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data-covid19-sfbayarea

Processes for sourcing data for the Stop COVID-19 SF Bay Area dashboard, which you can find here, or on GitHub.
We are looking for feedback! Did you come here looking for a data API? Do you have questions, comments, or concerns? Don't leave yet - let us know how you are using this project and what you'd like to see implemented. Please leave us your two cents over in Issues under #101 Feedback Mega Thread.

Installation

This project requires Python 3 to run. It was built specifically with version 3.7.4, but it may run with other versions. However, it does take advantage of insertion-ordered dictionaries which are only reliable in 3.7+. To install this project, you can simply run ./install.sh in your terminal. This will set up the virtual environment and install all of the dependencies from requirements.txt and requirements-dev.txt. However, it will not keep the virtual environment running when the script ends. If you want to stay in the virtual environment, you will have to run source env/bin/activate separately from the install script.

Running the scraper

This project includes three separate scraping tools for different purposes:

Legacy CDS Scraper

The Legacy CDS Scraper loads Bay Area county data from the Corona Data Scraper project. Run it by typing into your terminal:

$ ./run_scraper.sh

This takes care of activating the virtual environment and running the actual Python scraping script. If you are managing your virtual environments separately, you can run the Python script directly with:

$ python3 scraper.py

County Website Scraper

The newer county website scraper loads data directly from county data portals or by scraping counties’ public health websites. Running the shell script wrapper will take care of activating the virtual environment for you, or you can run the Python script directly:

# Run the wrapper:
$ ./run_scraper_data.sh

# Or run the script directly if you are managing virtual environments youself:
$ python3 scraper_data.py

By default, it will output a JSON object with data for all currently supported counties. Use the --help option to see a information about additional arguments (the same options also work when running the Python script directly):

$ ./run_scraper_data.sh --help
Usage: scraper_data.py [OPTIONS] [COUNTY]...

  Create a .json with data for one or more counties. Supported counties:
  alameda, san_francisco, solano.

Options:
  --output PATH  write output file to this directory
  --help         Show this message and exit.

  • To scrape a specific county or counties, list the counties you want. For example, to scraper only Alameda and Solano counties:

    $ ./run_scraper_data.sh alameda solano

  • --output specifies a file to write to instead of your terminal’s STDOUT.

County News Scraper

The news scraper finds official county news, press releases, etc. relevant to COVID-19 and formats it as news feeds. Running the shell script wrapper will take care of activating the virtual environment for you, or you can run the Python script directly:

# Run the wrapper:
$ ./run_scraper_news.sh

# Or run the script directly if you are managing virtual environments youself:
$ python3 scraper_news.py

By default, it will output a series of JSON Feed-formatted JSON objects — one for each county. Use the --help option to see a information about additional arguments (the same options also work when running the Python script directly):

$ ./run_scraper_news.sh --help
Usage: scraper_news.py [OPTIONS] [COUNTY]...

  Create a news feed for one or more counties. Supported counties: alameda,
  contra_costa, marin, napa, san_francisco, san_mateo, santa_clara, solano,
  sonoma.

Options:
  --from CLI_DATE                 Only include news items newer than this
                                  date. Instead of a date, you can specify a
                                  number of days ago, e.g. "14" for 2 weeks
                                  ago.

  --format [json_feed|json_simple|rss]
  --output PATH                   write output file(s) to this directory
  --help                          Show this message and exit.

  • To scrape a specific county or counties, list the counties you want. For example, to scraper only Alameda and Solano counties:

    $ ./run_scraper_data.sh alameda solano

  • --from sets the earliest date/time from which to include news items. It can be a date, like 2020-07-15, a specific time, like 2020-07-15T10:00:00 for 10 am on July 15th, or a number of days before the current time, like 14 for the last 2 weeks.

  • --format sets the output format. Acceptable values are: json_feed (see the JSON Feed spec), json_simple (a simplified JSON format), or rss (RSS v2). Specify this option multiple times to output multiple formats, e.g:

    $ ./run_scraper_data.sh --format rss --format json_feed

  • --output specifies a directory to write to instead of your terminal’s STDOUT. Each county and --format combination will create a separate file in the directory. If the directory does not exist, it will be created.

Running the API

The best way to run the API right now is to run the command FLASK_APP="app.py" FLASK_ENV=development flask run;. Note that this is not the best way to run the scraper at this time.

Development

We use CircleCI to lint the code and run tests in this repository, but you can (and should!) also run tests locally.

The commands described below should all be run from within the virtual environment you’ve created for this project. If you used install.sh to get set up, you’ll need to activate your virtual environment before running them with the command:

$ source env/bin/activate

If you manage your environments differently (e.g. with Conda or Pyenv-Virtualenv), use whatever method you normally do to set up your environment.

Tests

You can run tests using pytest like so:

# In the root directory of the project:
$ python -m pytest -v .

Linting and Code Conventions

We use Pyflakes for linting. Many editors have support for running it while you type (either built-in or via a plugin), but you can also run it directly from the command line:

# In the root directory of the project:
$ pyflakes .

We also use type annotations throughout the project. To check their validity with Mypy, run:

# In the root directory of the project:
$ mypy .