Improve python roadmap (#7323)
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# Code Formatting |
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Python code formatting is crucial for maintaining readability, consistency, and reducing errors. Black is a code formatter for Python. It is a tool that automatically formats Python code to adhere to the PEP 8 style guide. It is a great tool to use in your Python projects to ensure that your code is formatted consistently and correctly. |
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Visit the following resources to learn more: |
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- [@official@Pylint for Python](https://www.pylint.org/) |
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- [@official@Black Documentation](https://black.readthedocs.io/en/stable/) |
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# Common Packages and Modules |
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Python has a rich ecosystem of packages and modules that can be used to get the most out of the language. |
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Python has a rich ecosystem of packages and modules that can be used to get the most out of the language. A package is essentially a directory that contains multiple modules and subpackages. A module is a single file that contains a collection of related functions, classes, and variables. Modules are the basic building blocks of Python code organization. A module can be thought of as a container that holds a set of related code. |
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Here are some common Python packages that are widely used in various domains: |
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Visit the following resources to learn more: |
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- [requests](https://docs.python-requests.org/en/latest/) |
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- [pathlib](https://docs.python.org/3/library/pathlib.html) |
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- [asyncio](https://docs.python.org/3/library/asyncio.html) |
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- [dataclasses](https://docs.python.org/3/library/dataclasses.html) |
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- [python-dotenv](https://pypi.org/project/python-dotenv/) |
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- [numpy](https://numpy.org/doc/stable/) |
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- [pandas](https://pandas.pydata.org/docs/) |
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- [polars](https://github.com/pola-rs/polars) |
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- [@official@requests](https://docs.python-requests.org/en/latest/) |
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- [@official@pathlib](https://docs.python.org/3/library/pathlib.html) |
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- [@official@asyncio](https://docs.python.org/3/library/asyncio.html) |
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- [@official@dataclasses](https://docs.python.org/3/library/dataclasses.html) |
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- [@official@python-dotenv](https://pypi.org/project/python-dotenv/) |
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- [@official@numpy](https://numpy.org/doc/stable/) |
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- [@official@pandas](https://pandas.pydata.org/docs/) |
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# Conditionals |
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Conditional Statements in Python perform different actions depending on whether a specific condition evaluates to true or false. Conditional Statements are handled by IF-ELIF-ELSE statements and MATCH-CASE statements in Python. |
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Conditional Statements in Python perform different actions depending on whether a specific condition evaluates to true or false. Conditional Statements are handled by *if-elif-else* statements and MATCH-CASE statements in Python. |
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Visit the following resources to learn more: |
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- [@article@Python Conditional Statements: IF…Else, ELIF & Switch Case](https://www.guru99.com/if-loop-python-conditional-structures.html) |
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- [@article@Conditional Statements in Python](https://realpython.com/python-conditional-statements/) |
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- [@article@How to use a match statement in Python](https://learnpython.com/blog/python-match-case-statement/) |
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- [@article@W3Schools - Python Conditions and If statements](https://www.w3schools.com/python/python_conditions.asp) |
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- [@article@Python Conditional Statements](https://www.guru99.com/if-loop-python-conditional-structures.html) |
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- [@article@How to Use a Match Statement in Python](https://learnpython.com/blog/python-match-case-statement/) |
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# Context Manager |
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Context managers are a contruct in Python that allows you to set up context for a block of code, and then automatically clean up or relase resources when the block is exited. It is most commonly used with the `with` statement. |
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Context Managers are a construct in Python that allows you to set up context for a block of code, and then automatically clean up or release resources when the block is exited. It is most commonly used with the `with` statement. |
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Visit the following resources to learn more: |
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- [@article@Context managers in Python](https://www.freecodecamp.org/news/context-managers-in-python/) |
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- [@article@Context managers](https://book.pythontips.com/en/latest/context_managers.html) |
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- [@official@Context Libraries](https://docs.python.org/3/library/contextlib.html) |
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- [@article@Context Managers in Python](https://www.freecodecamp.org/news/context-managers-in-python/) |
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- [@article@Context Managers](https://book.pythontips.com/en/latest/context_managers.html) |
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# Decorators |
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decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate. |
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Decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate. |
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Visit the following resources to learn more: |
