This is the webpage for CMSE495 Data Science Capstone Course (Spring 2022)
In this assignment you will clean finish up our project structure to make it as easy as possible for others to use. We have been doing pieces of this all semester but here we will add a few finishing touches to make the project complete. Specifically we need to put in enough structure such that anyone taking the course can get it up and running. This includes:
If you remember from the first project, the structure of the repository should be something like the following:
ProjectName/
.gitignore
docs/
package_name/
module1.html
module2.html
images/
image1.jpg
environments.yml
Examples/
datafile1.csv
datafile2.tiff
datafile3.xls.
Figures/
Generate_Figure1.ipynb
Generate_Figure2.ipynb
Generate_Figure3.ipynb
LICENSE.txt
makefile
Reports/
Meeting_Minutes.md
Team_Charter.md
Project_proposal.ipynb
Closed_loop_Report.ipynb
package_name/
__init__.py
module1.py
module2.py
test/
__init__.py
test_module1.py
test_module2.py
README.md
setup.py
Final_Report.ipynb
Your project needs to include clear installation instructions with all requirements. These instructions can be included in your README.md file in the top directory.
I highly recommend you include instructions for creating a conda environment so that classmates are easily able to run your code. This means they need to temporarily set up their computer with the same settings as your system.
Ideally you want include a environment.yml
with your project so that other students and instructors can use the following commands to set up the environment:
conda env create --prefix ./envs --file environment.yml
conda activate ./envs
The environment.yml
file can be created to “copy” your current enviornment by running the following command:
conda env export --from-history > environment.yml
Note, try to make your environment.yml
file the minimum packages you will need to run your project. Do not create an environment.yml
file on your base anaconda environment as this will just install a lot of stuff that is not needed. A good way to figure out your base install is to create a new environment and add packages until your code works. For example:
conda create --prefix ./envs pip jupyter pytest pylint pdoc3
conda activate ./envs
Now just use “conda install” and “pip install” to add all of your project dependencies until it starts working. For example may of you will want to include one or all of the following:
conda install numpy
conda install matplotlib
conda install scipy
conda install jupyter
When you have it working run the conda env export --from-history
command from above. To deactivate and delete your environment just run:
conda deactivate
rm -rf ./envs
That should be it!!!
NOTE FOR INTERNATIONAL STUDENTS with English as a second language. If you are running on Windows and your computer’s default language is not English you may have trouble with UTF8 errors and the
environment.yml
file. The following line may fix the problem.
conda env export --from-history | Set-Content -Encoding utf8 environment.yml
Finally, include example code (jupyter notebooks or similar interface prefered) in an obvious location. Have the example(s) describe and show how to use the software and show some results.
The example should work “out-of-the-box” with no special commands once your conda environment has been installed.
Now, you just need to commit and push the project changes to your project git repository.
Written by Dr. Dirk Colbry, Michigan State University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.