Getting Started with Python Programming
Check out these Python tutorials and step up for becoming the next data scientist. Choose where to begin, learn at your own pace:
Unlock the latest Python tutorials – Start it from Scratch
- Introduction to Python
- Future of Python
- Python Environment Setup
- Features of Python
- Reasons to Learn Python
- Interesting Python Facts
- Why Python is in Demand
- Learn Python through Master Guide
- Python Best Practices
- Top Python Projects with Source Code
- Python for Machine Learning
- Python for Mathematics
- Python Case Studies
- Python Career Path
- How to become a Python Developer
- Python Syntax
- Python Statement, Indentation, and Comments
- Python Interpreter
- Python Advantages and Disadvantages
- Why Should I Learn Python?
- How a Fresher Get a Job in Python?
- Python Applications
- OpenCV & Computer Vision
- OpenCV Features
- OpenCV Environment Setup
- Read, Display & Save Image in OpenCV
- Computer Vision Techniques
- Computer Vision Project Ideas
- Python in Healthcare
- Python in Stock Market
- Python Advantages over Java
- Python Career Opportunities
- Python Variables and Data Types
- Python Variable Scope
- Python Identifiers
- Python Namespace and Scope
- Python Operators
- Python Bitwise Operator
- Python Comparison Operator
- Python Operator Precedence
- Python Numbers
- Python Strings
- Python Data Structures
- Python Lists
- Python Tuples
- Python Dictionaries
- Python Sets and Booleans
- Python Tuples vs Lists
- Sequences and Collections in Python
- Python Decision-Making
- Python Switch
- Python Loops
- Python Functions
- Python Built-in Functions
- Range() Function in python
- Python zip() Function
- Python eval() Function
- Python exec() Function
- Python Function arguments
- Python Recursion
- Python Terminologies Part I
- Python Terminologies Part II
- What’s new in Python 3.8
- Python vs Scala
- Python vs Java
- Python vs R
- Python at Netflix
- How to create a Perfect Python Resume
- Best Python Books
- Python For Beginners – Infographic
- Python Features – Infographic
- Python Career – Infographic
Level up to more exciting and challenging Python tutorials
- Python Classes
- Python Methods
- Python Methods vs Functions
- Constructors in Python
- Python Objects
- Python Inheritance
- Multiple Inheritance in Python
- Python Operator Overloading
- Python property Class
- Python Compilers
- Python Modules
- Python OS Module
- Python pprint Module
- Python sys Module
- Python repr Function
- Python Directory
- Copying Files with Python
- Renaming Files with Python
- Zipping Files with Python
- Python File I/O
- Reading and Writing Files in Python
- Python Slicing and slice() Construtor
- List Comprehension in Python
- Python Iterables
- Python Iterators
- Python Decorators
- Python Generators
- Python Generators vs Iterators
- Closure in Python
- Python array Module
- Generating Random Numbers in Python
- Python Modules-Counter, Defaultdict, Ordereddict, Namedtuple
- Python Counter Module
- Python defaultdict Module
- Python OrderedDict Module
- Python namedtuple() Factory Function
- Python Packages
- Python Modules vs Packages
- Python itertools Module
- Python Date and Time
- Python Datetime Object
- Python Calendar Module
- Lambda expressions in python
- Assert Statements in Python
- Ternary Operators
- Shallow Copy and Deep Copy- Python
Master essential Python skills and evolve as an expert
- Python Errors and Exceptions
- Python Exception Handling
- Python 3 Extensions
- Python Tools
- XML Processing in Python3
- Networking in python 3
- Sending mail with Python 3
- GUI Programming in Python 3
- CGI Programming in Python
- Python Multi-threading
- Multiprocessing with Python
- Python Subprocess module
- Python Regular Expressions
- SciPy with Python
- NumPy with Python
- Accessing Database with Python
- Python Image Processing
- Unit Testing with Python
- Logging in Python
- Serialization in Python
- Python Debugger
- Python Forensics
- Python Virtual Environments and Packages
- Python Virtual Environments and Packages
- Important Python Libraries
- Best Python Web frameworks
- Python Django Framework
- Python Pandas
- Python Flask
- Python PyQT
- 56 Python Open-source Projects
- Python Interview Questions for Beginners
- Python Interview Questions for Intermediates
- Python Interview Questions for Experts
- Python – 70+ Project Ideas & Datasets
- Python Project Ideas
- Python Project- Detecting Fake News
- Python Project- Detecting Parkinson’s Disease
- Python Project- Color Detection
- Python Project- Speech Emotion Recognition
- Python Project- Breast Cancer Classification
- Python Project- Gender & Age Detection
- Python Project- Handwritten Digit Recognition
- Python Project- Chatbot
- Python Project- Drowsiness Detection System
- Python Project- Traffic Signs Recognition
- Python Project- Image Caption Generator
- Python Quiz- Part 1
- Python Quiz- Part 2
- Python Quiz- Part 3
Implement your Python learning and step into the world of Data Science
- Learn Python for Data Science
- Mastering Python for Data Science
- Data Science with Python
- Python Data Science Environment Setup
- Data Scientist Salary in India
- Data Science Skills
- Data Operations and Data Cleansing
- Processing CSV, JSON, and XLS data
- Python Relational databases
- Python NoSQL databases
- Stemming and Lemmatization
- Data Wrangling and Aggregation
- Python Matplotlib
- Box Plots and Scatter Plots
- Bubble Charts and 3D Charts
- Python Heatmaps
- Histograms and Bar Plots
- Geographical Data and Graph Data
- Time Series Analysis
- Central Tendency and Variance
- Normal, Binomial, Poisson, Bernoulli Distributions
- p-Value and Correlation
- chi-Square Test and Linear Regression
Learn how Python is important for Machine Learning
- Machine Learning with Python
- Python Machine Learning Environment Setup
- Data Preprocessing, Analysis & Visualization- ML
- Training Data and Test Data- ML
- Python Machine Learning Techniques
- Python Machine Learning Algorithms
- Python Machine Learning Applications
- Deep Learning with Python
- Python Deep Learning Environment Setup
- Python Deep Learning Applications
- Python Deep Learning Libraries and Frameworks
- Deep Neural Networks- Deep Learning
- Computational Graphs- Deep Learning
Execute your Python skills to develop Artificial Intelligence
Crack Your Next Python Interview
Want to make it through the next interview you will appear for? Hone your skills with our three-part series of Python interview questions widely asked in the industry. With basic to advanced questions of Python, this is a great way to expand your repertoire and boost your confidence.
