Posted in Python

Python Post #2 Python Additional Features (☆^_^☆)

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I hope that you can understand the flow of the above function. If not please go to the previous post and read through the .py file that I have shared …
Okay then,just to recap ,I have tried to make sure to put as much python programming concepts in one executable file.I hope it was useful for whatever you were doing!
The file, if it had been studied with as much effort as was applied in the making,then you should be familiar with

  • Python variables
  • Conditionals
  • Class
  • File handling
  • Exception handling

(PS:I randomly update since I am not very comfortable with my incoherent .py files )

-(๑☆‿ ☆#)ᕗ

Now that we are familiar with the basic syntax of Python,we can now dive into a bunch of special libraries that have been a part of my toolbelt and should be a part of yours as well. So here they are:
1. Requests. The most famous http library written by kenneth reitz. It’s a must have for every python developer.
2. Scrapy. If you are involved in webscraping then this is a must have library for you. After using this library you won’t use any other.
3. wxPython. A GUI toolkit for python. I have primarily used it in place of tkinter. You will really love it.
4. OpenCV. OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. It’s an image processing library for machines,like the eyes of an automated machine.
5. SQLAlchemy. A database library. Many love it and many hate it. The choice is yours.
6. BeautifulSoup. I know it’s slow but this xml and html parsing library is very useful for beginners.
7. Twisted. The most important tool for any network application developer. It has a very beautiful api and is used by a lot of famous python developers.
8. NumPy. How can we leave this very important library ? It provides some advance math functionalities to python.
9. SciPy. When we talk about NumPy then we have to talk about scipy. It is a library of algorithms and mathematical tools for python and has caused many scientists to switch from ruby to python.
10. matplotlib. A numerical plotting library. It is very useful for any data scientist or any data analyzer.
11. Pygame. Which developer does not like to play games and develop them ? This library will help you achieve your goal of 2d game development.
12. Scapy. A packet sniffer and analyzer for python made in python.
13. nltk. Natural Language Toolkit – I realize most people won’t be using this one, but it’s generic enough. It is a very useful library if you want to manipulate strings. But it’s capacity is beyond that. Do check it out.
14. nose. A testing framework for python. It is used by millions of python developers. It is a must have if you do test driven development.
15. SymPy. SymPy can do algebraic evaluation, differentiation, expansion, complex numbers, etc. It is contained in a pure Python distribution.
16. IPython. I just can’t stress enough how useful this tool is. It is a python prompt on steroids. It has completion, history, shell capabilities, and a lot more. Make sure that you take a look at it.


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