Participants may wish to use Kaggle API for a few important things, such as downloading the data and submitting their results. For a detailed explanation, visit
[kaggle-api](https://github.com/Kaggle/kaggle-api)
, but for your convenience we also provide a short step-by-step tutorial here.
1. Create a Kaggle account. (You already have this.)
 2. Get the file `kaggle.json` which is a token, by clicking on _My Account_ > _Create New API Token_.
 3. Place the token in your local machine in `"~/.kaggle/kaggle.json"` (and for Windows users in `"C:\Users\
\.kaggle\kaggle.json"`. Otherwise, you won't be able to install kaggle-api.
 4. Install Kaggle-api through your local terminal:
    ```pip3 install --user kaggle```
 5. Check the installed version:
```kaggle --version```.
It should be higher than ```Kaggle API 1.5.3```.
 6. Visit the competition page in Kaggle (Search for "_bigdata2019-flare-prediction_" in the search bar). The competition is call "_BigData Cup Challenge 2019: Flare Prediction_".
 7. To download the data through Kaggle API you can use this command:
```kaggle competitions download -c bigdata2019-flare-prediction``` .
This command can also be found in the top menu bar > _Data_.
 8. Run the command in your local terminal to download the data. (**Note:** This may take a while depending on your Internet bandwidth, since you are going to download ~6GB of data).
 9. After all files are downloaded, you should have:
    * `fold1Training.json.zip`
    * `fold2Training.json.zip`
    * `fold3Training.json.zip`
    * `sampleSubmission.csv`
    * `testSet.json`
 10. Decompress the zip files.

Now, you can work on the data on your local machine. But don't forget to use the provided tutorial code in the _Kernels_.