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+<button type="primary" size="xs" icon="glyphicon glyphicon-bookmark">[[programming_lagugages| Programming Language]]</button>
+====== Python ======
+<data programminglanguage>
+Full Name: Python
+Short Name: Python
+Description: A scripting language that is often used by software developers to add programmability to their applications, such as engineering-analysis tools or animation software.
+Company: Unkown
+Web: Yes
+Mobile: No
+Enterprise: Yes
+Embedded : No
+</data>
+<accordion>
+<panel title='What is Python?'>
+Python is a high-level programming language that is widely used for web development, data analysis, artificial intelligence, scientific computing, and more. It was first released in 1991 by Guido van Rossum.
+</panel><panel title='What are some features of Python?'>
+Python includes features such as dynamic typing, automatic memory management, and support for object-oriented, functional, and procedural programming. It also includes built-in libraries and frameworks for a wide range of tasks, including web development, data analysis, and scientific computing.
+</panel><panel title='How is Python used in web development?'>
+Python is commonly used in web development for server-side scripting, creating dynamic web pages, and interacting with databases and other web services. It can be used with a wide range of web frameworks, including Django, Flask, and Pyramid.
+</panel><panel title='What are some popular Python frameworks and libraries?'>
+Some popular Python frameworks and libraries for web development include Django, Flask, Pyramid, and Bottle. For data analysis and scientific computing, popular libraries include NumPy, Pandas, Matplotlib, and SciPy.
+</panel><panel title='Is Python a compiled or interpreted language?'>
+Python is an interpreted language, meaning that code is executed by an interpreter rather than compiled into machine code like in a compiled language such as C++.
+</panel><panel title='What is pip?'>
+Pip is the package installer for Python, which allows developers to easily install and manage external libraries and packages for their Python projects. It uses a command-line interface to search, install, upgrade, and uninstall packages.
+</panel><panel title='What is the difference between Python 2 and Python 3?'>
+Python 2 and Python 3 are two major versions of the Python language, with Python 3 being the most recent. The main differences between the two are syntax and features, with Python 3 being more consistent and efficient in some areas, but not fully backward compatible with Python 2. Many new libraries and frameworks are now only available for Python 3.
+</panel><panel title='What are some advantages of using Python?'>
+Some advantages of using Python include its ease of use, readability, and large standard library. It is also a versatile language that can be used for a wide range of applications, and has a large and active community of developers.
+</panel><panel title='How is Python used in data analysis and scientific computing?'>
+Python is commonly used in data analysis and scientific computing for tasks such as data manipulation, visualization, and statistical analysis. It can be used with libraries such as NumPy, Pandas, Matplotlib, and SciPy to perform these tasks efficiently.
+</panel><panel title='What is the difference between a list and a tuple in Python?'>
+In Python, a list is a mutable sequence of elements, while a tuple is an immutable sequence of elements. This means that the elements of a list can be changed after it is created, while the elements of a tuple cannot be changed.
+</panel><panel title='What is a lambda function in Python?'>
+A lambda function in Python is a small anonymous function that can take any number of arguments, but can only have one expression. It is used when a function is needed for a short period of time and does not need to be named.
+</panel><panel title='What is a virtual environment in Python?'>
+A virtual environment in Python is a self-contained environment that allows developers to install and manage dependencies and packages for a specific project without affecting the system-wide installation of Python or other projects. It is created using the venv module in Python.
+</panel><panel title='How is Python used in artificial intelligence and machine learning?'>
+Python is commonly used in artificial intelligence and machine learning for tasks such as data preprocessing, model training, and model deployment. It can be used with libraries such as TensorFlow, Keras, PyTorch, and Scikit-learn to perform these tasks efficiently.
+</panel></accordion>
+{{wp>Python_(programming_language)}}
+<callout type="" title="GitHub Topics" icon="fa fa-github">
+  * https://github.com/topics/python
+Python is a dynamically-typed garbage-collected programming language developed by Guido van Rossum in the late 80s to replace ABC. Much like the programming language Ruby, Python was designed to be easily read by programmers. Because of its large following and many libraries, Python can be implemented and used to do anything from webpages to scientific research.
+</callout>
+<callout type="" title="GitHub Trending" icon="fa fa-github">
+  * https://github.com/trending/python?since=monthly
+</callout>
+<jumbotron>
+===== Hello World =====
+<sxh python>
+import sys
+sys.stdout.write("Hello, world!\n")
+</sxh>
+<WRAP column right><wrap lo>Source: [[https://en.wikibooks.org/wiki/Computer_Programming/Hello_world|Wikibooks]]</wrap></WRAP>
+</jumbotron>
+===== Benefits =====
+  * Community
+  * Open-source
+  * Productivity speed
+  * Data Structures
+  * Well-structured and clean code
+  * Third-Party Modules
+<callout title="External links:">
+  * https://blog.feedspot.com/python_rss_feeds/
+</callout>
+See also: [[dev:programming_lagugages]]
+{{tag>programminglanguage dev-ml ai python}}
+=== ## ToDo ## ===
+  * Dask - https://www.nvidia.com/en-us/glossary/data-science/dask/
+  * Variables
+  * Control structures
+  * Functions
+  * Object-oriented programming (OOP)
+  * Classes
+  * Inheritance
+  * Polymorphism
+  * Encapsulation
+  * Iterators
+  * Generators
+  * Decorators
+  * Built-in data types
+  * Lists
+  * Tuples
+  * Dictionaries
+  * Sets
+  * Modules
+  * Packages
+  * Exception handling
+  * File handling
+  * Regular expressions
+  * Database connectivity
+  * GUI programming
+  * Web frameworks (e.g., Django, Flask)
+  * Data science libraries (e.g., NumPy, Pandas, Matplotlib)