Open Source Python Software Development Software - Page 12
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Python Software Development Software
View 5757 business solutionsBrowse free open source Python Software Development Software and projects below. Use the toggles on the left to filter open source Python Software Development Software by OS, license, language, programming language, and project status.
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any cluster. Find templates (Lightning Apps), modify them and publish your own. Lightning Apps can even be full standalone ML products! Run on your laptop for free! Download the code and type 'lightning run app'. Feel free to ssh into any machine and run from there as well. In research, we often have multiple separate scripts to train models, finetune them, collect results and more. -
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notebooker
Productionise & schedule your Jupyter Notebooks
Productionise and schedule your Jupyter Notebooks, just as interactively as you wrote them. Notebooker is a webapp which can execute and parametrise Jupyter Notebooks as soon as they have been committed to git. The results are stored in MongoDB and searchable via the web interface, essentially turning your Jupyter Notebook into a production-style web-based report in a few clicks. -
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plotly.py
The interactive graphing library for Python
plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud. -
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script-server
Web UI for your scripts with execution management
Script-server is a Web UI for scripts. As an administrator, you add your existing scripts into Script server and other users would be able to execute them via a web interface. The UI is very straightforward and can be used by non-tech people. No script modifications are needed - you configure each script in Script server and it creates the corresponding UI with parameters and takes care of validation, execution, etc. -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. It supports libjpeg-turbo as well. libpng and libjpeg must be available at compilation time in order to be available. TorchVision also offers a C++ API that contains C++ equivalent of python models. -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data. -
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urllib3
Python HTTP library with thread-safe connection pooling
urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. Thread safety, connection pooling. Client-side TLS/SSL verification. File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, brotli, and zstd encoding. Proxy support for HTTP and SOCKS. 100% test coverage. Professional support for urllib3 is available as part of the Tidelift Subscription. Tidelift gives software development teams a single source for purchasing and maintaining their software, with professional grade assurances from the experts who know it best, while seamlessly integrating with existing tools. -
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uwsgi-nginx-flask
Docker image with uWSGI and Nginx for Flask applications in Python
Image with uWSGI and Nginx for Flask apps in Python running in a single container. Docker image with uWSGI and Nginx for Flask web applications in Python running in a single container. Optionally using Alpine Linux. This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container. The combination of uWSGI with Nginx is a common way to deploy Python Flask web applications. It is widely used in the industry and would give you decent performance. If you are starting a new project, you might benefit from a newer and faster framework based on ASGI instead of WSGI (Flask and Django are WSGI-based). Also, if you want to use new technologies like WebSockets it would be easier (and possible) with a newer framework based on ASGI, like FastAPI or Starlette. As the standard ASGI was designed to be able to handle asynchronous code like the one needed for WebSockets. -
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Gammu
Cellular manager for mobile phones/modems
Gammu is a cellular manager for mobile phones/modems. It contains libraries and functions for ringtones,logos,phonebook,SMS,etc. (used by external software), a command line version (with backup/restore) and SMS gateway (with MySQL and PostgreSQL supp -
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SIGAR (System Information Gatherer and Reporter) is a cross-platform, cross-language library and command-line tool for accessing operating system and hardware level information in Java, Perl and .NET.
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Free Java Flowchart simulator / interpreter
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cx_Oracle is a Python extension module that allows access to Oracle databases and conforms to the Python database API specification version 2.0 Project has moved to GitHub (https://github.com/oracle/python-cx_Oracle) and new builds are available at PyPI (https://pypi.python.org/pypi/cx_Oracle).
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A regex tool -- A Python GUI for creating, testing and debugging regular expressions for the Python programming language. Kodos utilizes the pyqt library for it's interface. Screenshots available on project homepage.
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Anymail
Django email backends and webhooks for Amazon SES, Mailgun, Mailjet
Anymail lets you send and receive email in Django using your choice of transactional email service providers (ESPs). It extends the standard django.core.mail with many common ESP-added features, providing a consistent API that avoids locking your code to one specific ESP (and making it easier to change ESPs later if needed). Integration of each ESP’s sending APIs into Django’s built-in email package, including support for HTML, attachments, extra headers, and other standard email features. Extensions to expose common ESP-added functionality, like tags, metadata, and tracking, with code that’s portable between ESPs. Inbound message support, to receive email through your ESP’s webhooks, with simplified, portable access to attachments and other inbound content. Anymail maintains compatibility with all Django versions that are in mainstream or extended support, plus (usually) a few older Django versions, and is extensively tested on all Python versions supported by Django. -
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Baby Buddy
Helps caregivers track sleep, feedings, diaper changes, and tummy time
A buddy for babies! Helps caregivers track sleep, feedings, diaper changes, tummy time and more to learn about and predict baby's needs without (as much) guesswork. A buddy to help caregivers track sleep, feedings, diaper changes, and tummy time to learn about and predict baby's needs without (as much) guess work. A demo of Baby Buddy is available on Heroku. The demo instance resets every hour. Baby Buddy is available in a variety of languages thanks to the efforts of numerous translators. Language can be set on a per-user basis from the user settings page (/user/settings/). -
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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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Dash
Build beautiful web-based analytic apps, no JavaScript required
Dash is a Python framework for building beautiful analytical web applications without any JavaScript. Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. Dash apps are very lightweight, requiring only a limited number of lines of Python or R code; and every aesthetic element can be customized and rendered in the web. It’s also not just for dashboards. You have full control over the look and feel of your apps, so you can style them to look any way you want. -
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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. 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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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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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases. -
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Eel
A Python library for making simple Electron-like HTML/JS GUI apps
Eel is a little Python library for making simple Electron-like offline HTML/JS GUI apps, with full access to Python capabilities and libraries. Eel hosts a local webserver, then lets you annotate functions in Python so that they can be called from Javascript, and vice versa. Eel is designed to take the hassle out of writing short and simple GUI applications. If you are familiar with Python and web development, probably just jump to this example which picks random file names out of the given folder (something that is impossible from a browser). There are several options for making GUI apps in Python, but if you want to use HTML/JS (in order to use jQueryUI or Bootstrap, for example) then you generally have to write a lot of boilerplate code to communicate from the Client (Javascript) side to the Server (Python) side. -
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Errbot
Chatbot daemon that connects to your favorite chat services
Errbot is a chatbot, a daemon that connects to your favorite chat service and brings your tools into the conversation. The goal of the project is to make it easy for you to write your own plugins so you can make it do whatever you want, a deployment, retrieving some information online, trigger a tool via an API, troll a co-worker, etc. Errbot is being used in a lot of different contexts, chatops (tools for devops), online gaming chatrooms like EVE, video streaming chatrooms like livecoding.tv, home security, etc. Extending Errbot and adding your own commands can be done by creating a plugin, which is simply a class derived from BotPlugin. The docstrings will be automatically reused by the !help command. We aim to give you all the tools you need to build a customized bot safely, without having to worry about basic functionality. As such, Errbot comes with a wealth of features out of the box. One of the main goals of Errbot is to make it easy to share your plugin with others as well. -
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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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Full Stack FastAPI and PostgreSQL
Full stack, modern web application generator
Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic interactive documentation. Many other features including automatic validation, serialization, interactive documentation, authentication with OAuth2 JWT tokens, etc. Celery worker that can import and use models and code from the rest of the backend selectively. REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time.
