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Nov 4th

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- [Python pip and pip's wheel](#python-pip-and-pips-wheel)
- [Python Feature Flags](#python-feature-flags)
- [Python testing](#python-testing)
- [Python Cyber Security](#python-cyber-security)
- [Data Science](#data-science)
- [Python Pandas and pivot tables](#python-pandas-and-pivot-tables)
- [PandasDatabase](#pandasdatabase)
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- [blog.teclado.com: Python Methods: Instance, Static and Class](https://blog.teclado.com/python-methods-instance-static-class/)
- [treyhunner.com: How to flatten a list in Python](https://treyhunner.com/2021/11/how-to-flatten-a-list-in-python/)
- [makeuseof.com: 7 Vital Commands to Get Started With Python for Beginners](https://www.makeuseof.com/python-for-beginners/)
- [pythonsimplified.com: Python secrets module for strong random number and token generation](https://pythonsimplified.com/python-secrets-module-for-strong-random-number-and-token-generation/) Do you know Python has a built-in module called secrets that can be used to generate cryptographically strong passwords, tokens, and other related secrets? The secrets module was first introduced in Python 3.6
- [freecodecamp.org: Python Sets – Explained with Examples](https://www.freecodecamp.org/news/python-set-operations-explained-with-examples/)
## APIs in Python
- [towardsdatascience.com: Quick-Fire Guide to APIs in Python](https://towardsdatascience.com/quick-fire-guide-to-apis-in-python-891dd98c8877) A straightforward guide to web communication
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- [gabbi - Declarative HTTP testing library pypi](http://pypi.python.org/pypi/gabbi/)
- [tracker: A time machine for debugging pesky stateful errors](https://github.com/madisonmay/tracker)
## Python Cyber Security
- [coursereport.com: A Beginner’s Guide to Python for Cybersecurity](https://www.coursereport.com/blog/python-for-cyber-security-with-flatiron-school)
## Data Science
- [towardsdatascience.com: Unlimited scientific libraries and applications in Kubernetes, instantly!](https://towardsdatascience.com/unlimited-scientific-libraries-and-applications-in-kubernetes-instantly-b69b192ec5e5) Set up a shared library of packages and applications that you can dynamically load into your Kubernetes Data Science environments.