Python Development Glossary (CloudMonk.io)
Python Development Glossary
#redirect Python Development Glossary
* Python Developer Glossary
Return to Python Standard Library Glossary, Python DevOps Glossary, Python Concurrency Glossary, Python Functional Programming Glossary, Python Data Science Glossary, Python Concurrency Glossary, Python Development, Python Software Engineering Glossary, Python Software Architecture Glossary, Python Design Pattern Glossary, General Programming Glossary, pip Glossary
* Provide a Python developer glossary of the top 100 Python development concepts sorted by the most commonly used. For each concept include a brief description and the URL for the Python official documentation and the appropriate GitHub repo, pypa.io Python package, Conda or other source code repository. Answer using MediaWiki format.
* Provide a Python developer glossary of the top 100 Python development concepts sorted by the most commonly used. For each Python concept include a brief description and the URL for the Python official documentation, include the URL to the appropriate rosettacode.org link, include the URL for the pypi.org pip link, include the appropriate URL of the Python 3 Module of the Week pymotw.com, and the Python standard library source code repository or appropriate GitHub repo. Answer using MediaWiki format.
* Provide a Python module glossary of the top 100 Python modules that are not part of the Python Standard Library sorted by the most commonly used. For each Python module include a brief description and the URL for the Python official documentation, include the URL to the appropriate rosettacode.org link, include the URL for the pypi.org pip link, include the appropriate URL of the Python 3 Module of the Week pymotw.com, and the Python standard library source code repository or appropriate GitHub repo. Answer using MediaWiki format.
* Provide a Python module glossary of the top 100 Python modules that are not part of the Python Standard Library sorted by the most commonly used. For each Python module include a brief description and the URL for the Python official documentation, include the URL for the pypi.org pip link, and include the URL for the appropriate GitHub repo. Answer using MediaWiki format.
Creating an exhaustive glossary of the top 100 Python development concepts, including descriptions and links to official documentation and relevant repositories, is a substantial task. This list will cover a mix of foundational elements, standard library modules, and popular third-party packages, along with their primary usage within the Python ecosystem. Note that the Python ecosystem is vast and dynamic, with many packages and tools available, so this list focuses on those concepts that are widely recognized and utilized across various Python applications.
```mediawiki
= Python Developer Glossary =
1. Variables
Stores data that can be used and manipulated in a program.
[Documentation: https://docs.python.org/3/tutorial/introduction.html#using-python-as-a-calculator]
2. Data Types
Defines the type of data: `int`, `float`, `str`, `bool`, `list`, `tuple`, `dict`, `set`.
[Documentation: https://docs.python.org/3/library/stdtypes.html]
3. Functions
A block of code which only runs when it is called.
[Documentation: https://docs.python.org/3/tutorial/controlflow.html#defining-functions]
4. Modules
A file containing Python definitions and statements.
[Documentation: https://docs.python.org/3/tutorial/modules.html]
5. Packages
A way of structuring Python’s module namespace by using “dotted module names”.
[Documentation: https://docs.python.org/3/tutorial/modules.html#packages]
6. Virtual Environments
A tool to keep dependencies required by different projects separate.
[Documentation: https://docs.python.org/3/tutorial/venv.html]
7. pip
The package installer for Python.
[Documentation: https://pip.pypa.io/en/stable/]
[Source: https://github.com/pypa/pip]
8. Control Flow Tools
Includes statements like `if`, `for`, `while`, and `try` for controlling the flow of execution.
[Documentation: https://docs.python.org/3/tutorial/controlflow.html]
9. List Comprehensions
Provides a concise way to create lists.
[Documentation: https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions]
10. Generators
A simple way of creating iterators using a function.
[Documentation: https://docs.python.org/3/tutorial/classes.html#generators]
11. Decorators
A way to modify functions or methods using other functions.
[Documentation: https://docs.python.org/3/glossary.html#term-decorator]
12. Classes/Objects
Python’s approach towards object-oriented programming.
[Documentation: https://docs.python.org/3/tutorial/classes.html]
13. Exceptions
Handling errors detected during execution.
[Documentation: https://docs.python.org/3/tutorial/errors.html]
14. File I/O
Reading and writing files.
[Documentation: https://docs.python.org/3/tutorial/inputoutput.html#reading-and-writing-files]
15. Regular Expressions
Provides regular expression matching operations.
[Documentation: https://docs.python.org/3/library/re.html]
16. NumPy
A library for numerical operations.
[Documentation: https://numpy.org/doc/stable/]
[Source: https://github.com/numpy/numpy]
17. pandas
A library for data manipulation and analysis.