Python Infographic – What is Python?
Check out more cool technologies related to Python
Exploring the Python Language
Let’s take a look at some facts about Python programming and its philosophies.
What is Python?
Python is a general-purpose, object-oriented, high-level programming language. It is interpreted and dynamically-typed. Its readability along with its powerful libraries have given it the honor of being the preferred language for exciting careers like that of a data scientist or a machine learning engineer. Python is also often chosen as the language to introduce students to programming in schools and universities. This Python tutorials package help you to learn it from scratch and you will become a master of Python soon.
Guido Van Rossum
Python History
Python first appeared in 1990 as a hobby project. Then came along Python 2.0 on 16 October 2000, and Python 3.0 followed on December 3, 2008, after a long period of testing. While most Python code still runs on version 2.7, the future belongs to version 3.0. The end-of-life for Python 2.7 is scheduled to be January 1, 2020; this is to buy some time for the transition for code from Python 2.0. What we recognize today as Python finds its etymological origins in his penchant for Monty Python’s Flying Circus, a British sketch comedy from 1969.
While the community dubs Guido the Benevolent Dictator For Life (BDFL), he permanently resigned from this post on July 12, 2018.
Python Quotes
“The fun of coding Python should be in seeing short, concise, readable classes that describe a lot of action in a small amount of clear code — not in reams of trivial code that bores the reader to death.” – Guido van Rossum, Founder of Python
“Everyone knows that any scripting language shootout that doesn’t depict Python as the best language is faulty by design.” – Max M
“The canonical, “Python is a great first language”, elicited, “Python is a great last language!” – Noah Spurrier
“Python has been an essential part of Google since the beginning and remains so as the system grows and evolves. Today many Google engineers use Python, and we’re looking for more people with skills in this language.” – Peter Norvig, Search Quality Director at Google
“Python is fast enough for our site and allows us to generate maintainable features in record times, with a minimum of developers.” – Cuong Do, Software Architect at YouTube
Python Facts
- Python is a fully packed war machine with its applications in all domains. It’s used in web development, data science, machine learning, networking, scripting, automation, web scraping, game development, scientific and numeric calculations, 3D graphics, robotics, etc.
- In the GitHub’s state of the octoverse 2019 annual survey reports, Python overtook Java to become the second most popular language after JavaScript.
- Python has large community support, many developers and people learning on their own support each other and continuously contributes to the development of Python.
- Google has been supporting Python from the beginning. It has integrated Python in its workflow and Python is also called as the official language of Google.
Python Features
Let’s see some of the interesting features of Python:
- Easy to read, write and learn – Python is called a beginner-friendly language because of its simplicity. Python is easier to read, write and learn than other general programming languages.
- Free and open-source – Python is freely available to download and it’s also open-source, which means you can create your flavour of Python by modifying the code and even distribute it.
- Dynamic typed – Python is an interpreted language and the data type of Python is decided during the runtime and not at compile time. We don’t have to declare the data type for each variable.
- Portable – Python is highly portable, you don’t have to change the code in order to shift your program from one operating system to another.
- Large standard library – Python standard library comes with lots of implementations so you don’t have to write code for every task. The standard library comes packed with libraries for regular expressions, documentation-generator, unit-testing, web browsers, threading, database, emails, image manipulation, etc.
Python Frameworks
Frameworks let developers automate redundant tasks. This allows users to focus on application logic rather than the routine elements.
Let us discuss some of the popular frameworks of Python:
- Django – Django is one of the most loved full-stack frameworks for web development. It follows the DRY(Don’t Repeat Yourself) principle and offers rapid development.
- Flask – Flask is a microframework for web-based applications that is well suited for easy and small projects.
- Robot framework – Robot is an open-source testing framework for test-driven development. It’s an extensible keyword-driven automation framework for acceptance testing.
- Tornado – The tornado framework is mainly built to handle asynchronous programming. It is highly scalable due to non-blocking system which was inspired by the node.js
- CherryPy- CherryPy is an object-oriented Python framework which is a non-full stack web framework. It is used to provide CRUD functionalities for applications and helps in managing project.
Zen of Python
20 software principles inspire the design of Python; in June of 1999, Tim Peters articulated 19 of those. As an easter egg, you can find this in the interpreter by entering import this.
