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Release Schedules

• Python 3.9 Release Schedule
• Python 3.8 Release Schedule
• Python 3.7 Release Schedule
• Python 3.6 Release Schedule
• Python 3.5 Release Schedule
• Python 2.7 Release Schedule

OpenPGP Public Keys

Source and binary executables are signed by the release manager or binary builder using their OpenPGP key. Release files for currently supported releases are signed by the following:

• Pablo Galindo Salgado (3.10.x and 3.11.x source files and tags) (key id: 64E628F8D684696D)
• Steve Dower (Windows binaries) (key id: FC62 4643 4870 34E5)
• Łukasz Langa (3.8.x and 3.9.x source files and tags) (key id: B269 95E3 1025 0568)
• Ned Deily (macOS binaries, 3.7.x / 3.6.x source files and tags) (key ids: 2D34 7EA6 AA65 421D, FB99 2128 6F5E 1540, and Apple Developer ID DJ3H93M7VJ)
• Larry Hastings (3.5.x source files and tags) (key id: 3A5C A953 F73C 700D)
• Benjamin Peterson (2.7.z source files and tags) (key id: 04C3 67C2 18AD D4FF and A4135B38)

Release files for older releases which have now reached end-of-life may have been signed by one of the following:

• Anthony Baxter (key id: 0EDD C5F2 6A45 C816)
• Georg Brandl (key id: 0A5B 1018 3658 0288)
• Martin v. Löwis (key id: 6AF0 53F0 7D9D C8D2)
• Ronald Oussoren (key id: C9BE 28DE E6DF 025C)
• Barry Warsaw (key ids: 126E B563 A74B 06BF, D986 6941 EA5B BD71, and ED9D77D5)

You can import a person's public keys from a public keyserver network server you trust by running a command like:

gpg --recv-keys [key id]

or, in many cases, public keys can also be found at keybase.io. On the version-specific download pages, you should see a link to both the downloadable file and a detached signature file. To verify the authenticity of the download, grab both files and then run this command:

gpg --verify Python-3.6.2.tgz.asc

Note that you must use the name of the signature file, and you should use the one that's appropriate to the download you're verifying.

• (These instructions are geared to GnuPG and Unix command-line users.)

Other Useful Items

• Looking for 3rd party Python modules? The Package Index has many of them.
• You can view the standard documentation online, or you can download it in HTML, PostScript, PDF and other formats. See the main Documentation page.
• Information on tools for unpacking archive files provided on python.org is available.
• Tip: even if you download a ready-made binary for your platform, it makes sense to also download the source. This lets you browse the standard library (the subdirectory Lib) and the standard collections of demos (Demo) and tools (Tools) that come with it. There's a lot you can learn from the source!
• There is also a collection of Emacs packages that the Emacsing Pythoneer might find useful. This includes major modes for editing Python, C, C++, Java, etc., Python debugger interfaces and more. Most packages are compatible with Emacs and XEmacs.

Want to contribute?

Want to contribute? See the Python Developer's Guide to learn about how Python development is managed.

Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.

The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python web site, https://www.python.org/, and may be freely distributed. The same site also contains distributions of and pointers to many free third party Python modules, programs and tools, and additional documentation.

The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). Python is also suitable as an extension language for customizable applications.

This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well.

For a description of standard objects and modules, see The Python Standard Library. The Python Language Reference gives a more formal definition of the language. To write extensions in C or C++, read Extending and Embedding the Python Interpreter and Python/C API Reference Manual. There are also several books covering Python in depth.

This tutorial does not attempt to be comprehensive and cover every single feature, or even every commonly used feature. Instead, it introduces many of Python’s most noteworthy features, and will give you a good idea of the language’s flavor and style. After reading it, you will be able to read and write Python modules and programs, and you will be ready to learn more about the various Python library modules described in The Python Standard Library.

The Glossary is also worth going through.

