How do I pack a python program?

How do I pack a python program?

How to Create Packages of Your Application’s New Versions

1. Edit the setup.py file with a text editor (e.g. nano) and set the new version number: version=”0.1.1″
2. Edit the CHANGES.txt to reflect the changes.
3. Make the necessary adjustments to the LICENSE.txt and README.txt.
4. Upload your code following the previous step.

Which package is best for python?

With that said, here are the Top 10 Python Libraries for Data Science.

1. Pandas. You’ve heard the saying.
2. NumPy. NumPy is mainly used for its support for N-dimensional arrays.
3. Scikit-learn. Scikit-learn is arguably the most important library in Python for machine learning.
4. Gradio.
5. TensorFlow.
6. Keras.
7. SciPy.
8. Statsmodels.

How do you package and deploy python code?

To deploy, you need to upload this artifact to your production machine. To install it, just run dpkg -i my-package. deb . Your virtualenv will be placed at /usr/share/python/ and any script files defined in your setup.py will be available in the accompanying bin directory.

What are the best tools for creating packaged executables for python?

Bringing your own Python executable

• pyInstaller – Cross-platform.
• cx_Freeze – Cross-platform.
• constructor – For command-line installers.
• py2exe – Windows only.
• py2app – Mac only.
• bbFreeze – Windows, Linux, Python 2 only.
• osnap – Windows and Mac.
• pynsist – Windows only.

What are the different Python packages?

Top 10 Python Packages Every Developer Should Learn

• #1 NumPy. You can do basic mathematical operations without any special Python packages.
• #2 Pendulum.
• #3 Python Imaging Library.
• #4 MoviePy.
• #5 Requests.
• #6 Tkinter.
• #7 PyQt.
• #8 Pandas.