Python is a major language used by data scientists for data science projects because there are thousands of open source libraries that can simplify and perform data scientist tasks. More than 235,000 Python packages can be imported through PyPl.
Multiple libraries and frameworks need to import every ˚F ORM tasks in data science case studies. Whenever a data scientist or analyst starts a new jupyter notebook or any other IDE, they need to import all the libraries according to their requirements. Sometimes it can be frustrating to write multiple lines of the same import statement over and over. The pyforest library here can help you, and it will do the work for you.
Pyforest Library:
Pyforest is an open source Python library that enables data scientists to feel the happiness of automatic import. When conducting data science case studies, you need to import multiple packages or libraries, such as pandas, matplotlib, seaborn, NumPy, SkLearn, etc. Importing all these libraries every time can be boring and disrupt the natural flow of work. Also, you don't need to search for the exact import statement, for example from sklearn.ensemble import RandomForestClassifier.
Using pyforest can overcome these problems. Pyforest enables you to use all your favorite libraries without importing. Pyforest does the work for you by automatically importing libraries to be used for case studies.
After importing the pyforest library in one line, now you can use all python libraries as usual. Any libraries you use will not be imported, Pyforest will automatically import them for you. Import the library only after calling the library or creating the library object. If the library is not used or called, pyforest will not import the library.
installation:
You can install Pyforest from Pypl using the following command:
<span style="color:#292929"><strong>pip安装pyforest</strong></span>After installing the library, you only need to import it into one line of code. Now you can use your favorite library as usual without writing an import. In the example jupyter notebook below, we have not imported the pandas, seaborn and matplotlib libraries, we can still use them by importing the pyforest library.
Can pyforest import all libraries?
This package aims to add all the libraries that account for more than 99% of the imports, including popular libraries such as pandas as pd, NumPy as np, matplotlob.pyplot as plt, seaborn as sns, and many more. In addition to these libraries, it also some helper modules such as os, tqdm, re, and many more.
If you want to view the library list, please use dir (py forest).
To add the OUN IMPOOR statement to the first type of pyorest itraies in Exlicit Impor Trtemen, please add it to the file in the middle directory ~1/.pyForest/user_inports.py.
Functions of pyforest:
The goal of this package is to provide more than 19% of imprs cufng opla ltaies as pute 2e al nlr as n, atol io prlt ia l, veaoms srme and other auxiliary modules in these libraries, such as os, tqdm, re, etc.
- active_imports() : Returns a list of libraries that have been imported and are in use.
- lazy_imports() : Returns a list of all libraries to be imported into the pyforest library.
in conclusion:
In this article, we discussed the pyforest library, which is an automatic import library. Using this library can reduce the pressure of importing a large number of necessary libraries, on the contrary, it will automatically import requirements. For data scientists who often work with new Jupyter notebooks to explore their data science case studies, the library may be helpful, and now they can avoid the hassle of importing the library, thus speeding up the workflow.
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