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Showing 56 open source projects for "good"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Furo
A clean customizable documentation theme for Sphinx
...Responsive, adapting perfectly to the available screen space, to work on all sorts of devices. Customizable, change the color palette, font families, logo and more! Easy to navigate, with carefully-designed sidebar navigation and inter-page links. Good-looking content, through clear typography and well-stylized elements. Good looking search, helps readers find what they want quickly. Biased for smaller docsets, intended for smaller documentation sets, where presenting the entire hierarchy in the sidebar is not overwhelming. Furo allows customizing the icons that are presented in the page footer. ... -
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Django Rules
Awesome Django authorization, without the database
...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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Jinja
Ultra fast and expressive template engine
...It offers full unicode support, a sandboxed environment for safe executions, and so much more. Jinja is among the most widely used template engines for Python, and for good reason. It is both beautiful and powerful, and makes a template designer’s job a lot easier. Jinja is inspired by Django's templating system, but steps it up with an expressive language that results in more powerful tools, plus an automatic HTML escaping system for utmost security. Internally Jinja is based on Unicode and will run on a wide range of Python versions. -
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Django Ninja
Fast, Async-ready, Openapi, type hints based framework
...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. -
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Faker for Python
Python package that generates fake data for you
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating your codebase to support Python 3 so you can enjoy the latest features Faker has to offer. ... -
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Oh My Zsh (ohmyzsh)
A framework for managing your zsh configuration
...Once installed, your terminal shell will become the talk of the town or your money back! With each keystroke in your command prompt, you'll take advantage of the hundreds of powerful plugins and beautiful themes. It's a good idea to inspect the install script from projects you don't yet know. You can do that by downloading the install script first, looking through it so everything looks normal, then running it. -
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H2O Wave
Realtime Web Apps and Dashboards for Python and R
...Easily share your apps with end-users, get feedback, improve and iterate. ~10MB static executables for Linux, Windows, OSX, BSD, Solaris on AMD64, 386, ARM, PPC. Run it on a RPi Zero for great good! -
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Slack Machine
A simple, yet powerful and extendable Slack bot
Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly but also allows for easy code organization. A plugin can look as simple as this: -
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PyGitHub
Typed interactions with the GitHub API v3
PyGitHub is a Python library to access the GitHub REST API. This library enables you to manage GitHub resources such as repositories, user profiles, and organizations in your Python applications. PyGithub is a Python library to use the Github API v3. With it, you can manage your Github resources (repositories, user profiles, organizations, etc.) from Python scripts. Should you have any question, any remark, or if you find a bug, or if there is something you can do with the API but not with... -
Free and Open Source HR SoftwareGive your HR team the tools they need to streamline administrative tasks, support employees, and make informed decisions with the OrangeHRM free and open source HR software.
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simple-modern-uv
A minimal, modern Python project template
...It aims to be “small but serious,” giving you the essentials—testing, linting, type checking, formatting, GitHub Actions—without burying you in boilerplate. The layout is opinionated around a pyproject.toml so configuration is centralized and easy to inspect. Defaults encourage good hygiene from day one, including reproducible builds and a clean release workflow to PyPI. Because the template is intentionally compact, it’s easy to understand and customize for libraries, CLIs, or small services. It’s a fast way to start new Python projects with modern tooling and guardrails already in place. -
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MkDocs
Project documentation with Markdown
...Documentation source files are written in Markdown, and configured with a single YAML configuration file. Start by reading the introductory tutorial, then check the User Guide for more information. There's a stack of good-looking themes available for MkDocs. Choose between the built in themes: mkdocs and readthedocs, select one of the third-party themes listed on the MkDocs Themes wiki page, or build your own. Get your project documentation looking just the way you want it by customizing your theme and/or installing some plugins. Modify Markdown's behavior with Markdown extensions. ... -
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Graphene-Django
Integrate GraphQL into your Django project
...It is worth reading the core graphene docs to familiarize yourself with the basic utilities. Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus in this tutorial is to give a good understanding of how to connect models from Django ORM to Graphene object types. GraphQL presents your objects to the world as a graph structure rather than a more hierarchical structure to which you may be accustomed. In order to create this representation, Graphene needs to know about each type of object which will appear in the graph. -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
Prompt-eng-interactive-tutorial is a comprehensive, hands-on tutorial that teaches the craft of prompt engineering with Claude through guided, executable lessons. It starts with the anatomy of a good prompt and moves into techniques that deliver the “80/20” gains—separating instructions from data, specifying schemas, and setting evaluation criteria. The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts the way you would debug code. Lessons include building prompts from scratch for common tasks like extraction, classification, transformation, and step-by-step reasoning, with checkpoints that let you compare your outputs against solid baselines. ... -
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
...Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports. Need to synthesize one or multiple data types? We have you covered. ... -
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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.... -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
...You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder. -
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Boltons
250+ constructs, recipes, and snippets which extend the Python library
...Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. In many cases the respective boltons module will describe 3rd-party alternatives worth investigating when use cases outgrow boltons. If you’ve found a natural “next-step” library worth mentioning, consider filing an issue! ... -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
...It contains numerous Python scripts organized by topic (lists, dictionaries, loops, functions, classes, modules, etc.), each with code examples, explanations, test assertions, and links to further readings. The design supports “learn by doing”: you can modify the code, run the tests, see how behavior changes, and thus internalize Python language features, idioms, and good style practices (including linting and PEP8). Because it is organized in bite-sized chunks, it’s ideal for beginners or people refreshing their Python skills who want to revisit syntax and common patterns before moving into larger frameworks or applications. It also supports usage as a reference: if you forgot how a list comprehension works or how decorators behave, you can quickly open the relevant script. -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is... -
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MegaLinter
Mega-Linter analyzes 50 languages, 22 formats, 21 tooling formats etc.
...By using code formatters and code linters, you ensure that your code base is easier to read and respects best practices, from the kick-off to each step of the project lifecycle. Not all developers have the good habit to use linters in their IDEs, making code reviews harder and longer to process. -
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wemake-python-styleguide
The strictest and most opinionated python linter ever!
Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to... -
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pythondialog
Python module to build dialogs for terminal-based applications
This is a Python module for doing terminal-based user interaction. It wraps the dialog/Xdialog program, and provides a nice, object-oriented programming model. -
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ComfyUI Experiments
Some experimental custom nodes
ComfyUI_experiments is a playground repo for trying out new, sometimes unstable ideas in the ComfyUI ecosystem before they graduate into more official nodes or workflows. It’s where experimental nodes, pipelines, or integrations can live without breaking users’ main installations. The project is aimed at power users and contributors who want to see “what’s possible” with ComfyUI beyond the stable set of features. Because it is exploratory, the code may change often, rely on specific... -
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Gerapy
Distributed Crawler Management Framework Based on Scrapy
Distributed Crawler Management Framework Based on Scrapy, Scrapyd, Scrapyd-Client, Scrapyd-API, Django and Vue.js. Someone who has worked as a crawler with Python may use Scrapy. Scrapy is indeed a very powerful crawler framework. It has high crawling efficiency and good scalability. It is basically a necessary tool for developing crawlers using Python. If you use Scrapy as a crawler, then of course we can use our own host to crawl when crawling, but when the crawl is very large, we can’t run the crawler on our own machine, a good one. The method is to deploy Scrapy to a remote server for execution. ... -
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DeepCTR
Package of deep-learning based CTR models
...With the great success of deep learning,DNN-based techniques have been widely used in CTR prediction task. The data in CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. Since DNN are good at handling dense numerical features,we usually map the sparse categorical features to dense numerical through embedding technique.
