Today I will introduce 20 Python libraries for commonly used tools. I believe you will feel that you can't live without them after reading them.
They are:(Recommended learning:Python video tutorial)
Requests.Written by Kenneth Reitz The most famous http library. Every Python programmer should have it.
Scrapy. If you are engaged in crawler-related work, then this library is also essential. After using it, you won't want to use other similar libraries again.
wxPython. A GUI (graphical user interface) tool for Python. I mainly use it as a replacement for tkinter. You will love it.
Pillow. It is a friendly fork of PIL (Python graphics library). More user-friendly than PIL, it is a must-have library for anyone working in the graphics field.
SQLAlchemy. A database library. It received mixed reviews. The decision whether to use it or not is up to you.
BeautifulSoup. I know it is slow, but this xml and html parsing library is very useful for newbies.
Twisted. The most important tool for web application developers. It has a very beautiful API and is used by many Python development experts.
NumPy. How could we lack such an important library? It provides many advanced mathematical methods for Python.
SciPy. Since we mentioned NumPy, we have to mention SciPy. This is a Python algorithm and mathematical tool library. Its functions attract many scientists from Ruby to Python.
matplotlib. A library for drawing data graphs. Very useful for data scientists or analysts.
Pygame. Which programmer doesn’t like playing games and writing games? This library will make you even more powerful when developing 2D games.
Pyglet. 3D animation and game development engine. The very famous Python version of Minecraft is made using this engine.
pyQT.Python GUI tool. This is my second choice after wxPython when developing user interfaces for Python scripts.
pyGtk. is also a Python GUI library. The famous Bittorrent client is made of it.
Scapy. Packet detection and analysis library written in Python.
pywin32. A Python library that provides methods and classes for interacting with windows.
nltk. Natural language toolkit. I know most people won't use it, but it's very versatile. It's a great library if you need to handle strings. But its function is much more than that, explore it yourself.
nose.Python testing framework. Used by thousands of Python programmers. If you do test-oriented development, it's essential.
SymPy.SymPy can do algebraic evaluation, differentiation, expansion, complex numbers, etc. It is packaged in a pure Python distribution.
IPython. It’s hard to overstate the functionality of this tool. It takes Python's prompt information to the extreme. Including completion information, historical information, shell functions, and many other aspects. Be sure to research it.
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