A python project to create python package which calculates Gaussian and Binomial distributions. This is the first project on how to create package and upload on PyPi (implementation of that is given below under the heading How to create and upload a package to PyPi).
Link to the PyPi package link: pypi.org/project/statistical-distribution/1.0/
To use the statistical_distribution package, pip install the package directly (Check Installing section inside the statistical_distribution directory).
In order to work with the source code: Download or clone the repository in the local system, install the prerequisites and run testing code.
Twine is needed for uploading the code to PyPi if one wants to try doing it.
$ pip install twine
For those using conda, install using conda command.
$ conda install twine
Create and run a new virtual environment to avoid interfering with the base python library's installation on your system. Using conda, this can be done easily:
$ conda create -n yourenvname
$ conda activate yourenvname
To install the impllemented library from PyPi, pip install the package.
$ pip install statistical-distribution
To build the library from source code, go to the project directory path, which contains the setup.py file, in terminal and run the following commands.
$ pip install .
This installs the statistical-distribution package on your system in your virtual environment. To quick check if the installation is working properly, run the following commands in a python interpreter.
>>> from distributions import Gaussian
>>> gaussian_one = Gaussian(25, 2)
>>> gaussian_one.mean
You should get the following output without any errors if the package is installed correctly.
>>> 25
To check if the code of Binomial distribution and Gaussian distribution is running correctly and giving correct results, run the following test commands which runs the test.py file :
$ python -m unittest test
test.py file passes multiple values in the objects created from Binomial and Gaussian classes and checks if the numerical values returned are correct according to the mathematical formulae.
If the test ran successfully without error, you should see an 'OK' as output
If changes to the base code are made, make sure to reinstall the package locally before running the unit test again. To bring the code changes to effect, run the following code:
$ pip install --upgrade .
Note that if you change the code in the project folder after pip installing the package, Python will not know about the changes. You'll need to run above mentioned command everytime you make changes to the package files.
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This section explains how you can create and upload your own package on PyPi so that anyone can pip install the package.
Twine is needed for uploading the code to PyPi if one wants to try doing it.
$ pip install twine
For those using conda, install using conda command.
$ conda install twine
In the directory where a setup.py file is created, run the following command:
$ python setup.py sdist bdist_wheel
This will output a folder called 'dist' having a tar.gz file and a .whl file. The tar.gz file is called a source archive whereas the .whl file is a built distribution.
We can even use just python setup.py sdist which will get only tar.gz file in 'dist' folder.
When we pip install a package, pip will first look for a whl file (wheel file) and if there isn't one, will then look for the tar.gz file.
A tar.gz file, i.e. an sdist, contains the files needed to compile and install a Python package. A whl file, i.e. a built distribution, only needs to be copied to the proper place for installation. Behind the scenes, pip installing a whl file has fewer steps than a tar.gz file.
To upload your package to PyPi, you first need to create an account on their site. After that, run the following commands and enter your username and password to upload the package successfully.
$ twine upload dist/*
$ pip install statistical_distribution
Remember to use a unique name for your package as it cannot be similar to any other package on PyPi site.
Check the Installing section under the heading PyPi-Package-Deployment-Project.
This project is licensed under the MIT License - see the license.txt file for details