[Documentation: https://pandas.pydata.org/pandas-docs/stable/]
[Source: https://github.com/pandas-dev/pandas]
18. Matplotlib
A plotting library for creating static, interactive, and animated visualizations.
[Documentation: https://matplotlib.org/stable/contents.html]
[Source: https://github.com/matplotlib/matplotlib]
19. SciPy
A library used for scientific computing and technical computing.
[Documentation: https://docs.scipy.org/doc/scipy/reference/]
[Source: https://github.com/scipy/scipy]
20. Jupyter Notebook
An open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.
[Documentation: https://jupyter-notebook.readthedocs.io/en/stable/]
[Source: https://github.com/jupyter/notebook]
21. Flask
A micro web framework.
[Documentation: https://flask.palletsprojects.com/en/2.0.x/]
[Source: https://github.com/pallets/flask]
22. Django
A high-level Python Web framework that encourages rapid development and clean, pragmatic design.
[Documentation: https://docs.djangoproject.com/en/3.2/]
[Source: https://github.com/django/django]
23. Asyncio
A library to write concurrent code using the async/await syntax.
[Documentation: https://docs.python.org/3/library/asyncio.html]
24. PyTest
A framework that makes it easy to write small tests, yet scales to support complex functional testing.
[Documentation: https://docs.pytest.org/en/stable/]
[Source: https://github.com/pytest-dev/pytest]
25. Requests
A simple, yet elegant HTTP library.
[Documentation: https://docs.python-requests.org/en/master/]
[Source: https://github.com/psf/requests]
26. Beautiful Soup
A library for pulling data out of HTML and XML files.
[Documentation: https://www.crummy.com/software/BeautifulSoup/bs4/doc/]
[Source: https://www.crummy.com/software/BeautifulSoup/]
27. SQLAlchemy
A SQL toolkit and Object-Relational Mapping (ORM) library.
[Documentation: https://www.sqlalchemy.org/]
[Source: https://github.com/sqlalchemy/sqlalchemy]
28. TensorFlow
An end-to-end open-source platform for machine learning.
[Documentation: https://www.tensorflow.org/overview]
[Source: https://github.com/tensorflow/tensorflow]
29. PyTorch
An open-source machine learning library.
[Documentation: https://pytorch.org/docs/stable/index.html]
[Source: https://github.com/pytorch/pytorch]
30. scikit-learn
A machine learning library for Python.
[Documentation: https://scikit-learn.org/stable/documentation.html]
[Source: https://github.com/scikit-learn/scikit-learn]
31. virtualenv
A tool to create isolated Python environments.
[Documentation: https://virtualenv.pypa.io/en/latest/]
[Source: https://github.com/pypa/virtualenv]
32. Poetry
A tool for dependency management and packaging in Python.
[Documentation: https://python-poetry.org/docs/]
[Source: https://github.com/python-poetry/poetry]
33. Black
The uncompromising Python code formatter.
[Documentation: https://black.readthedocs.io/en/stable/]
[Source: https://github.com/psf/black]
34. MyPy
An optional static type checker for Python.
[Documentation: http://mypy-lang.org/]
[Source: https://github.com/python/mypy]
35. Type Hints
A way to specify the expected data types of function arguments, return values, and variables.
[Documentation: https://docs.python.org/3/library/typing.html]
36. Sphinx
A tool that makes it easy to create intelligent and beautiful documentation.
[Documentation: https://www.sphinx-doc.org/en/master/]
[Source: https://github.com/sphinx-doc/sphinx]
37. tox
A generic virtualenv management and test command-line tool.
[Documentation: https://tox.readthedocs.io/en/latest/]
[Source: https://github.com/tox-dev/tox]
38. Conda
An open-source package management system and environment management system.
[Documentation: https://docs.conda.io/en/latest/]
[Source: https://github.com/conda/conda]
39. Celery
An asynchronous task queue/job queue based on distributed message passing.
[Documentation: https://docs.celeryproject.org/en/stable/]
[Source: https://github.com/celery/celery]
40. FastAPI
A modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.
[Documentation: https://fastapi.tiangolo.com/]
[Source: https://github.com/tiangolo/fastapi]
41. Dash
A productive Python framework for building web applications.
[Documentation: https://dash.plotly.com/introduction]
[Source: https://github.com/plotly/dash]
42. Plotly
An interactive, open-source, and browser-based graphing library for Python.
[Documentation: https://plotly.com/python/]
[Source: https://github.com/plotly/plotly.py]
43. Pygame
A set of Python modules designed for writing video games.
