Capstone Assignment

Capston Part 0: Preparation

to run scripts and application you will need:

• setup virtual environment for python (for example using conda) % conda create -n test2 python=3.7 anaconda

• activate virtual environment % conda activate test2

• clone repository with python scripts, flask application, DockerFiles and reports with outcomes % git clone https://github.ibm.com/Tomasz-Rozmus/CapstonAssasment

• change working directory % cd to_dir_with_assigment

• install required python library $ pip install -r requirements.txt

Capstone project checklist

Are there unit tests for the API?

• to test api (run api server before ) $ python -m unittest tests/api_tests.py

Are there unit tests for the model?

• to test models: $ python -m unittest tests/Model_tests.py

Are there unit tests for the logging?

• to test logging capabilites run: $ python -m unittest tests/Logger_tests.py

Can all of the unit tests be run with a single script and do all of the unit tests pass?

• or run all tests $ python run_all_test.py

Is there a mechanism to monitor performance?

$ python part-2.py

Was there an attempt to isolate the read/write unit tests from production models and logs?

Does the API work as expected? For example, can you get predictions for a specific country as well as for all countries combined?

• start api by running: $ python app.py

• open following url in browser:

http://localhost:8080/predict?country=united_kingdom&date=2019-05-05

http://localhost:8080/predict?country=all&date=2019-05-05

Does the data ingestion exists as a function or script to facilitate automation?

helper/fetchlib.py helper/modeltools.py

Were multiple models compared?

time-series-notebooks

Did the EDA investigation use visualizations?

Capstone Part1.ipynb

Is everything containerized within a working Docker image?

Dockerfile

Did they use a visualization to compare their model to the baseline model?

time-series-notebooks

Build the Docker image and run it

• build docker image $ docker build -t apiapp .

• Check that the image is there.

$ docker image ls

• run docker $ docker run -d -p 8080:8080 apiapp

• check API open below url in a browser:

http://localhost:8080/predict?country=united_kingdom&date=2019-05-05