Search Results for "schema"
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Showing 63 open source projects for "schema"
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1
Schemathesis
Guarantee flawless API functionality with test scenarios
...Schemathesis uses your API's schema to generate both valid and invalid test scenarios, helping you verify API compliance and catch potential issues. It also verifies examples from the schema itself. -
2
Ariadne
Python library for implementing GraphQL servers
...If you are missing or unhappy with something, extend or easily swap with your own. Asynchronous resolvers and query execution. Subscriptions. Custom scalars, enums, and schema directives. Unions and interfaces. File uploads. Defining schema using SDL strings. Loading schema from .graphql files. WSGI middleware for implementing GraphQL in existing sites. -
3
Barfi
A Python visual Flow Based Programming library
A Python visual Flow-Based Programming library that integrates into your existing workflow. Barfi is a Flow-Based Programming environment that provides a graphical programming interface. It is integratable into your existing Python workflows. A schema is built using barfi.Blocks. Then the schema is executed with barfi.ComputeEngine. Each barfi.Block has some properties that enable the FBP and schema building. Firstly, each Block has Input and Output interfaces that link to other Blocks. Each Block can carry an executable function, that is specified by the user. This function can access/get data from the Input interface, perform computations or calculations, and set the Output interface. ... -
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Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
...Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your application. To support graphql Subscriptions over WebSockets you need to provide a WebSocket enabled server. Create a GraphQL schema defining a User type and a single query field user that will return a hardcoded user. -
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5
LangExtract
A Python library for extracting structured information
LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and validation via automatically generated interactive HTML visualizations. LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. ... -
6
lxml
The lxml XML toolkit for Python
A Python library for efficient XML and HTML processing, known for speed and compatibility. The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all CPython versions from 3.6 to 3.12. See the introduction for more information about the... -
7
SQL Explorer
Easily share data across your company via SQL queries
...Quickly write and share SQL queries in a simple, usable SQL editor, preview the results in the browser, share links, download CSV, JSON, or Excel files (and even expose queries as API endpoints, if desired), and keep the information flowing! Comes with support for multiple connections, to many different SQL database types, a schema explorer, query history (e.g. lightweight version control), a basic security model, in-browser pivot tables, and more. SQL Explorer values simplicity, intuitive use, unobtrusiveness, stability, and the principle of least surprise. SQL Explorer is inspired by any number of great query and reporting tools out there. -
8
Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution... -
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Pony ORM
Pony Object Relational Mapper
Pony ORM is a Python ORM that enables developers to write database queries using generator expressions and Pythonic syntax, making code more readable and intuitive. It automatically translates Python expressions into SQL and supports multiple databases including SQLite, MySQL, PostgreSQL, and Oracle. With an emphasis on simplicity and maintainability, Pony ORM is suitable for both small projects and complex applications. -
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10
FastAPI
FastAPI framework, high performance, easy to learn, fast to code
...Get production-ready code. With automatic interactive documentation. Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. If you are building a CLI app to be used in the terminal instead of a web API, check out Typer. Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. In summary, you declare once the types of parameters, body, etc. as function parameters. You do that with standard modern Python types. You don't have to learn a new syntax, the methods or classes of a specific library, etc. -
11
Data Contract CLI
Enforce Data Contracts
...It uses YAML-based contract files to define the structure, meaning, quality rules, service levels, and connection details for a data product. The tool can connect to real data sources and check whether the actual dataset matches the schema, constraints, and quality expectations described in the contract. It supports both the Data Contract Specification and the Open Data Contract Standard, making it useful for teams standardizing data governance across different platforms. It can run locally, inside CI/CD pipelines, through Docker, or directly from Python code. Overall, it helps data producers and consumers treat data products more like APIs, with explicit expectations, automated checks, and clearer accountability. -
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sqlite-utils
Python CLI utility and library for manipulating SQLite databases
sqlite-utils is both a Python library and a command-line tool for creating, inspecting, and transforming SQLite databases with minimal boilerplate. It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a... -
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Tortoise ORM
Familiar asyncio ORM for python, built with relations in mind
Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) for Python, inspired by Django's ORM. It is designed to work with asynchronous frameworks, providing a simple and familiar API for interacting with databases. Tortoise ORM supports various relational databases and is suitable for building high-performance web applications. -
14
Graphene
GraphQL in Python Made Easy
Graphene is a Python library for building GraphQL APIs fast and easily, using a code-first approach. Instead of writing GraphQL Schema Definition Langauge (SDL), Python code is written to describe the data provided by your server. Graphene helps you use GraphQL effortlessly in Python, but what is GraphQL? GraphQL is a data query language developed internally by Facebook as an alternative to REST and ad-hoc webservice architectures. With Graphene you have all the tools you need to implement a GraphQL API in Python, with multiple integrations with different frameworks including Django, SQLAlchemy and Google App Engine. -
15
Piccolo
A fast, user friendly ORM and query builder which supports asyncio
Piccolo is a modern, fast, and type-safe ORM for Python, designed with developer ergonomics in mind. It provides a clean syntax for defining schemas and building queries while supporting both sync and async execution. With built-in admin tools and rich introspection, Piccolo is suitable for web apps, APIs, and small-to-medium scale backends that prioritize clarity and speed. -
16
Petastorm
Petastorm library enables single machine or distributed training
...Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. It can also be used from pure Python code. A dataset created using Petastorm is stored in Apache Parquet format. On top of a Parquet schema, petastorm also stores higher-level schema information that makes multidimensional arrays into a native part of a petastorm dataset. Petastorm supports extensible data codecs. These enable a user to use one of the standard data compressions (jpeg, png) or implement her own. -
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PaaSTA
An open, distributed platform as a service
...PaaSTA aims to take a declarative description of the services that teams need to run and then ensures that those services are deployed safely, efficiently, and in a manner that is easy for the teams to maintain. Rather than managing Kubernetes YAML files, PaaSTA provides a simplified schema to describe your service and in addition to configuring Kubernetes it can also configure other infrastructure tools to provide monitoring, logging, cost management etc. -
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Responder
A familiar HTTP Service Framework for Python
...Mutable response object passed into each view. No need to return anything. Background tasks spawned off in a ThreadPoolExecutor. GraphQL (with GraphiQL) support! OpenAPI schema generation, with interactive documentation! Single-page webapp support! -
19
Mimesis
High-performance fake data generator for Python
Mimesis is an open source high-performance fake data generator for Python, able to provide data for various purposes in various languages. It's currently the fastest fake data generator for Python, and supports many different data providers that can produce data related to people, food, transportation, internet and many more. Mimesis is really easy to use, with everything you need just an import away. Simply import an object, called a Provider, which represents the type of data you... -
20
GQL
A GraphQL client in Python
This is a GraphQL client for Python 3.7+. Plays nicely with graphene, graphql-core, graphql-js and any other GraphQL implementation compatible with the spec. GQL architecture is inspired by React-Relay and Apollo-Client. GQL 3 is a GraphQL Client for Python 3.6+ which plays nicely with other graphql implementations compatible with the spec. Under the hood, it uses GraphQL-core which is a Python port of GraphQL.js, the JavaScript reference implementation for GraphQL. GQL supports multiple... -
21
Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Validate the functions that produce your data by automatically generating test cases for them. Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects. -
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent... -
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Django Ninja
Fast, Async-ready, Openapi, type hints based framework
...Very high performance thanks to Pydantic and async support. Type hints and automatic docs lets you focus only on business logic. Based on the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. Django friendly (obviously) has good integration with the Django core and ORM. Used by multiple companies on live projects. -
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WTForms
A flexible forms validation and rendering library for Python
WTForms is a flexible forms validation and rendering library for Python web development. It can work with whatever web framework and template engine you choose. It supports data validation, CSRF protection, internationalization (I18N), and more. There are various community libraries that provide closer integration with popular frameworks. WTForms is designed to work with any web framework and template engine. There are a number of community-provided libraries that make integrating with... -
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drf-yasg
Automated generation of real Swagger/OpenAPI 2.0 schemas
Only the latest version of drf-yasg is supported. Support of old versions is dropped immediately with the release of a new version. Please do not create issues before upgrading to the latest release available at the time. Regression reports are accepted and will be resolved with a new release as quickly as possible. Removed features will usually go through a deprecation cycle of a few minor releases. If you are looking to add Swagger/OpenAPI support to a new project you might want to take a...
