This is a practical example of how to process GitHub events from the dlt repository, such as issues or pull request creation, comments addition, etc.
We'll use the GitHub API to fetch the events and duckdb as a destination. Each event type will be sent to a separate table in DuckDB.
Setup#
- Install dlt with duckdb support:
pip install "dlt[duckdb]"
- Create a new file
github_events_dispatch.pyand paste the following code:
import dlt
from dlt.sources.helpers import requests
@dlt.resource(
primary_key="id",
table_name=lambda i: i["type"],
write_disposition="append",
)
def repo_events(last_created_at=dlt.sources.incremental("created_at")):
url = "https://api.github.com/repos/dlt-hub/dlt/events?per_page=100"
while True:
response = requests.get(url)
response.raise_for_status()
yield response.json()
# Stop requesting pages if the last element was already older than
# the initial value.
# Note: incremental will skip those items anyway, we just do not
# want to use the API limits.
if last_created_at.start_out_of_range:
break
# Get the next page.
if "next" not in response.links:
break
url = response.links["next"]["url"]
pipeline = dlt.pipeline(
pipeline_name="github_events",
destination="duckdb",
dataset_name="github_events_data",
)
load_info = pipeline.run(repo_events)
row_counts = pipeline.last_trace.last_normalize_info
print(row_counts)
print("------")
print(load_info)
In the code above, we define a resource repo_events that fetches events from the GitHub API.
Events content never changes, so we can use the append write disposition and track new events using the created_at field.
We name the tables using a function that receives event data and returns the table name: table_name=lambda i: i["type"]
- Now run the script:
python github_events_dispatch.py
- Peek at the created tables:
dlt pipeline -v github_events info
dlt pipeline github_events trace
- And preview the data:
dlt pipeline -v github_events show
Learn more:
- Change the nesting of the tables with a decorator.