Browse 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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  • 1

    CoSimA+

    The Co-Simulation Adaptation Platform

    The co-simulation adapation platform serves as programming framework and middleware to enable coupling of distributed, heterogeneous numerical models. The framework facilitates the adaptation and integration of new sub-models into a common simulation platform.
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  • 2
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  • 3
    CodeWP Local
    CodeWP Local is a desktop application that allows you to run WordPress, Laravel 13, and PHP-based websites locally on your Windows machine — no technical expertise required. It comes bundled with everything you need: Nginx, PHP 8.3/8.4, MariaDB, and phpMyAdmin — all managed through a clean, modern interface.
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  • 4
    Connexion

    Connexion

    Swagger/OpenAPI First framework for Python on top of Flask

    Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees that it will work as you specified. We built Connexion this way in order to simplify the development process. Reduce misinterpretation about what an API is going to look like. With Connexion, you write the spec first. Connexion then calls your Python code, handling the mapping from the specification to the code. This incentivizes you to write the specification so that all of your developers can understand what your API does, even before you write a single line of code.
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  • 5
    Cookiecutter Django

    Cookiecutter Django

    Framework for jumpstarting production-ready Django projects quickly

    Powered by Cookiecutter, Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly. Cookiecutter Django works with Python 3.9 and renders Django projects with 100% starting test coverage. It has 12-Factor based settings via django-environment. Secure by default, beacuse we believe in SSL. Optimized development and production settings. Registration is handled via django-allauth. It comes with custom user model ready to go. Provides an optional basic ASGI setup for Websockets and an optional custom static build using Gulp and livereload. Send emails via Anymail (using Mailgun by default or Amazon SES if AWS is selected cloud provider, but switchable). Media storage using Amazon S3 or Google Cloud Storage. Docker support using docker-compose for development and production (using Traefik with LetsEncrypt support). Procfile for deploying to Heroku. Provides instructions for deploying to PythonAnywhere. You can run tests with unittest or pytest.
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  • 6
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data.
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  • 7
    DBOS Transact PY

    DBOS Transact PY

    Lightweight Durable Python Workflows

    dbos-transact-py is the Python counterpart to dbos-transact-ts, offering durable transactional programming with automatic state persistence in PostgreSQL. It simplifies building resilient and idempotent applications by enabling Python functions to retain their state, restart after failure, and guarantee consistency. It's designed for data-heavy and fault-intolerant use cases.
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  • 8
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities.
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  • 9
    Digital Preservation Software Platform (DPSP) consists of a number of open source products such as Xena and Digital Preservation Recorder. This installs and configures the complete platform for preserving digital records - just install and use! NO LONGER MAINTAINED, NO LONGER SUPPORTED
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  • 10
    Django Autocomplete Light

    Django Autocomplete Light

    A fresh approach to autocomplete implementations

    A fresh approach to autocomplete implementations, specially for Django. Python 2.7, 3.4, Django 2.0+ support (Django 1.11 (LTS), is supported until django-autocomplete-light-3.2.10), Django (multiple) choice support, Django (multiple) model choice support, Django generic foreign key support (through django-querysetsequence), Django generic many to many relation support (through django-generic-m2m and django-gm2m). Multiple widget support: select2.js, easy to add more. Creating choices that don't exist in the autocomplete, offering choices that depend on other fields in the form, in an elegant and innovative way. Dynamic widget creation (ie. inlines), supports YOUR custom scripts too. Provides a test API for your awesome autocompletes, to support YOUR custom use cases too. A documented automatically tested example for each use case in test_project.
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  • 11
    Django Cachalot

    Django Cachalot

    No effort, no worry, maximum performance

    Caches your Django ORM queries and automatically invalidates them. Cachalot officially supports Python 3.7-3.10 and Django 2.2, 3.2, and 4.0-4.1 with the databases PostgreSQL, SQLite, and MySQL. Note: an upper limit on Django version is set for your safety. Please do not ignore it. To start developing, install the requirements and run the tests via tox. Currently, benchmarks are supported on Linux and Mac/Darwin. You will need a database called "cachalot" on MySQL and PostgreSQL. Additionally, on PostgreSQL, you will need to create a role called "cachalot." You can also run the benchmark, and it'll raise errors with specific instructions for how to fix it. Use cachalot for cold or modified <50 times per minutes (Most people should stick with only cachalot since you most likely won't need to scale to the point of needing cache-machine added to the bowl).
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  • 12
    Django Celery

    Django Celery

    Old Celery integration project for Django

    Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via messages, usually using a broker to mediate between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. Celery requires a message transport to send and receive messages.
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  • 13
    Django Extra Views

    Django Extra Views

    Django's class-based generic views are awesome

    Django's class-based generic views are awesome, let's have more of them. Django-extra-views is a Django package that introduces additional class-based views in order to simplify common design patterns such as those found in the Django admin interface. Supported Python and Django versions: Python 3.5+, Django 2.1–3.2, see tox.ini for an up-to-date list. Add support for pagination in ModelFormSetView and its derivatives, the goal being to be able to mimic the change_list view in Django's admin. Currently, this is proving difficult because of how Django's MultipleObjectMixin handles pagination.
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  • 14
    Django JET

