Open Source Python Frameworks - Page 21
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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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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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Wooey
A Django app that creates automatic web UIs for Python scripts
Wooey is a simple web interface to run command line Python scripts. Think of it as an easy way to get your scripts up on the web for routine data analysis, file processing, or anything else. The project was inspired by how simply and powerfully sandman could expose users to a database and by how Gooey turns ArgumentParser-based command-line scripts into WxWidgets GUIs. Originally two separate projects (Django-based djangui by Chris Mitchell and Flask-based Wooey by Martin Fitzpatrick) it has been merged to combine our efforts. Enable the easy wrapping of any program in simple python instead of having to use language specific to existing tools such as Galaxy. Enable fellow lab members with no command line experience to utilize python scripts. Autodocument workflows for data analysis (simple model saving). -
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WorkStyle-py is a GTD Tools. TODO is only classified by TAG and status. It's easy to use and install. WorkStyle-py is work with Django Web Framework. With Java/php/Rails are comming.
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X-JHBuild is a framework for working with multiple repositories. It makes use of JHBuild and is specialized for working with modules that use Git as VCS.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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An Excel addin and server framework for implementing remote excel user-defined functions (UDFs). This framework is designed to provide a centralised warehouse of functions for Excel users (eg. within an organisation).
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"Yet Another Do-It-Yourself (Test) Automation Framework" specification. Use or modify one of the existing software implementations (hosted/referenced here), or implement the framework yourself. Download and read the spec for more details.
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The ZODBData Framework provides a Cocoa API to handle persistent objects stored in a Zope Object Database (ZODB).
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Zappa
Serverless Python
Zappa makes it super easy to build and deploy serverless, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance - and at a fraction of the cost of your current deployments! With a traditional HTTP server, the server is online 24/7, processing requests one by one as they come in. If the queue of incoming requests grows too large, some requests will time out. With Zappa, each request is given its own virtual HTTP "server" by Amazon API Gateway. AWS handles the horizontal scaling automatically, so no requests ever time out. Each request then calls your application from a memory cache in AWS Lambda and returns the response via Python's WSGI interface. After your app returns, the "server" dies. -
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Zappa - Serverless Python
Serverless Python
Zappa makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance - and at a fraction of the cost of your current deployments! With a traditional HTTP server, the server is online 24/7, processing requests one by one as they come in. If the queue of incoming requests grows too large, some requests will time out. With Zappa, each request is given its own virtual HTTP "server" by Amazon API Gateway. AWS handles the horizontal scaling automatically, so no requests ever time out. Each request then calls your application from a memory cache in AWS Lambda and returns the response via Python's WSGI interface. After your app returns, the "server" dies. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Zendriver
A blazing fast, async-first, undetectable webscraping
Zendriver is a modern Python web automation and scraping framework that leverages the Chrome DevTools Protocol to provide fast, asynchronous control over real browser instances. Unlike traditional tools that rely on Selenium or WebDriver, Zendriver communicates directly with the browser through CDP, enabling higher performance and more precise control over browser behavior. The framework is designed to be difficult to detect by anti-bot systems, making it suitable for advanced scraping and automation use cases where stealth is important. It features an async-first architecture that allows developers to build highly concurrent workflows, improving efficiency when handling multiple tasks or large-scale scraping operations. Zendriver also includes built-in utilities for managing cookies, browser profiles, and element selection, simplifying common automation tasks. -
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc. -
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agglo
Multi facets CASE/AGL for easy project developments
Agglo is a CASE (Computer Aided Software Engineering) or AGL (Atelier Génie Logiciel), whose aim is to facilitate installation ans use of various tools (either existing opensource tools, or agglo tools), in several facets of project development: - requirements management - unit tests - automated integration tests - toolkit for various languages (cpp, c, python, shell, xsl) other facets are to come ultimately: - coverage tests - planification - integration with hudson - code quality analysis - indicator production -
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bioweb
polyglot language framework to analyze genetic data
polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. The project’s focus on extreme quantization dramatically reduces memory footprint and energy consumption compared with traditional 16-bit or 32-bit LLMs, making it practical to deploy advanced language understanding and generation models on everyday machines. BitNet is built to scale across architectures, with configurable kernels and tiling strategies that adapt to different hardware, and it supports large models with impressive throughput even on modest resources. -
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bu-agent-sdk
An agent is just a for-loop
The bu-agent-sdk from the Browser Use project is a minimalistic Python framework that defines an AI agent as a simple loop of tool calls, aiming to keep abstractions low so developers can build autonomous agents without unnecessary complexity. At its core, the agent loop repeatedly queries a large language model, interprets its output, and executes defined “tools” — functions annotated with task names — to perform actions, allowing the agent to complete tasks like arithmetic, decision-making, or domain-specific work. The SDK emphasizes simplicity and control, avoiding heavy orchestration frameworks and instead letting developers specify exactly what tools an agent can employ and how it should signal task completion. This lightweight design means developers can rapidly prototype AI agent behavior, test custom tools, and integrate models like Anthropic’s Claude with minimal overhead. -
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cleversheep
Test framework and support library
A testing framework. This framework is an Xunit style framework, but its origins lie in system level testing. Also includes an amount of supporting code and miscellaneous library code. -
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cs-test
A Python test framework aimed at higher level testing.
Warning! This is in development. the following description is what will be - not what is. This framework is an Xunit style framework, but its origins lie in system level testing. It includes support for some of the trickier aspects of testing at this level, such as needing to track the contents of multiple log files, asynchronously interact with multiple networked components and the need to fake complex components. -
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An environment (library + IDE) that emulates Delphi but uses python as the programming language and wxPython as the graphical API. Starting with the library, we have a set of modules/classes that emulates the units/classes of the famous VCL.
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deoplete.nvim
Dark powered asynchronous completion framework for neovim/Vim8
deoplete.nvim is an asynchronous completion framework for Neovim and Vim 8. It was designed to provide extensible code-completion behavior while avoiding the blocking feel of older synchronous completion plugins. The framework can display completion candidates through Vim’s built-in completion interface and can be extended with dedicated completion sources. It supports a plugin ecosystem where different languages, tools, and contexts can provide their own candidate sources. deoplete.nvim is useful for users who want configurable, editor-native completion without adopting a full IDE. Although newer completion systems are now more common, it remains an important project in the evolution of asynchronous completion for Vim and Neovim. -
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dj-stripe
dj-stripe automatically syncs your Stripe Data to your local database
Dj-stripe is an extensible wrapper around the Stripe API that continuously syncs most of the Stripe Data to your local database as pre-implemented Django Models, out of the box! This allows you to use the Django ORM, in your code, to work with the data making it easier and faster! For example, if you need to interact with a customer subscription, you can use dj-stripe’s Subscription Model, in your code, to get the subscription data for that customer as well as the related models’ data too (if need be and potentially in 1 database query!) instead of making multiple slower and unreliable consecutive network calls only to parse through 1 or more of Stripe’s JSON like objects! We make it simple for you to collect sensitive data such as credit card numbers and remain PCI compliant. This means the sensitive data is sent directly to Stripe instead of passing through your server. We support all Stripe supported wallets including but not limited to Apple Pay and Google Pay. -
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django-bootstrap 4
Bootstrap 4 integration with Django
Bootstrap 4 integration for Django. The goal of this project is to seamlessly blend Django and Bootstrap 4. The django-bootstrap4 has some pre-configured settings. They can be modified by adding a dict variable called BOOTSTRAP4 in your settings.py and customizing the values you want. You can customize the output of django-bootstrap4 by writing your own templates. -
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django-braces
Reusable, generic mixins for Django
django-braces provides useful Mixins for Django's class-based views. Most of these mixins replicate the behavior of Django's function-based view decorators. Others solve common headaches with working with class-based views. django-braces is stable and time-tested. It does not receive a lot of updates and is not in active development. django-braces also only officially supports Python versions that are still receiving fixes and Django LTS versions. django-braces will work with a most modern versions of Python and Django, however.