Firstly start with the installation of Python in your system. Just visit on Python’s official site, download the latest version and you are good to go.
Once the installation has completed, you may use IDLE to write and run Python code. Now we are going to list out some topics to start with learning Python.
It will take almost 1 – 1.5 weeks to cover all the basic stuff.
- The Python shell, basic arithmetic.
- Control structures.
- Accepting user input, Strings & Typecasting.
- Looping in Python: For & While loops.
- Exception handling.
- Functions, modules & Imports.
This section will be a bit tough especially if you don’t know about object-oriented programming concepts. Take the help of some resources which we have mentioned and with some practice, you will be able to understand the concepts.
These concepts will be widely used in making complex applications so understand these topics very well.
It may take 1 – 1.5 weeks to learn.
- Object oriented programming in Python
- Lists & List functions
- Regular Expressions
- List comprehension
- List slicing
- String formatting
- Lambdas
- List, Dictionaries & Tuples
There are so many frameworks for web applications in Python some of them are Django, Flask, Bottle, Tornado, and Pyramid.
A high level web framework mostly used in startups and enterprise for web development. It follows the MVC pattern and you can use multiple databases such as PostgreSQL, MySQL, SQLite, and Oracle.
If you are a complete beginner and not aware of the terminology authentication, URL routing, API and models then you will feel a lot of pain while learning Django but take your time, have patience, go through some more resources and understand each line of code. Slowly and gradually you will understand everything.
Learning Django may take 2 – 2.5 weeks.
Flask is one of the easiest microframework to learn in Python. If you wish to develop a simple and lightweight web application then Flask is suitable for that. It is not as powerful and extensive as Django still provides features such as support for unit testing and building REST APIs.
Learning Flask will take 1 – 1.5 weeks.
Tkinter, PyQT, Kivy, WxPython or PyGUI libraries are very good for building desktop-based applications.
Tkinter is open source library and it allows you to build desktop GUI applications using Python. Learning Tkinter is simple and provides a graphical interface. It will take around 1 week to learn Tkinter. Official Docs
PyQt is one of the most powerful cross-platform GUI library owned by Nokia. It combines Python programming and the Qt library. It can be used to design graphical user interfaces for a desktop application. Official Docs
It can be used to create desktop applications also it supports platforms like Android, iOS, Linux & Raspberry Pi. Official Docs
Numpy, Pandas, Seaborn, Bokeh, SciPy, Matplotlib these libraries are good for data analysis. These libraries are helpful for those who want to become data analysts/ data scientists. Learning Numpy or Pandas will take around 1 week.
It is an array-processing package and provides high-performance array object. It is widely used for scientific computing with Python and provides essential features. Official Docs
Pandas is also a very good open-source library that is used for data analysis. It provides high-level data structures (such as DataFrame) and a vast variety of tools for analysis. It also can translate complex operations in a few commands. Using this library, data manipulation becomes a much easier task. Official Docs
Most popular deep learning library developed by Google. It is a computational framework used to express algorithms that involve numerous Tensor operations. Official Docs
A machine learning library for Python, designed to work with numerical libraries such as SciPy & NumPy. Official Docs
It can handle dynamic computation graphs on the go. It also provides easy to use API. Official Docs
The Jupyter Notebook is an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text. Jupyter Notebook is maintained by the people at Project Jupyter. Officaial Docs
Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It saves hours or days of work for a programmer.
Scrapy is an application framework for crawling websites and extracting structured data for data mining, information processing or historical archival.
Source : Geeks for Geeks