Open Source Python Frameworks - Page 10
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Python Frameworks
View 166 business solutionsBrowse free open source Python Frameworks and projects below. Use the toggles on the left to filter open source Python Frameworks by OS, license, language, programming language, and project status.
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Flexible python library for web-development. It does not enforce any development model or structure, but instead includes tools to simplify modern (web)development trends like UNIT testing, WSGI, and XML.
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Ennesbot is an open source automated IRC client (aka Bot) written entirely in Python. It uses direct sockets and medusa style sockets. It has pluggable python personality modules that can extend the bot.
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Entangled is a distributed hash table (DHT) and peer-to-peer tuple space, based on Kademlia. It is written in Python, and makes use of the Twisted framework. This can be used as a base for creating peer-to-peer (P2P) network applications.
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Err
err is a plugin based chatbot designed to be easily extensible
err is a plugin based chatbot designed to be easily deployable, extensible and maintainable. It allows you to start scripts interactively from your chatrooms for any reason: random humour, starting a build, monitoring commits, triggering alerts ... It is really easy to add your own feature. Features Backends support: - XMPP : Tested with hipchat, openfire and Jabber but should be compatible with any standard XMPP servers. - CampFire support - Supports MUCs (chatrooms) - Local Graphical Console (for testing/dev) - Local Text Console (for testing/dev) -
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Etch is a cross-platform, language- and transport-independent framework for building and consuming network services. With Etch, service development and consumption becomes no more difficult than library development and consumption.
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Ethereum ETL
Python scripts for ETL (extract, transform and load) jobs for Ethereum
Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery. Ethereum ETL lets you convert blockchain data into convenient formats like CSVs and relational databases. -
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XAMPLE creates a separate, encrypted and independent LAMP environment on a system that does or does not already run a web server and database. It is useful to provide a customized environment for software refusing to work with the installed LAMP stack.
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Eynhorn is a 3d action rpg engine / framework. It will support dialog system, fight system, armors and weapons, and will include a map assembly. It is realized in Soya 3d and Python, so it'll be platform independent.
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations. -
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FATS - FATS is a Twisted and Fast Asterisk's Telephony Services. Project contains implementation of FastAGI, AMI protocols for the Twisted framework. Using it you can develop fast and pretty services for the Asterisk IP-PBX.
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FastAPI CRUD Router
A dynamic FastAPI router that automatically creates CRUD routes
Tired of rewriting generic CRUD routes? Need to rapidly prototype a feature for a presentation or a hackathon? Thankfully, fastapi-crudrouter has your back. As an extension to the APIRouter included with FastAPI, the FastAPI CRUDRouter will automatically generate and document your CRUD routes for you, all you have to do is pass your model and maybe your database connection. fastapi-crudrouter provides a number of features that allow you to get the most out of your automatically generated CRUD routes. The CRUDRouter is able to dynamically generate detailed documentation based on the models given to it. By default, all routes generated by the CRUDRouter will be documented according to OpenAPI spec. The CRUDRouter is able to dynamically generate detailed documentation based on the models given to it. -
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FastUI
Build better UIs faster
FastUI is a library that lets developers build interactive user interfaces for FastAPI applications using Pydantic models. It automatically generates frontend components based on data schemas and endpoint logic, reducing the need for manual UI development. Designed to be type-safe, reactive, and fast, FastUI streamlines the creation of web dashboards, admin panels, and internal tools within a FastAPI backend. -
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At the moment it's a collection of moderately useful python utility classes focusing mainly on unit test framework setup and development.