    Django JET

    Modern responsive template for the Django admin interface

    Django JET has two kinds of licenses: open-source (AGPLv3) and commercial. Please note that using AGPLv3 code in your programs makes them AGPL compatible too. So if you don't want to comply with that we can provide you a commercial license (visit the Home page). The commercial license is designed for using Django JET in commercial products and applications without the provisions of the AGPLv3. Add URL-pattern to the URL patterns of your Django project urls.py file (they are needed for related–lookups and autocomplete). Dashboard is located into a separate application. So after a typical JET installation it won't be active. Add URL-pattern to the urlpatterns of your Django project urls.py file (they are needed for related–lookups and autocomplete).
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  • 15
    Django Notifications

    Django Notifications

    GitHub notifications alike app for Django

    django-notifications is a GitHub notification alike app for Django, it was derived from django-activity-stream. Notifications are actually actions events, which are categorized by four main components. To generate a notification anywhere in your code, simply import the notify signal and send it with your actor, recipient, and verb. Generating notifications is probably best done in a separate signal. Using django-model-utils, we get the ability to add queryset methods to not only the manager, but to all querysets that will be used, including related objects. To ensure users always have the most up-to-date notifications, django-notifications includes a simple javascript API for updating specific fields within a django template. Customize the display of notifications using javascript callbacks.
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  • 16
    Django REST framework

    Django REST framework

    Powerful and flexible toolkit for building Web APIs

    Django REST framework is a powerful and flexible toolkit for building Web APIs. Some reasons you might want to use REST framework: The Web browsable API is a huge usability win for your developers. Authentication policies including packages for OAuth1a and OAuth2. Serialization that supports both ORM and non-ORM data sources. Customizable all the way down - just use regular function-based views if you don't need the more powerful features. Extensive documentation, and great community support. Used and trusted by internationally recognised companies including Mozilla, Red Hat, Heroku, and Eventbrite. REST framework is a collaboratively funded project. If you use REST framework commercially we strongly encourage you to invest in its continued development by signing up for a paid plan.
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  • 17
    Django Rules

    Django Rules

    Awesome Django authorization, without the database

    rules is a tiny but powerful app providing object-level permissions to Django, without requiring a database. At its core, it is a generic framework for building rule-based systems, similar to decision trees. It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions, anything really. A good Django citizen. Seamless integration with Django views, templates and the Admin for testing for object-level permissions. Efficient and smart. No need to mess around with a database to figure out whether John really wrote that book. Simple. Dive in the code. You'll need 10 minutes to figure out how it works. Powerful. rules comes complete with advanced features, such as invocation context and storage for arbitrary data, skipping evaluation of predicates.
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  • 18
    Django friendly finite state machine

    Django friendly finite state machine

    Django friendly finite state machine support

    Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a mixin and template tags to integrate Django-fsm state transitions into the Django admin. FSM really helps to structure the code, especially when a new developer comes to the project. FSM is most effective when you use it for some sequential steps. Transition logging support could be achieved with help of django-fsm-log package.
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  • 19
    Django-dataplot enables developers using the Django web framework to seamlessly integrate data-driven graphical plots into their web pages.
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  • 20
    Dr0p1t-Framework

    Dr0p1t-Framework

    A framework that create an advanced stealthy dropper

    Dr0p1t-Framework is a penetration testing tool designed to generate advanced and stealthy droppers capable of delivering and executing payloads on target systems while evading detection mechanisms. A dropper is a type of malware used to download and install additional malicious software, and this framework focuses on making that process more flexible and difficult to detect. It provides a wide range of modules that allow users to customize payload delivery, persistence mechanisms, and execution methods. The framework includes features such as antivirus evasion, privilege escalation, and system persistence, enabling it to maintain access on compromised systems. It also incorporates techniques to avoid forensic analysis, such as self-deletion and cleaning traces after execution. The generated executables are optimized to be small and efficient, improving their ability to bypass security controls.
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  • 21

    Drid

    Multi-Purpose Automation Grid

    Console-based tool that will allow for multiple types of automation testing to run in parallel. Written in Python
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  • 22
    DrissionPage

    DrissionPage

    Python based web automation tool. Powerful and elegant

    DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone.
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  • 23
    Drupy is a Python implementation of the Drupal content management system. This project is no longer maintained. You can find the original codebase at https://github.com/brendoncrawford/drupy/
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  • 24
    Dshell

    Dshell

    Dshell is a network forensic analysis framework

    An extensible network forensic analysis framework. Enables rapid development of plugins to support the dissection of network packet captures. This is a major framework update to Dshell. Plugins written for the previous version are not compatible with this version, and vice versa. By extension, dpkt and pypcap have been replaced with Python3-friendly pypacker and pcapy (respectively). Enables development of external plugin packs, allowing the sharing and installation of new, externally-developed plugins without overlapping the core Dshell libraries. Plugins can now use all output modules, available to the command line switch, -O. That does not mean every output module will be useful to every plugin (e.g. using netflow output for a plugin that looks at individual packets), but they are available.
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  • 25
    EH Forwarder Bot

    EH Forwarder Bot

    An extensible message tunneling chat bot framework

    Codename EH Forwarder Bot (EFB) is an extensible message tunneling chat bot framework that delivers messages to and from multiple platforms and remotely controls your accounts. Since the majority of our channels are using polling for message retrieval, a stable internet connection is necessary for channels to run smoothly. An unstable connection may lead to slow response, or loss of messages. EFB uses a *nix user configuration style, which is described in details in Directories. In short, if you are using the default configuration, you need to create ~/.ehforwarderbot, and give read and write permission to the user running EFB. Currently, all modules that was submitted to us are recorded in the modules repository. You can choose the channels that fits your need the best. When you have successfully installed the modules of your choices, you can the use the configuration wizard which guides you to enable channels and middlewares, and continue to setup those modules.
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