use cases can be found at project wiki page - https://github.com/go-jet/jet/wiki.

Package obreron provides a simple, fast and cheap query builder

Package jet is a framework for writing type-safe SQL queries in Go, with ability to easily convert database query result into desired arbitrary object structure. Use the bellow command to install jet Install jet generator to GOPATH bin folder. This will allow generating jet files from the command line. *Make sure GOPATH bin folder is added to the PATH environment variable. Jet requires already defined database schema(with tables, enums etc), so that jet generator can generate SQL Builder and Model files. File generation is very fast, and can be added as every pre-build step. Sample command: Then next step is to import generated SQL Builder and Model files and write SQL queries in Go: To write SQL queries for PostgreSQL import: To write SQL queries for MySQL and MariaDB import: *Dot import is used so that Go code resemble as much as native SQL. Dot import is not mandatory. Write SQL: Store result into desired destination: Detail info about all features and use cases can be found at project wiki page - https://github.com/go-jet/jet/wiki.

Package rds provides the client and types for making API requests to Amazon Relational Database Service. Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, resizable capacity for an industry-standard relational database and manages common database administration tasks, freeing up developers to focus on what makes their applications and businesses unique. Amazon RDS gives you access to the capabilities of a MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle, or Amazon Aurora database server. These capabilities mean that the code, applications, and tools you already use today with your existing databases work with Amazon RDS without modification. Amazon RDS automatically backs up your database and maintains the database software that powers your DB instance. Amazon RDS is flexible: you can scale your DB instance's compute resources and storage capacity to meet your application's demand. As with all Amazon Web Services, there are no up-front investments, and you pay only for the resources you use. This interface reference for Amazon RDS contains documentation for a programming or command line interface you can use to manage Amazon RDS. Note that Amazon RDS is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide. Amazon RDS API Reference For the alphabetical list of API actions, see API Actions (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_Operations.html). For the alphabetical list of data types, see Data Types (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_Types.html). For a list of common query parameters, see Common Parameters (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/CommonParameters.html). For descriptions of the error codes, see Common Errors (http://docs.aws.amazon.com/AmazonRDS/latest/APIReference/CommonErrors.html). Amazon RDS User Guide For a summary of the Amazon RDS interfaces, see Available RDS Interfaces (http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html#Welcome.Interfaces). For more information about how to use the Query API, see Using the Query API (http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Using_the_Query_API.html). See https://docs.aws.amazon.com/goto/WebAPI/rds-2014-10-31 for more information on this service. See rds package documentation for more information. https://docs.aws.amazon.com/sdk-for-go/api/service/rds/ To Amazon Relational Database Service with the SDK use the New function to create a new service client. With that client you can make API requests to the service. These clients are safe to use concurrently. See the SDK's documentation for more information on how to use the SDK. https://docs.aws.amazon.com/sdk-for-go/api/ See aws.Config documentation for more information on configuring SDK clients. https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config See the Amazon Relational Database Service client RDS for more information on creating client for this service. https://docs.aws.amazon.com/sdk-for-go/api/service/rds/#New The rdsutil package's BuildAuthToken function provides a connection authentication token builder. Given an endpoint of the RDS database, AWS region, DB user, and AWS credentials the function will create an presigned URL to use as the authentication token for the database's connection. The following example shows how to use BuildAuthToken to create an authentication token for connecting to a MySQL database in RDS. See rdsutil package for more information. http://docs.aws.amazon.com/sdk-for-go/api/service/rds/rdsutils/

Package jet is a complete solution for efficient and high performance database access, consisting of type-safe SQL builder with code generation and automatic query result data mapping. Jet currently supports PostgreSQL, MySQL, MariaDB and SQLite. Future releases will add support for additional databases. Use the command bellow to add jet as a dependency into go.mod project: Jet generator can be installed in one of the following ways: (Go1.16+) Install jet generator using go install: go install github.com/go-jet/jet/v2/cmd/jet@latest Install jet generator to GOPATH/bin folder: cd $GOPATH/src/ && GO111MODULE=off go get -u github.com/go-jet/jet/cmd/jet Install jet generator into specific folder: git clone https://github.com/go-jet/jet.git cd jet && go build -o dir_path ./cmd/jet Make sure that the destination folder is added to the PATH environment variable. Jet requires already defined database schema(with tables, enums etc), so that jet generator can generate SQL Builder and Model files. File generation is very fast, and can be added as every pre-build step. Sample command: Before we can write SQL queries in Go, we need to import generated SQL builder and model types: To write postgres SQL queries we import: Then we can write the SQL query: Now we can run the statement and store the result into desired destination: We can print a statement to see SQL query and arguments sent to postgres server: Output: If we print destination as json, we'll get: Detail info about all statements, features and use cases can be found at project wiki page - https://github.com/go-jet/jet/wiki.

Package dbx provides a set of DB-agnostic and easy-to-use query building methods for relational databases. This example shows how to do CRUD operations. This example shows how to populate DB data in different ways. This example shows how to use query builder to build DB queries. This example shows how to use query builder in transactions.