Mastering Python can change your life; using Python effectively can greatly enhance your efficiency!—— Follow me to unlock a world of efficiency with Python.Many people often feel that after learning Python, aside from daily office tasks, studying, data collection, and AI training deployment, they are unsure of what else to do with it. In fact, there are currently a large number of AI model projects and software developed with Python. Today, I will introduce some well-known software and projects developed with Python. The following projects are personally collected and organized; please credit the source if reproduced.Yingdao RPANot entirely developed in Python, but Python accounts for a significant portion, with a large number of Python environments and libraries packaged internally. After installation, you can see 3GB of files on the hard drive, containing a lot of Python files. Many libraries have been introduced in my previous articles.
My ABC ToolboxA large number of commands are written as Python scripts, and you can completely write these application commands in Python according to their functionality. I also have many similar tools.
Odoo
Open-source Enterprise Resource Planning (ERP) system developed using Python and PostgreSQL, covering multiple business modules such as finance and human resources. Reply with Odoo to get the project address.
A small company can completely use this open-source ERP to replace expensive paid ERPs and secondary development.
Calibre
eBook management software that supports format conversion and eBook library management, with core functions implemented in Python.
Python libraries used, etc.
OpenStack
The core components of OpenStack (such as Nova, Neutron, Cinder, etc.) are mostly written in Python, with the business logic and API services of its control plane primarily relying on Python. This is due to Python’s rich library support, good readability, and development efficiency, which can meet the needs for rapid iteration and cross-platform deployment in OpenStack’s complex architecture. Some lower-level components (such as those involving high-performance computing and network forwarding) may use languages like C/C++ to enhance performance. Many companies are using it.
Anki
Flashcard software that uses spaced repetition algorithms to help users efficiently memorize knowledge points (such as language words, medical terms), with core algorithms and plugin systems developed in Python.
However, to optimize performance and implement some system interaction features, Anki also incorporates other technologies, such as using C++ for some interface rendering and low-level operations, while the mobile version (like AnkiDroid) is primarily developed in Java.
Zim Lightweight Desktop Note Software
Supports Markdown syntax, mind mapping, and task management, suitable for personal knowledge organization and team collaboration. Written entirely in Python, it has a simple interface and low resource usage, with data stored in text files to ensure cross-device compatibility and data security.
uTools
A multifunctional efficiency tool platform that supports functionality expansion through plugins, many of which are developed in Python. Users can achieve quick search, translation, format conversion, and other functions through it.
Honeyview
A lightweight image viewer, with some auxiliary functions (such as batch format conversion, simple editing) implemented in Python to efficiently handle image-related tasks.
Blender (partially developed in Python)
Blender is an open-source 3D modeling, animation, and rendering software. Many of Blender’s features and plugins are developed using Python, and Python’s powerful libraries and frameworks enable efficient 3D graphics processing. Its core engine and most features are written in C and C++, but Blender includes a complete Python interpreter, allowing users to automate operations, extend functionality, and customize workflows through Python scripts. A large number of plugins and tools (such as modeling aids, batch processing for animations, etc.) are developed in Python, giving Blender high flexibility and extensibility.
Ansible Automation Platform
Red Hat® Ansible® Automation Platform is a unified solution for implementing strategic automation. It integrates security, functionality, integration items, and flexibility to meet the needs for cross-domain scalable automation, orchestrating basic workflows, and optimizing IT operations to successfully adopt enterprise-level AI technologies.
Developed using Python. Ansible can automate server management, application configuration, and software deployment, with Python’s concise syntax and powerful libraries enabling efficient automation tasks.
Reddit was founded in 2005, initially developed in Common Lisp, and later migrated to Python in 2006. This migration was mainly due to Python’s richer library ecosystem, more maintainable code, and broader developer community support. Python remains an important part of its technology stack to this day.
Dropbox
The founders of Dropbox chose Python as the primary development language in the early stages of their startup because it allowed for rapid implementation of core functionalities such as file synchronization and storage management, and it had high development efficiency suitable for rapid iteration. Many of the client applications (especially early versions) and backend service logic heavily relied on Python.
However, as the business scaled, Dropbox gradually introduced other languages (such as Go, Rust, etc.) to optimize performance-sensitive modules, but Python remains an important part of its technology stack, continuously playing a role in business logic, data analysis, and other aspects. This also reflects Python’s applicability in rapid development and complex business scenarios.
Of course, there are now many AI deep learning models and tools developed and packaged in Python, such as those for voice cloning, voice separation, speech synthesis, OCR, PDF processing, automatic translation, image processing, lip-syncing, digital humans, podcasts, etc., so Python can help you build a powerful ecological application.
