Introduction to python
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This document provides an introduction to the Python programming language. It discusses what Python is, its key features such as being multi-purpose, object oriented, and interpreted. It describes Python's releases and popularity compared to other languages. The document also covers how to run and write Python programs, popular IDEs and code editors, installing packages with pip, categories of public Python packages, and package popularity. It discusses Python modularity with Anaconda and conda versus pip for installation.
![Python public packages (category) [1/2]
❏ Admin Panels
❏ Algorithms and Design Patterns
❏ Audio
❏ Authentication
❏ Build Tools
❏ Built-in Classes Enhancement
❏ Caching
❏ ChatOps Tools
❏ CMS
❏ Code Analysis
❏ Command-line Interface Development
❏ Command-line Tools
❏ Compatibility
❏ Computer Vision
❏ Concurrency and Parallelism
❏ Configuration
❏ Cryptography
❏ Data Analysis
❏ Data Validation
❏ Data Visualization
❏ Database
❏ Database Drivers
❏ Date and Time
❏ Debugging Tools
❏ Deep Learning
❏ DevOps Tools
❏ Distributed Computing
❏ Distribution
❏ Documentation
❏ Downloader
❏ E-commerce
❏ Editor Plugins and IDEs
❏ Email
❏ Environment Management
❏ Files
❏ Foreign Function Interface
❏ Forms
❏ Functional Programming
❏ Game Development
❏ Geolocation
❏ GUI Development
❏ Hardware
❏ HTML Manipulation
❏ HTTP Clients
❏ Image Processing
❏ Implementations
❏ Interactive Interpreter
❏ Internationalization
❏ Job Scheduler
❏ Logging
❏ Machine Learning
Total: 63595 packages](https://image.slidesharecdn.com/introductiontopython-190820054621/85/Introduction-to-python-19-320.jpg)
![Python public packages (category) [2/2]
❏ Miscellaneous
❏ Natural Language Processing
❏ Network Virtualization
❏ Networking
❏ News Feed
❏ ORM
❏ Package Management
❏ Package Repositories
❏ Permissions
❏ Processes
❏ Queue
❏ Recommender Systems
❏ RESTful API
❏ Robotics
❏ RPC Servers
❏ Science
❏ Search
❏ Serialization
❏ Serverless Frameworks
❏ Specific Formats Processing
❏ Static Site Generator
❏ Tagging
❏ Template Engine
❏ Testing
❏ Text Processing
❏ Third-party APIs
❏ URL Manipulation
❏ Video
❏ Web Asset Management
❏ Web Content Extracting
❏ Web Crawling
❏ Web Frameworks
❏ WebSocket
❏ WSGI Servers
Total: 63595 packages
https://github.com/vinta/awesome-python](https://image.slidesharecdn.com/introductiontopython-190820054621/85/Introduction-to-python-20-320.jpg)
Introduction to python
- 1. Introduction to Python Delft, 19 Aug 2019
- 2. What is Python? ❏ Multi-purpose (Web, GUI, Scripting, etc.) ❏ Object Oriented ❏ Interpreted ❏ Both strongly typed and dynamically typed ❏ Focus on readability and productivity
- 3. Features ❏ Batteries Included ❏ Everything is an Object ❏ Interactive Shell ❏ Strong Introspection ❏ Cross Platform ❏ CPython, Jython, IronPython, PyPy
- 4. Releases ❏ Created in 1989 by Guido Van Rossum ❏ Python 1.0 released in 1994 ❏ Python 2.0 released in 2000 ❏ Python 3.0 released in 2008 ❏ Python 2.7 is the recommended version ❏ 3.0 adoption will take a few years
- 5. Python popularity among other languages TIOBE, Jan 2019 PyPL, Jan 2019
- 6. Python among other programming languages (benchmark) ❏ https://en.wikipedia.org/wiki/List_of_programm ing_languages_by_type ❏ https://attractivechaos.github.io/plb/ ❏ http://www.bioinformatics.org/benchmark/resu lts.html ❏ https://github.com/kostya/benchmarks
- 7. ❏ End-users just don’t care: 0.001 vs. 0.01 seconds no matter; horizontal scalability used ❏ More productive: more concise and expressive language and requires less time, effort, and lines of code to perform the same operations ❏ Execution Speed does not matter as much as Business Speed ❏ Rich set of standard libraries and frameworks ❏ Large community (packages, Q/A, discussions) Despite being slow, why is Python still popular?
