Examples

Environment Setup

Some of the examples on this page rely on files from the test/ directory of the srepkg repo. Files from test/ are not included when installing PyPI, so we will create a fresh Conda environment and install srepkg there using a cloned GitHub repo as the source.

conda create -n srepkg_tests=3.10
conda activate srepkg_tests
git clone https://github.com/duanegoodner/srepkg
cd srepkg
pip install .

**Example #1: Using srepkg to Avoid a Dependency Conflict**

For this example, we will use two local packages located under ./test/demos/ of the srepkg repo: oldmath at ./test/demos/oldmath and newmath at ./test/demos/newmath.

Here is the content of the pyproject.toml for oldmath:

# ./test/demos/oldmath/pyproject.toml

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "oldmath"
version = "0.1.0"

dependencies = ["numpy<=1.26.4"]

[tool.setuptools]
package-dir = {"" = "src"}

[tool.setuptools.packages.find]
where = ["src"]

[project.scripts]
oldmath = "oldmath.app:run"

And here is the pyproject.toml for newmath:

# ./test/demos/newmath/pyproject.toml

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "newmath"
version = "0.1.0"

dependencies = ["numpy>=2.0.0"]

[tool.setuptools]
package-dir = {"" = "src"}

[tool.setuptools.packages.find]
where = ["src"]

oldmath has a command-line entry point named oldmath. newmath contains module newmath.array_addition. Since oldmath depends on numpy<=1.26.4, and newmath depends on numpy>=2.0.0, installing both packages in the same environment will result in a dependency conflict.

We can avoid this conflict and still have access to the oldmath command and the newmath.array_addition module in the same Python environment if use srepkg to re-package oldmath, and install this re-packaged distribution and a newmath in the same environment.

Repackage the Package that has a Command Line Entry Point

First, use srepkg to re-package oldmath by running:

srepkg test/demos/oldmath/

The output should look like this:

✅ Building original package wheel from source code
✅ Creating virtual env
    Virtual env created with the following pypa packages installed:
    • pip==25.0.1
    • setuptools==75.8.0
    • wheel==0.45.1
✅ Installing oldmath-0.1.0-py3-none-any.whl in virtual env
✅ Building srepkg wheel
    oldmathsrepkg wheel saved as: /home/duane/dproj/srepkg/srepkg_dists/oldmathsrepkg-0.1.0-py3-none-any.whl
✅ Building srepkg sdist
    oldmathsrepkg sdist saved as: /home/duane/dproj/srepkg/srepkg_dists/oldmathsrepkg-0.1.0.tar.gz

oldmathsrepkg can be installed using either of the following commands:
    • pip install /home/duane/dproj/srepkg/srepkg_dists/oldmathsrepkg-0.1.0-py3-none-any.whl
    • pip install /home/duane/dproj/srepkg/srepkg_dists/oldmathsrepkg-0.1.0.tar.gz
Upon installation, oldmathsrepkg will provide access to the following command line entry points: 
    • oldmath

The repackaged version of oldmath is called oldmathsrepkg, and it has been built into both wheel and sdist distributions located under ./srepkg_distributions.

**Install newmath and Re-packaged Version of oldmath in same Environment**

Next, install oldmathsrepkg from the newly created wheel:

pip install ./srepkg_dists/oldmathsrepkg-0.1.0-py3-none-any.whl

Then, install the regular newmath package:

pip install ./test/demos/newmath/

Check Version of Potentially-Conflicting Dependency

We can check the version of numpy that has been installed (as a dependency of newmath) by running:

conda list | grep numpy

The output should be similar to:

numpy                     2.2.3                    pypi_0    pypi

numpy 2.2.3 satisfies the newmath requirement numpy>=2.0.0 but does not satisfy the oldmath requirement numpy<=1.26.4.

Use the Command-Line Interface Exposed by Re-packaged Distribution

With oldmathsrepkg installed, we can use the oldmath command-line interface.

First, run:

oldmath --help

The output with the above --help option is:

usage: oldmath [-h] factor

Multiplies the numpy array [1 2 3] by a user-provided integer.
Displays the resulting array as well as the version of numpy used.

positional arguments:
  factor      An integer that numpy array [1 2 3] will be multiplied by

options:
  -h, --help  show this help message and exit

Then use the oldmath command to do some math. Running

oldmath 2025

gives:

2025 * [1 2 3] = [2025 4050 6075]
numpy version used by this program = 1.26.4

Confirm Absence of Dependency Conflicts

Finally, confirm that we do not have any dependency conflicts:

$ pip check

No broken requirements found.