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- [@article@Learn Decorators in Python](https://pythonbasics.org/decorators/) |
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- [@article@Python Decorators](https://www.datacamp.com/tutorial/decorators-python) |
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- [@video@Decorators in Python](https://www.youtube.com/watch?v=FXUUSfJO_J4) |
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- [@video@Python Decorators in 1 Minute](https://www.youtube.com/watch?v=BE-L7xu8pO4) |
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# Python Frameworks |
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Frameworks automate the common implementation of common solutions which gives the flexibility to the users to focus on the application logic instead of the basic routine processes. |
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Frameworks automate the common implementation of common solutions which gives the flexibility to the users to focus on the application logic instead of the basic routine processes. Frameworks make the life of web developers easier by giving them a structure for app development. They provide common patterns in a web application that are fast, reliable and easily maintainable. |
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Frameworks make the life of web developers easier by giving them a structure for app development. They provide common patterns in a web application that are fast, reliable and easily maintainable. |
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Visit the following resources to learn more: |
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- [@article@Pyscript: A Browser-Based Python Framework for the 99%](https://thenewstack.io/pyscript-a-browser-based-python-framework/) |
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- [@article@Pyscript: A Browser-Based Python Framework](https://thenewstack.io/pyscript-a-browser-based-python-framework/) |
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- [@feed@Explore top posts about Python](https://app.daily.dev/tags/python?ref=roadmapsh) |
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# Plotly Dash |
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Plotly Dash is a Python framework that allows you to build analytical web applications. It's a high-level library that enables you to create interactive, web-based data visualization dashboards without requiring extensive knowledge of web development. |
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Visit the following resources to learn more: |
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- [@official@Plotly Dash Documentation](https://dash.plotly.com/) |
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- [@official@20 Minutes Tutorial](http://dash.plotly.com/tutorial) |
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# pyproject.toml |
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This file is used to define the project configuration and dependencies. It is a configuration file that |
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contains metadata about the project, such as its name, version, dependencies, and build settings. The |
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`pyproject.toml` file is used by tools like `poetry` and `flit` to manage Python projects and their |
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dependencies. |
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This file is used to define the project configuration and dependencies. It is a configuration file that contains metadata about the project, such as its name, version, dependencies, and build settings. The `pyproject.toml` file is used by tools like `poetry` and `flit` to manage Python projects and their dependencies. |
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Learn more about `pyproject.toml` by visiting the following resources: |
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Learn more from the following resources: |
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- [@official@Writing pyproject.toml files](https://packaging.python.org/en/latest/guides/writing-pyproject-toml/) |
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# Testing |
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Testing in programming means checking if your code works as expected. It's a systematic way to find and fix errors (bugs) before your code goes live. Imagine building a beautiful house without checking if the walls are straight or the roof doesn't leak—that's what coding without testing can feel like! |
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Visit the following resources to learn more: |
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- [@official@Unit Testing in Python](https://docs.python.org/3/library/unittest.html) |
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- [@article@Python Testing Tutorial](https://realpython.com/python-testing/) |
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# tox - python testing |
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# Tox |
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tox is a tool for automating test environment management and testing against multiple interpreter configurations. It is particularly useful for Python codebases that need to support multiple versions of Python. |
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Tox is a tool for automating test environment management and testing against multiple interpreter configurations. It is particularly useful for Python codebase that need to support multiple versions of Python. |
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Learn more about tox from the following resources: |
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- [@official@tox documentation](https://tox.wiki/en/) |
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- [@official@Tox Documentation](https://tox.wiki/en/) |
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# typing |
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# Typing |
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typing is a module in Python that provides runtime support for type hints. The typing module defines a standard set of names that can be used to describe types in the Python language. The typing module was added to the standard library in Python 3.5. |
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Typing is a module in Python that provides runtime support for type hints. The typing module defines a standard set of names that can be used to describe types in the Python language. The typing module was added to the standard library in Python 3.5. |
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- [@official@typing python](https://docs.python.org/3/library/typing.html) |
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- [@official@Typing Module](https://docs.python.org/3/library/typing.html) |
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