kansan 0.5

A Docker and AWS utility package

Install python3

apt install python3

Install Virtual Environment

$ apt-get install python3-pip

$ apt-get update

$ apt install python3.8-venv

$ python3 -m pip install --user virtualenv

$ python3 -m venv env

$source env/bin/activate

Install the required packages:

1. Setuptools: Setuptools is a package development process library designed for creating and distributing Python packages.

2. Wheel: The Wheel package provides a bdist_wheel command for setuptools. It creates .whl file which is directly installable through the pip install command. We'll then upload the same file to pypi.org.

3. Twine: The Twine package provides a secure, authenticated, and verified connection between your system and PyPi over HTTPS.

4. Tqdm: This is a smart progress meter used internally by Twine.

python3 -m pip install --upgrade pip setuptools wheel python3 -m pip install tqdm python3 -m pip install --upgrade twine

Build your package: python3 setup.py bdist_wheel

Test Installing on to local machine from whl file: python3 -m pip install dist/kansan-0.1-py3-none-any.whl

or

pip3 install dist/kansan-0.1-py3-none-any.whl

Create file ~/.pypirc

[distutils] index-servers=pypi [pypi] repository = https://upload.pypi.org/legacy/ username = kansalster

Upload on pip: python3 -m twine upload dist/* --skip-existing

You can change the package version in setup.py and upload the new version to pypi.org

Login in to pypi and check the package there. https://pypi.org/

pip3 install tree pip3 install kansan

Now login in to azure devops and create feed with no upstream option. Click on the connect to feed and get the file pip.conf content and save it on your machine in /etc/pip.conf e.g. [global] index-url=https://:@pkgs.dev.azure.com/kansalster/lastproject/_packaging//pypi/simple/

Now try installing any pip library

pip3 install tree pip3 install kansan

Now we will push our package new version on to azure feed.

1. Change the version number
2. Push it to azure feed this time using command

python -m twine upload -r feedName --config-file dist/*.whl

1. this should fail until upstream option is disabled.
2. Once you enabled upstream option, you should be able to install any library
3. The package will be saved to feed first and then installed on your machine so that next request does not go to upstream
4. you can also set the retention of the packages saved in to feed.

Now lets write the azure pipeline to build the package and push it to pypi and make it available to use for consumers.