These Python scripts update the data used on the Vaccination Progress site, which reports the progress of the COVID-19 vaccination rollout in Germany.
The file main.py runs through the following steps:
- Retrieve the latest data release from the German Impfdashboard, processing the data and updating the PostgreSQL database.
- Queries the database and returns the data in a Pandas dataframe.
- Produces a JSON file to be used to generate the Progress Bars on the site.
- Produces a Line Graph, using the Plotly Python library.
- The JSON and the Line Graph are pushed to the website.
- (After screenshots of the site are taken manually,) writes two tweets describing the progress bar and line graph.
- Posts the tweets and accompanying images to Twitter.
- Find a way to save the images for the tweets programmatically, without needing to take the site screenshots manually.
- Explore different implementations of the Progress Bars and Line Graphs.
- Create Progress Bars in Python. (Using what libraries?)
-
Create Line Graphs using the Plotly JS library. - What pros/cons are there to using Python-built graphs over JS-built?
| Package | Version |
|---|---|
| certifi | 2021.10.8 |
| charset-normalizer | 2.0.9 |
| idna | 3.3 |
| numpy | 1.21.4 |
| oauthlib | 3.1.1 |
| pandas | 1.3.4 |
| plotly | 5.4.0 |
| psycopg2 | 2.9.2 |
| python-dateutil | 2.8.2 |
| pytz | 2021.3 |
| requests | 2.26.0 |
| requests-oauthlib | 1.3.0 |
| six | 1.16.0 |
| tenacity | 8.0.1 |
| tweepy | 4.4.0 |
| urllib3 | 1.26.7 |