Do you need something like range() but with float numbers? Try numpy.arange()

>>> range(0, 5, 0.5) #Error!

>>> np.arange(0, 5, 0.5)
array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5])


If you need exactly X steps, but one step is not a short decimal number, you can use:

>>> np.linspace(0, 1, 4)
array([0., 0.3333333, 0.6666667, 1.])

# In Python 3.4+ you can use
# contextlib.suppress() to selectively
# ignore specific exceptions:

import contextlib

with contextlib.suppress(FileNotFoundError):
os.remove('somefile.tmp')

# This is equivalent to:

try:
os.remove('somefile.tmp')
except FileNotFoundError:
pass

# contextlib.suppress docstring:
#
# "Return a context manager that suppresses any
# of the specified exceptions if they occur in the body
# of a with statement and then resumes execution with
# the first statement following the end of
# the with statement."

What is the difference between __str__ and __repr__ in #Python?

In short, the goal of __repr__ is to be unambiguous and __str__ is to be readable.

==> "__repr__ is for developers, __str__ is for customers."

🐍📰 Introduction to Git and GitHub for Python Developers

What is Git, what is GitHub, and what's the difference? Learn the basics of Git and GitHub from the perspective of a Pythonista in this tutorial
#python

https://realpython.com/python-git-github-intro/

🐍📺 Reading and Writing CSV Files [Video]

This short course covers how to read and write data to CSV files using Python's built in "csv" module and the "pandas" library
#python

notifiers: The easy way to send notifications #python

We love #Python namedtuples, a tuple subclass with named fields:

The @dataclass decorator helps reduce boilerplate code when writing your #Python classes: