200,000 Python Packages: 10 Powerful Gems You Can't Miss in 2024
If You Don’t Know These 10 Python Packages, Don’t Say You Know Python!
There are more than 200,000 Python packages. This is based on the official Python Package Index, PyPI. With so many choices, it can be hard to know where to start. Which packages should all Python programmers learn first?
To help answer this, here is a list of the ten most important, useful, and widely used Python packages. These packages often come up when working on various projects.
This list focuses on Python packages that cover multiple programming scenarios and goals. It does not solely focus on specific domains like data science or web development.
1. Numpy
You can do basic math in Python without any special packages. However, NumPy makes coding much easier for complex math tasks.
NumPy provides tools to help build multi-dimensional arrays. It can do calculations on the data stored in them. You can solve algebraic formulas and perform common statistical operations.
>>> import numpy as np
>>> a = np.arange(15).reshape(3, 5)
>>> a
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14]])
>>> a.shape
(3, 5)
>>> a.ndim
2
>>> a.dtype.name
'int64'
>>> a.itemsize
8
>>> a.size
15
>>> type(a)
<class 'numpy.ndarray'>
>>> b = np.array([6, 7, 8])
>>> b
array([6, 7, 8])
>>> type(b)
<class 'numpy.ndarray'>NumPy is valuable for various general programming tasks. It is especially important if you want to do machine learning. NumPy provides part of the foundation for libraries like TensorFlow.