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Firmata
generic protocol for communicating with microcontrollers
Firmata is a generic protocol for communicating with microcontrollers from software on a host computer. It is intended to work with any host computer software package. There are implementations for multiple microcontrollers and host software packages. -
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Flask App Builder
Simple and rapid application development framework
Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Automatic permissions lookup, based on exposed methods. Inserts on the Database all the detailed permissions possible on your application. Public (no authentication needed) and Private permissions. Role-based permissions. Authentication support for OpenID, Database and LDAP. Support for self-user registration. Automatic, Add, Edit, and Show from Database Models. Labels and descriptions for each field. Automatic base validators from the model's definition. Custom validators, extra fields, and custom filters for related dropdown lists. Image and File support for upload and database field association. Field sets for Forms (Django style). -
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Flask JSONDash
Build complex dashboards without any front-end code
Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go. Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only. Ready to go. This project is a flask blueprint that allows you to create sleek dashboards without writing any front-end (or backend) code. Everything is powered through simple JSON configurations for declaring arbitrary charts. Leveraging popular libraries like C3.js and D3.js, and much more. Also supports templates and iframes. Only a basic intuitive configuration is required. The dashboard layout and blueprint styles are pre-packaged, and provide only the essentials, while getting out of the way. Drag-and-drop your layout easily and intuitively. Multiple layout modes - bootstrap grid-based or totally freeform. Data utilities for munging and manipulating data suitable for various charts. -
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Flask RESTX
Fully featured framework for fast, easy and documented API development
Fork of Flask-RESTPlus fully featured framework for fast, easy and documented API development with Flask. Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger. With Flask-RESTX, you only import the api instance to route and document your endpoints. -
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Flask-APScheduler
Adds APScheduler support to Flask
Flask-APScheduler is a Flask extension that adds support for the APScheduler. Loads scheduler configuration from Flask configuration. Loads job definitions from Flask configuration. Allows to specify the hostname which the scheduler will run on. Provides a REST API to manage the scheduled jobs. Provides authentication for the REST API. Integrates with Flask Blueprints. -
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Flask-Caching
A caching extension for Flask
Flask-Caching is an extension to Flask that adds caching support for various backends to any Flask application. By running on top of cachelib it supports all of werkzeug’s original caching backends through a uniformed API. It is also possible to develop your own caching backend by subclassing flask_caching.backends.base.BaseCache class. Flask’s pluggable view classes are also supported. To cache them, use the same cached() decorator on the dispatch_request method. Using the same @cached decorator you are able to cache the result of other non-view related functions. The only stipulation is that you replace the key_prefix, otherwise it will use the request.path cache_key. Keys control what should be fetched from the cache. If, for example, a key does not exist in the cache, a new key-value entry will be created in the cache. Otherwise, the value (i.e. the cached result) of the key will be returned. -
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Flask-GraphQL
Adds GraphQL support to your Flask application
Adds GraphQL support to your Flask application. This will add /graphql endpoint to your app and enable the GraphiQL IDE. If you are using the Schema type of Graphene library, be sure to use the graphql_schema attribute to pass as schema on the GraphQLView view. Otherwise, the GraphQLSchema from graphql-core is the way to go. The GraphQLSchema object that you want the view to execute when it gets a valid request. A value to pass as the context_value to graphql execute function. By default is set to dict with request object at key request. The root_value you want to provide to graphql execute. -
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Flask-JWT-Extended
An open source Flask extension that provides JWT support
Flask-JWT-Extended not only adds support for using JSON Web Tokens (JWT) to Flask for protecting routes, but also many helpful (and optional) features built in to make working with JSON Web Tokens easier. Adding custom claims to JSON Web Tokens. Automatic user loading (current_user). Custom claims validation on received tokens. Refresh tokens, first-class support for fresh tokens for making sensitive changes. Token revoking/blocklisting. Storing tokens in cookies and CSRF protection. Adding custom claims to JSON Web Tokens. Automatic user loading (current_user). Custom claims validation on received tokens. Refresh tokens. First-class support for fresh tokens for making sensitive changes. Token revoking/blocklisting. Storing tokens in cookies and CSRF protection. -
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Flask-Limiter
Rate Limiting extension for Flask
Flask-Limiter provides rate-limiting features to flask applications. It allows configuring various backends to persist the rate limits, which is provided by the limits library. Sponsored by Zuplo - fully-managed API Gateway with rate limiting, authentication, and more. Add rate limiting to your API in minutes, try it at zuplo.com Test it out. The fast endpoint respects the default rate limit while the slow endpoint uses the decorated one. ping has no rate limit associated with it. By adding the extension to your flask application, you can configure various rate limits at different levels (e.g. application wide, per Blueprint, routes, resource etc). To include extra dependencies for a specific storage backend you can add the specific backend name via the extras notation. -
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Flask-MongoEngine
MongoEngine flask extension with WTF model forms support
Flask-MongoEngine is a Flask extension that provides integration with MongoEngine, WtfForms and FlaskDebugToolbar. By default, Flask-MongoEngine will install integration only between Flask and MongoEngine. Integration with WTFForms and FlaskDebugToolbar are optional and should be selected as extra option, if required. This is done by users request, to limit amount of external dependencies in different production setup environments. All methods end extras described below are compatible between each other and can be used together. We still maintain special case for Flask = 1.1.4 support (the latest version in 1.x.x branch). To install flask-mongoengine with required dependencies use legacy extra option. Flask-mongoengine can be installed with Flask-WTF and WTFForms support. This will extend project dependencies with Flask-WTF, WTFForms and related packages. -
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Flask-RESTful
Simple framework for creating REST APIs
Flask-RESTful is an extension for Flask that adds support for quickly building REST APIs. It is a lightweight abstraction that works with your existing ORM/libraries. Flask-RESTful encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTful should be easy to pick up. Flask-RESTful provides an extension to Flask for building REST APIs. Flask-RESTful was initially developed as an internal project at Twilio, built to power their public and internal APIs. Flask-RESTful understands multiple kinds of return values from view methods. Similar to Flask, you can return any iterable and it will be converted into a response, including raw Flask response objects. Flask-RESTful also support setting the response code and response headers using multiple return values.
