For my final project in the de-zoomcamp course, I built a data pipeline that continuously fetches data from the League of Legends API. Every day, I ingest the previous day's matches, aggregate the data, and display it on a Google dashboard. To gather data, I collected the match histories of the top 0.01% of players (Challenger) games'. By analyzing their match histories, I aimed to identify the best times to play League of Legends.

After analyzing the data, I found that the worst games are played early in the morning, between 00:00 and 08:00 AM. However, since I have only collected data on 8.4k games so far, this conclusion is not yet certain. I plan to continue collecting data over the next few days to see if this trend holds up. Even though the results are still preliminary, they suggest that players should avoid playing League of Legends in the early morning hours if they want to have better games.

1. Create a leauge of legends account. (https://developer.riotgames.com/)

2. Use development DEVELOPMENT API KEY to call the API.

   Note: The API key will reset everyday so you need to renew it. If you don't want to renew it everyday then you need to apply for personal API key which takes 10 bussiness days to get it.

1. Create a Prefect Cloud Account [link]

2. Create a Prefect Workspace

3. Jump to the Cloud Step

4. Download the service account that is created by terraform.

5. Create Prefect Blocks

   cd prefect
   pip install -r requiremetns.txt
   prefect cloud login
   python blocks.py --sa_path="$SA_PATH" --riot_api_key="$RIOT_API_KEY"
   python deployment.py

6. Do a Test Run

1. Create Google Cloud Account

2. Install Terraform [link] and gcloud-cli [link]

3. Create a GCP Project

   Note: You mush have owner permissions in the project to able to run terraform.

4. Build the infra.

   cd terraform
   terraform init
   terraform apply \
       -var="project=$PROJECT_ID" \
       -var="prefect_key=$PREFECT_API_KEY" \
       -var="prefect_account_id=$PREFECT_ACCOUNT_ID" \
       -var="prefect_workspace_id=$PREFECT_WORKSPACE_ID" \
       --auto-approve

1. Setup a dbt cloud account.

2. Follow instructions to setup bigquery connection [link]

3. Connect this github repo to dbt cloud and specify the subdirectory as dbt.

4. Run dbt build