list of some popular and commonly used Python libraries across different domains:

Data Manipulation and Analysis:

NumPy: Numerical computing library for arrays and matrices.

pandas: Data manipulation and analysis library with powerful data structures.

matplotlib: Plotting library for creating static, interactive, and animated visualizations.

seaborn: Data visualization library built on top of matplotlib.

SciPy: Library for mathematics, science, and engineering tasks.

Machine Learning and Data Science:

scikit-learn: Machine learning library for classification, regression, clustering, etc.

TensorFlow: Open-source machine learning framework developed by Google.

PyTorch: Deep learning framework for research and production.

Keras: High-level neural networks API built on top of TensorFlow, Theano, or CNTK.

XGBoost: Gradient boosting library for improved model performance.

LightGBM: Gradient boosting framework that focuses on speed and efficiency.

Web Development:

Flask: Micro web framework for building web applications.

Django: High-level web framework for rapid development.

FastAPI: Modern web framework for building APIs with automatic documentation.

Natural Language Processing (NLP):

NLTK: Natural Language Toolkit for text processing and analysis.

spaCy: NLP library for advanced text processing and analysis.

TextBlob: Simple NLP library based on NLTK and Pattern.

Data Visualization:

Plotly: Interactive graphing library for creating interactive, web-based visualizations.

Bokeh: Interactive visualization library that targets modern web browsers.

Altair: Declarative statistical visualization library based on Vega and Vega-Lite.

Database Interaction:

SQLAlchemy: SQL toolkit and Object-Relational Mapping (ORM) library.

psycopg2: PostgreSQL adapter for Python.

PyMySQL: MySQL client library for Python.

Utilities:

requests: HTTP library for making requests and handling responses.

beautifulsoup4: HTML and XML parsing library.

virtualenv: Tool for creating isolated Python environments.

pytest: Testing framework for writing simple and scalable test cases.

logging: Built-in library for flexible and configurable logging.