- 8. How readable is Python?
- 9. How readable is Python?
- 10. How readable is Python?
- 11. How readable is Python?
- 12. How readable is Python?
- 13. When use and not use Python? Use ❏ Execution speed does not matter ❏ Everyone is new to programming ❏ Readability is more important Not use ❏ Speed-intensive applications including games that require high-performance ❏ OS or system-level applications (e.g., memory manipulation)
- 14. How to run a Python program ❏ Using embedded interpreter in IDE/Notebook ❏ Using stand-alone interpreter ❏ Using the interactive shell
- 15. How to write a Python program ❏ IDE: Eclipse + PyDev, Visual Studio, PyCharm, Spyder, Thonny ❏ Code editor: Sublime Text, Atom, GNU Emacs, Vi / Vim / Nano, Visual Studio Code, ... ❏ Notebook: Jupyter, Zeppelin
- 16. How to write a Python program ❏ Use IDE: write a complex program, collaboration in a team, many dependencies/libraries/binaries ❏ Use code editor: write a simple program ❏ Notebook: interactive, reporting-like deliverable
- 17. Most popular Python IDE/Code Editor https://insights.stackoverflow.com/survey/201 9#development-environments-and-tools
- 18. Python package installer (pip) ❏ pip is the recommended tool to install python package from python package public repos (such as public PyPI - and its mirrors) and private repos ❏ pip can install from either Source Distributions (sdist) or wheels, but if both are present on PyPI, pip will prefer a compatible wheel (pre-built).
- 19. Python public packages (category) [1/2] ❏ Admin Panels ❏ Algorithms and Design Patterns ❏ Audio ❏ Authentication ❏ Build Tools ❏ Built-in Classes Enhancement ❏ Caching ❏ ChatOps Tools ❏ CMS ❏ Code Analysis ❏ Command-line Interface Development ❏ Command-line Tools ❏ Compatibility ❏ Computer Vision ❏ Concurrency and Parallelism ❏ Configuration ❏ Cryptography ❏ Data Analysis ❏ Data Validation ❏ Data Visualization ❏ Database ❏ Database Drivers ❏ Date and Time ❏ Debugging Tools ❏ Deep Learning ❏ DevOps Tools ❏ Distributed Computing ❏ Distribution ❏ Documentation ❏ Downloader ❏ E-commerce ❏ Editor Plugins and IDEs ❏ Email ❏ Environment Management ❏ Files ❏ Foreign Function Interface ❏ Forms ❏ Functional Programming ❏ Game Development ❏ Geolocation ❏ GUI Development ❏ Hardware ❏ HTML Manipulation ❏ HTTP Clients ❏ Image Processing ❏ Implementations ❏ Interactive Interpreter ❏ Internationalization ❏ Job Scheduler ❏ Logging ❏ Machine Learning Total: 63595 packages
- 20. Python public packages (category) [2/2] ❏ Miscellaneous ❏ Natural Language Processing ❏ Network Virtualization ❏ Networking ❏ News Feed ❏ ORM ❏ Package Management ❏ Package Repositories ❏ Permissions ❏ Processes ❏ Queue ❏ Recommender Systems ❏ RESTful API ❏ Robotics ❏ RPC Servers ❏ Science ❏ Search ❏ Serialization ❏ Serverless Frameworks ❏ Specific Formats Processing ❏ Static Site Generator ❏ Tagging ❏ Template Engine ❏ Testing ❏ Text Processing ❏ Third-party APIs ❏ URL Manipulation ❏ Video ❏ Web Asset Management ❏ Web Content Extracting ❏ Web Crawling ❏ Web Frameworks ❏ WebSocket ❏ WSGI Servers Total: 63595 packages https://github.com/vinta/awesome-python
- 21. Python public package popularity https://stackoverflow.blog/2017/09/14/python- growing-quickly/
- 22. Python public package popularity
- 23. Python modularity Anaconda (app+ libraries+ binaries) *Miniconda is the light version of Anaconda (less packages)
- 24. Python modularity: conda vs pip pip installs only Python packages, but conda installs also the system binaries needed by the Python packages. Very important for a non-sudo user to leverage the server capability
- 25. Python modularity in practice
- 26. Basic Python Tutorial ❏ We’re using Anaconda ❏ Clone: https://gitlab.erc.monash.edu.au/andrease/Python4Maths