Historical articles on Python:
Basic articles for learning Python
Basics of Basics (suitable for beginners)
Must-Know OS Standard Library in Python
Overview of Built-in Functions in Python, Simple and Intuitive
Application of Regular Expressions in Office
Must-Know sys Standard Library in Python
Python Knowledge Handy Reference【Save the Essentials】
Using Domestic Sources for pip to Speed Up Python Library Installation
Usage of lambda in Python
Must-Know socket in Python
Four Ways to Package Python Projects into exe
Common Programming Handy Reference Atlas for Python
Common Programming Knowledge Handy Reference Atlas for Python II
Four Progress Bars in Python
Timestamp Calculation in Python
Seven Ways to Read and Write Configuration Files in Python
Concurrency with Multiple Coroutines in Python using asyncio Library
Mathematics and Computation
Topic: The Three Musketeers of Python Mathematical Operations – Pandas
Topic: The Three Musketeers of Python Mathematical Operations – Numpy
Topic: The Three Musketeers of Python Mathematical Operations – A Brief Discussion on Scipy
The Wonderful Collision of Python and Mathematics, Making Computation Easy
Data Analysis and Visualization
Python Visualization with Bokeh Library
Python Visualization with pyechart
Matplotlib Turns Mathematics into Visualization
Python Visualization Charts with Seaborn Library
CuteCharts – The Adorable Python Hand-drawn Chart Library
Web Scraping
Notes on the New Version of Selenium 4.0
Must-Know BeautifulSoup Library in Python
Practical: Easily Implement HTTP Requests with Requests Library
Scrapy to be Supplemented
urllib to be Supplemented
Playwright Library – Let Python Help You with Browser Tasks
Image Processing
Must-Know OpenCV Library in Python
Image Processing Library in Python – Pillowimageio to be SupplementedNatural Language Processing
Chinese Word Segmentation in Python with Jieba Library
Natural Language Processing in Python with spaCy Library
NLTK to be Introduced
Office Applications
Python Task Scheduling Tool Schedule, Let It Help You Work on Time
Automating Word Document Processing with Python-docx
Five Ways to Write Data into CSV Files in Python
Several Ways to Read and Write Files in Python
Getting Started with Python Documentation Auto-generation using Sphinx Library
Python’s Swiss Army Knife for PDF Operations – PyMuPDF Library
PyPDF2 to be Supplemented
Python Automation Operation Library PyAutoGUI
Industrial ApplicationsEfficiency Applications of Python in Mechanical Drawing with CadQuery LibrarySoftware Interfaces and GamesPyQt Development Library to be IntroducedTkinter Interface Library to be IntroducedUsing Pygame to Teach You How to Create a Plane Battle GameProject Engineering Related
Getting Started with Python’s Automated Testing Library Pytest
Python Project Logging with Loguru Library
Must-Know threading Library in Python
Using Lightweight Database SQLite in Python Projects
Must-Know Cryptography Library in Python
Exploring the Faker Library, a Powerful Tool for Generating Test Data
Thread Pool Relatedconcurrent.futures to be Introduced
Fun Projects
Exploring the Stars and the Sea with Python using Skyfield Library
Python’s Super Fun Library – Turtle Graphics
Deep Use of Python in Music Creation【For Audio Processing Reference】
System Hardware, etc.
System Monitoring and Process Management Tool in Python – Psutil Library
platformdirs to be Supplemented
pypiwin32to be Supplemented
pyserialto be Supplemented
pywifito be Supplemented
Python Web Development Related
Flask to be IntroducedDjango to be IntroducedVideo Processingffmpeg-python to be UpdatedAccurately Dubbing Videos in Bulk with PythonPython Development, a Tool for Converting Chinese Videos into 30+ Languages
Others
Python Application Universe, Thoroughly Discussing Various Uses
Organizing Personal Library Files Installed in pip list
Popular Articles
Python Video Processing Tools, Assisting Learning and Recreation
Comprehensive Review of Domestic GPU Rental Platforms (The Most Comprehensive on the Internet, No Exceptions)
Notes on the New Version of Selenium 4.0
Four Progress Bars in Python
Python’s Super Fun Library – Turtle Graphics
Must-Know BeautifulSoup Library in Python
Must-Know OpenCV Library in Python
Must-Know threading Library in Python
Must-Know OS Standard Library in Python
Reading Large CSV Files with Python and Searching Content
Python Task Scheduling Tool Schedule, Let It Help You Work on Time
Creating a Custom Tomato Timer exe with Python to Improve Work Efficiency and Easily Achieve Time Management
Using Domestic Sources for pip to Speed Up Python Library Installation
Five Ways to Write Data into CSV Files in Python
Ways to Read and Write Files in Python
Four Ways to Package Python Projects into exe
Python Automation Operation Library PyAutoGUI
Keyboard and Mouse Automation Operation with Pynput Library
Historical Articles on Intelligent Agents
Detailed Analysis and Operation Modification of Intelligent Agent OWL Architecture
Detailed Breakdown of OpenManus Intelligent Agent
Historical Articles on AIRecord of Deploying Speech-to-Text Deep Learning Tools on Local CPU
Guide to Feeding DeepSeek API for Multi-turn Dialogue with Python
Alternative Solutions for Busy DeepSeek Servers (Ongoing Follow-up)
The Most Comprehensive Alternative Solutions and Evaluations for DeepSeek on the Internet, No Exceptions
Building Your Own DeepSeek R1 and Knowledge Base – A Step-by-Step Tutorial
Instructions for Feeding Suno API with Python
Comprehensive Review of Domestic GPU Rental Platforms (The Most Comprehensive on the Internet, No Exceptions)
Recreating Your Digital Avatar – Voice Avatar
Case Applications