[Documentation: https://www.pygame.org/docs/]
[Source: https://github.com/pygame/pygame]
44. PyInstaller
A program that converts Python programs into stand-alone executables, under Windows, Linux, and Mac OS X.
[Documentation: https://www.pyinstaller.org/]
[Source: https://github.com/pyinstaller/pyinstaller]
45. configparser
A library that provides a structure similar to what’s found in Microsoft Windows INI files.
[Documentation: https://docs.python.org/3/library/configparser.html]
46. logging
The standard library for implementing flexible event logging systems.
[Documentation: https://docs.python.org/3/library/logging.html]
47. argparse
The recommended command-line
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Python: Python Variables, Python Data Types, Python Control Structures, Python Loops, Python Functions, Python Modules, Python Packages, Python File Handling, Python Errors and Exceptions, Python Classes and Objects, Python Inheritance, Python Polymorphism, Python Encapsulation, Python Abstraction, Python Lists, Python Dictionaries, Python Tuples, Python Sets, Python String Manipulation, Python Regular Expressions, Python Comprehensions, Python Lambda Functions, Python Map, Filter, and Reduce, Python Decorators, Python Generators, Python Context Managers, Python Concurrency with Threads, Python Asynchronous Programming, Python Multiprocessing, Python Networking, Python Database Interaction, Python Debugging, Python Testing and Unit Testing, Python Virtual Environments, Python Package Management, Python Data Analysis, Python Data Visualization, Python Web Scraping, Python Web Development with Flask/Django, Python API Interaction, Python GUI Programming, Python Game Development, Python Security and Cryptography, Python Blockchain Programming, Python Machine Learning, Python Deep Learning, Python Natural Language Processing, Python Computer Vision, Python Robotics, Python Scientific Computing, Python Data Engineering, Python Cloud Computing, Python DevOps Tools, Python Performance Optimization, Python Design Patterns, Python Type Hints, Python Version Control with Git, Python Documentation, Python Internationalization and Localization, Python Accessibility, Python Configurations and Environments, Python Continuous Integration/Continuous Deployment, Python Algorithm Design, Python Problem Solving, Python Code Readability, Python Software Architecture, Python Refactoring, Python Integration with Other Languages, Python Microservices Architecture, Python Serverless Computing, Python Big Data Analysis, Python Internet of Things (IoT), Python Geospatial Analysis, Python Quantum Computing, Python Bioinformatics, Python Ethical Hacking, Python Artificial Intelligence, Python Augmented Reality and Virtual Reality, Python Blockchain Applications, Python Chatbots, Python Voice Assistants, Python Edge Computing, Python Graph Algorithms, Python Social Network Analysis, Python Time Series Analysis, Python Image Processing, Python Audio Processing, Python Video Processing, Python 3D Programming, Python Parallel Computing, Python Event-Driven Programming, Python Reactive Programming.
Variables, Data Types, Control Structures, Loops, Functions, Modules, Packages, File Handling, Errors and Exceptions, Classes and Objects, Inheritance, Polymorphism, Encapsulation, Abstraction, Lists, Dictionaries, Tuples, Sets, String Manipulation, Regular Expressions, Comprehensions, Lambda Functions, Map, Filter, and Reduce, Decorators, Generators, Context Managers, Concurrency with Threads, Asynchronous Programming, Multiprocessing, Networking, Database Interaction, Debugging, Testing and Unit Testing, Virtual Environments, Package Management, Data Analysis, Data Visualization, Web Scraping, Web Development with Flask/Django, API Interaction, GUI Programming, Game Development, Security and Cryptography, Blockchain Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, Scientific Computing, Data Engineering, Cloud Computing, DevOps Tools, Performance Optimization, Design Patterns, Type Hints, Version Control with Git, Documentation, Internationalization and Localization, Accessibility, Configurations and Environments, Continuous Integration/Continuous Deployment, Algorithm Design, Problem Solving, Code Readability, Software Architecture, Refactoring, Integration with Other Languages, Microservices Architecture, Serverless Computing, Big Data Analysis, Internet of Things (IoT), Geospatial Analysis, Quantum Computing, Bioinformatics, Ethical Hacking, Artificial Intelligence, Augmented Reality and Virtual Reality, Blockchain Applications, Chatbots, Voice Assistants, Edge Computing, Graph Algorithms, Social Network Analysis, Time Series Analysis, Image Processing, Audio Processing, Video Processing, 3D Programming, Parallel Computing, Event-Driven Programming, Reactive Programming.
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