This project builds upon the dataset of John Hopkins University in CSV form which was converted to JSON Time Series format by pomber.
Our project intends to make that set queryable in a manner in which it could be easily consumed to build public dashboards.
Analyzing the dataset, here are the major points that we came across.
The API's have been mapped to use ISO 3166 standard to query countries instead of names as in the source datasets built upon as it wasn't in a standard format.
The API's consume & return dates as per ISO 8601 standards in yyyy-mm-dd format The dates have been normalized from the underlying dataset by padding single digits in the date and month section.
There's no authentication required. Anybody and everybody is welcome to use this widely.
There is no rate limit of any kind but we hope that you use it in a sensible manner and whenever possible cache response for a few hours as the underlying API's are updated thrice a day daily.
The datasets are updated thrice a day daily. As of now, we manually trigger the updation of our API's as we don't have any downstream notification's sent on updation. We are also working on having a notification mechanism in place to support all the consumers of the API. PR's are always welcome!
Postman collection has been created along with documentation for you to get started with this project. Docs can be found here
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How do I get the global data on any given day?
You could use the
/api/v1/global/2020-03-15endpoint -
How do I get the data for a country in a date-range?
Ex: To get the data for India between 10th and 19th March 2020, you could use
/api/v1/country/IND/timeseries/2020-03-10/2020-03-19 -
How do I get the data for the last record for a country?
Ex: You'll need to get the last date for any country by hitting the
/api/v1/latest-dateendpoint and then use that date to query the country endpoint like this/api/v1/country/IND/2020-03-15
git clone https://github.com/backtrackbaba/covid-api.git
Python version 3.6+ would be required to run the project
virtualenv -p python3 path/for/environment/covid
source path/for/environment/covid/bin/activate
cd path/to/cloned/project
# Change the values of env as per your local setup using example.env
source .env
cd path/to/cloned/project
flask run
Once the local instance of flask is up and running, you could use the /protected/update-db endpoint to start with the seeding of the database
Same as what you did seeding the database, you'll need to hit the same endpoint to start updating the DB with the latest data
While developing an endpoint, you could remove the cache decorator from the endpoint and enable it once the whole endpoint is up and running. Changes have been made in v2 to ensure this thing is taken care of automatically in local environment.
While hitting any global endpoints which, you might get into TypeError which is usually caused when JHU, the data provider changes names of any of the countries in the data or add a name which isn't in the country_name_to_iso.json file. You could simply add the same into the file and update the database again
Please open an issue if you get into some other problem and aren't able to figure out why it happened. I'll be glad to discuss any design decisions that you might come across in the code.
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
JSON time-series of coronavirus cases (confirmed, deaths and recovered) per country - updated daily
Saiprasad Balasubramanian - LinkedIn - Github
Harsh Jain - LinkedIn
Girisha Navani - LinkedIn
Contributions are always welcome and encouraged!! This code was whipped out in a very shot span of time for a friend to query on it. There's some refactoring to be done to remove any hacks and build on in a good manner. Ideas are always welcome
There's a roadmap in mind to build up more endpoints. As of now there are just two endpoints which with plans to add more. I'll put it out here in the Kanban board as link it with the Issues.
MIT Licensed