• 1. Whetting Your Appetite
• 2. Using the Python Interpreter
  • 2.1. Invoking the Interpreter
    • 2.1.1. Argument Passing
    • 2.1.2. Interactive Mode
  • 2.2. The Interpreter and Its Environment
    • 2.2.1. Source Code Encoding
• 3. An Informal Introduction to Python
  • 3.1. Using Python as a Calculator
    • 3.1.1. Numbers
    • 3.1.2. Strings
    • 3.1.3. Lists
  • 3.2. First Steps Towards Programming
• 4. More Control Flow Tools
  • 4.1. if Statements
  • 4.2. for Statements
  • 4.3. The range() Function
  • 4.4. break and continue Statements, and else Clauses on Loops
  • 4.5. pass Statements
  • 4.6. match Statements
  • 4.7. Defining Functions
  • 4.8. More on Defining Functions
    • 4.8.1. Default Argument Values
    • 4.8.2. Keyword Arguments
    • 4.8.3. Special parameters
      • 4.8.3.1. Positional-or-Keyword Arguments
      • 4.8.3.2. Positional-Only Parameters
      • 4.8.3.3. Keyword-Only Arguments
      • 4.8.3.4. Function Examples
      • 4.8.3.5. Recap
    • 4.8.4. Arbitrary Argument Lists
    • 4.8.5. Unpacking Argument Lists
    • 4.8.6. Lambda Expressions
    • 4.8.7. Documentation Strings
    • 4.8.8. Function Annotations
  • 4.9. Intermezzo: Coding Style
• 5. Data Structures
  • 5.1. More on Lists
    • 5.1.1. Using Lists as Stacks
    • 5.1.2. Using Lists as Queues
    • 5.1.3. List Comprehensions
    • 5.1.4. Nested List Comprehensions
  • 5.2. The del statement
  • 5.3. Tuples and Sequences
  • 5.4. Sets
  • 5.5. Dictionaries
  • 5.6. Looping Techniques
  • 5.7. More on Conditions
  • 5.8. Comparing Sequences and Other Types
• 6. Modules
  • 6.1. More on Modules
    • 6.1.1. Executing modules as scripts
    • 6.1.2. The Module Search Path
    • 6.1.3. “Compiled” Python files
  • 6.2. Standard Modules
  • 6.3. The dir() Function
  • 6.4. Packages
    • 6.4.1. Importing * From a Package
    • 6.4.2. Intra-package References
    • 6.4.3. Packages in Multiple Directories
• 7. Input and Output
  • 7.1. Fancier Output Formatting
    • 7.1.1. Formatted String Literals
    • 7.1.2. The String format() Method
    • 7.1.3. Manual String Formatting
    • 7.1.4. Old string formatting
  • 7.2. Reading and Writing Files
    • 7.2.1. Methods of File Objects
    • 7.2.2. Saving structured data with json
• 8. Errors and Exceptions
  • 8.1. Syntax Errors
  • 8.2. Exceptions
  • 8.3. Handling Exceptions
  • 8.4. Raising Exceptions
  • 8.5. Exception Chaining
  • 8.6. User-defined Exceptions
  • 8.7. Defining Clean-up Actions
  • 8.8. Predefined Clean-up Actions
• 9. Classes
  • 9.1. A Word About Names and Objects
  • 9.2. Python Scopes and Namespaces
    • 9.2.1. Scopes and Namespaces Example
  • 9.3. A First Look at Classes
    • 9.3.1. Class Definition Syntax
    • 9.3.2. Class Objects
    • 9.3.3. Instance Objects
    • 9.3.4. Method Objects
    • 9.3.5. Class and Instance Variables
  • 9.4. Random Remarks
  • 9.5. Inheritance
    • 9.5.1. Multiple Inheritance
  • 9.6. Private Variables
  • 9.7. Odds and Ends
  • 9.8. Iterators
  • 9.9. Generators
  • 9.10. Generator Expressions
• 10. Brief Tour of the Standard Library
  • 10.1. Operating System Interface
  • 10.2. File Wildcards
  • 10.3. Command Line Arguments
  • 10.4. Error Output Redirection and Program Termination
  • 10.5. String Pattern Matching
  • 10.6. Mathematics
  • 10.7. Internet Access
  • 10.8. Dates and Times
  • 10.9. Data Compression
  • 10.10. Performance Measurement
  • 10.11. Quality Control
  • 10.12. Batteries Included
• 11. Brief Tour of the Standard Library — Part II
  • 11.1. Output Formatting
  • 11.2. Templating
  • 11.3. Working with Binary Data Record Layouts
  • 11.4. Multi-threading
  • 11.5. Logging
  • 11.6. Weak References
  • 11.7. Tools for Working with Lists
  • 11.8. Decimal Floating Point Arithmetic
• 12. Virtual Environments and Packages
  • 12.1. Introduction
  • 12.2. Creating Virtual Environments
  • 12.3. Managing Packages with pip
• 13. What Now?
• 14. Interactive Input Editing and History Substitution
  • 14.1. Tab Completion and History Editing
  • 14.2. Alternatives to the Interactive Interpreter
• 15. Floating Point Arithmetic: Issues and Limitations
  • 15.1. Representation Error
• 16. Appendix
  • 16.1. Interactive Mode
    • 16.1.1. Error Handling
    • 16.1.2. Executable Python Scripts
    • 16.1.3. The Interactive Startup File
    • 16.1.4. The Customization Modules