The key thing to note is that we can access the command-line interface of oldmath with its numpy<=1.26.4 requirement and have newmath installed with its numpy>=2.0.0 requirement in the same environment without any dependency conflict .

Sharing oldmath with colleagues and/or the general Python community would run a high risk of breaking a Python environment due to the outdated numpy requirement. However, we can share oldmathsrepkg, knowing that it will not cause problems a user's Python environment — even if they are using a current version of numpy and do not know much / anything about Python dependencies and environments.

Example #2: Re-package a Distribution Obtained from PyPI

We can re-package the latest version of scrape available on the PyPI using:

srepkg scrape

The output should look similar to:

✅ Retrieving scrape from Python Packaging Index
    Downloaded files:
    • scrape-0.11.3-py3-none-any.whl
✅ Creating virtual env
    Virtual env created with the following pypa packages installed:
    • pip==25.0.1
    • setuptools==75.8.0
    • wheel==0.45.1
✅ Installing scrape-0.11.3-py3-none-any.whl in virtual env
✅ Building srepkg wheel
    scrapesrepkg wheel saved as: /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3-py3-none-any.whl
✅ Building srepkg sdist
    scrapesrepkg sdist saved as: /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3.tar.gz

scrapesrepkg can be installed using either of the following commands:
    • pip install /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3-py3-none-any.whl
    • pip install /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3.tar.gz
Upon installation, scrapesrepkg will provide access to the following command line entry points: 
    • scrape

We can then install scrapesrepkg:

pip install pip install srepkg_dists/scrapesrepkg-0.11.3-cp310-abi3-linux_x86_64.whl

Output:

Processing ./srepkg_dists/scrapesrepkg-0.11.3-py3-none-any.whl
Installing collected packages: scrapesrepkg
Successfully installed scrapesrepkg-0.11.3

Then we can use the scrape command on http://example.com/

scrape http://example.com/ -pt

Output:

Failed to enable cache: No module named 'requests_cache'
Example Domain
Example Domain
This domain is for use in illustrative examples in documents. You may use this domain in literature without prior coordination or asking for permission.
More information...

If we wanted to re-package a specific version (e.g.0.11.0) from PyPI we could do this:

srepkg scrape -r 0.11.0

Example #3: Re-package a Distribution Obtained from GitHub

We can also re-package using a GitHub repo as the original source:

srepkg https://github.com/huntrar/scrape

Output:

✅ Cloning https://github.com/huntrar/scrape into temporary directory
✅ Building original package wheel from source code
✅ Creating virtual env
    Virtual env created with the following pypa packages installed:
    • pip==25.0.1
    • setuptools==75.8.0
    • wheel==0.45.1
✅ Installing scrape-0.11.3-py3-none-any.whl in virtual env
✅ Building srepkg wheel
    scrapesrepkg wheel saved as: /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3-py3-none-any.whl
✅ Building srepkg sdist
    scrapesrepkg sdist saved as: /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3.tar.gz

scrapesrepkg can be installed using either of the following commands:
    • pip install /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3-py3-none-any.whl
    • pip install /home/duane/dproj/srepkg/srepkg_dists/scrapesrepkg-0.11.3.tar.gz
Upon installation, scrapesrepkg will provide access to the following command line entry points: 
    • scrape

If we want to re-package a specific commit from the scrape GitHub repo, we can run:

srepkg https://github.com/huntrar/scrape -g 1dfd98bb0a308ef2a45b1e5dd136c38b17c27bc7

If we want to re-package a specific release or tag, we would run:

srepkg https://github.com/huntrar/scrape -g 0.11.2

Examples

Environment Setup

Example #1: Using srepkg to Avoid a Dependency Conflict

Repackage the Package that has a Command Line Entry Point

Install newmath and Re-packaged Version of oldmath in same Environment

Check Version of Potentially-Conflicting Dependency

Use the Command-Line Interface Exposed by Re-packaged Distribution

Confirm Absence of Dependency Conflicts

Share the Re-packaged Distribution with Confidence

Example #2: Re-package a Distribution Obtained from PyPI

Example #3: Re-package a Distribution Obtained from GitHub

**Example #1: Using srepkg to Avoid a Dependency Conflict**

**Install newmath and Re-packaged Version of oldmath in same Environment**