NCHS Mortality Data

We import the NCHS motality data from CDC website and export the state-level data as-is. For detailed information see the files DETAILS.md contained in this directory.

Create a MyAppToken

MyAppToken is required when fetching data from SODA Consumer API (https://dev.socrata.com/foundry/data.cdc.gov/r8kw-7aab). Follow the steps below to create a MyAppToken.

• Click the Sign up for an app toekn buttom in the linked website
• Sign In or Sign Up with Socrata ID
• Clck the Create New App Token button
• Fill in Application Name and Description (You can just use NCHS_Mortality for both) and click Save
• Copy the App Token

Running the Indicator

The indicator is run by directly executing the Python module contained in this directory. The safest way to do this is to create a virtual environment, installed the common DELPHI tools, and then install the module and its dependencies. To do this, run the following code from this directory:

make install

This command will install the package in editable mode, so you can make changes that will automatically propagate to the installed package.

All of the user-changable parameters are stored in params.json. (NOTE: In production we specify "export_start_date": "latest",). To execute the module and produce the output datasets (by default, in receiving), run the following. Fill in the token that you created.

env/bin/python -m delphi_nchs_mortality

If you want to enter the virtual environment in your shell, you can run source env/bin/activate. Run deactivate to leave the virtual environment.

Once you are finished, you can remove the virtual environment and params file with the following:

make clean

Testing the code

To run static tests of the code style, run the following command:

make lint

Unit tests are also included in the module. To execute these, run the following command from this directory:

make test

To run individual tests, run the following:

(cd tests && ../env/bin/pytest <your_test>.py --cov=delphi_nchs_mortality --cov-report=term-missing)

The output will show the number of unit tests that passed and failed, along with the percentage of code covered by the tests.

None of the linting or unit tests should fail, and the code lines that are not covered by unit tests should be small and should not include critical sub-routines.