Python packages list github
Python packages list github
I'd be happy to help!
Here's a comprehensive list of popular Python packages on GitHub:
Requests: A lightweight HTTP library for making requests, which provides a simple and intuitive way to work with RESTful APIs.Repository: https://github.com/psf/requests
Flask: A micro web framework that helps build small-scale web applications quickly and efficiently.Repository: https://github.com/pallets/flask
Repository: https://github.com/django/django
Repository: https://github.com/scikit-learn/scikit-learn
Pandas: A library that provides data structures and functions to efficiently handle structured data, such as CSVs, Excel spreadsheets, and SQL databases.
Repository: https://github.com/pandas-dev/pandas
NumPy: A library for numerical computing that provides support for large, multi-dimensional arrays and matrices, along with various high-level mathematical functions.Repository: https://github.com/numpy/numpy
OpenCV: A computer vision library that provides algorithms and data structures for image processing, feature detection, object recognition, and more.Repository: https://github.com/opencv/opencv
Matplotlib: A plotting library that enables creating high-quality 2D and 3D plots, charts, and graphs.Repository: https://github.com/matplotlib/matplotlib
Seaborn: A visualization library based on Matplotlib that provides a variety of tools for statistical graphics, including heatmaps, scatterplots, and box plots.Repository: https://github.com/mwaskom/seaborn
TensorFlow: An open-source machine learning framework developed by Google that enables building and training neural networks.Repository: https://github.com/tensorflow/tensorflow
Keras: A high-level, Python-based neural networks API that can run on top of TensorFlow, CNTK, or Theano.Repository: https://github.com/keras-rcall/keras
Scipy: A scientific computing library that provides various algorithms and tools for scientific and engineering applications, including signal processing, optimization, and statistics.Repository: https://github.com/scipy/scipy
Statsmodels: A statistical modeling library that provides classes and functions for statistical analysis of data, including linear regression, time series analysis, and hypothesis testing.Repository: https://github.com/statsmodels/statsmodels
Plotly: An interactive visualization library that allows creating web-based visualizations using Python, R, or MATLAB.Repository: https://github.com/plotly/plotly.py
Bokeh: A Python data visualization library that provides elegant, concise construction of versatile graphics, as well as a wide variety of tools for working with large datasets.Repository: https://github.com/bokeh/bokeh
Beautiful Soup: A Python library used for parsing and scraping HTML and XML documents.Repository: https://github.com/python-parsing/beautifulsoup
Selenium: An open-source tool that allows automating web browsers, enabling functional testing of web applications.Repository: https://github.com/SeleniumHQ/selenium
Pillow: A Python Imaging Library (PIL) for opening, manipulating, and saving various image file formats, such as JPEGs, PNGs, GIFs, and more.Repository: https://github.com/python-pillow/Pillow
NLTK: A natural language processing library that provides tools and resources for working with text data, including tokenization, stemming, tagging, parsing, and semantic reasoning.Repository: https://github.com/nltk/nltk
spaCy: A modern natural language processing library designed to help you work quickly and efficiently with text data, including tokenization, entity recognition, language modeling, and more.Repository: https://github.com/explosion/spaCy
python list installed packages
I'd be happy to help!
In Python, you can use the pip package manager to manage your packages and list them using various commands. Here are some ways to do so:
pip list
This will show you a list of all packages that are currently installed on your Python environment.
List specific package details: To see detailed information about a specific package, including its version and dependencies, use the following command:pip show
Replace <package_name> with the actual name of the package you want to see more details about (e.g., numpy, matplotlib, etc.).
pip list --versions
pip list --outdated
This will show you a list of packages that need updating.
List packages by category: You can also group your packages by category (e.g., development tools, scientific libraries) using the--category option along with the list command. For example:
pip list --category "development"
This will show you a list of development-related packages installed on your system.
List packages for a specific directory: To see which packages are installed in a particular directory (e.g., project-specific packages), use the following command:pip freeze > requirements.txt
Replace requirements.txt with the actual file name you want to write the package list to.
pip list --recursive
Please note that you might need to install additional packages (e.g., setuptools) to fully utilize some of these commands.
These are just a few ways to list the Python packages installed on your system. Depending on your specific use case or needs, there may be other approaches as well!
