Source
yaml
id: couchbase-to-pandas
namespace: company.team
tasks:
- id: query_couchbase
type: io.kestra.plugin.couchbase.Query
connectionString: couchbase://10.57.233.41
username: admin
password: admin_password
query: |
SELECT id, country, name, type, iata, icao
FROM `travel-sample`.`inventory`.`airline`
fetchType: FETCH
- id: pandas
type: io.kestra.plugin.scripts.python.Script
beforeCommands:
- pip install pandas > /dev/null
outputFiles:
- final.csv
script: |
import pandas as pd
data = {{ outputs.query_couchbase.rows }}
df = pd.DataFrame(data)
agg_df = df.groupby('country')['country'].count().reset_index(name="count")
print(agg_df.head())
agg_df.to_csv("final.csv", index=False)
About this blueprint
Python SQL
This flow extracts data from a Couchbase database and then performs transformation (aggregation) on the fetched results using Pandas in a Python script.
The sample bucket travel-sample is used in this blueprint.
You can setup Couchbase locally on Docker using:
bash
docker run -d --name db -p 8091-8096:8091-8096 -p 11210-11211:11210-11211
couchbase
Once the container is up and running, go to http://localhost:8091/ in your browser and select "Setup New Cluster". Set up the new cluster by providing the appropriate Cluster Name, Admin Username, and Password.
Once the cluster is created, load data from Sample Buckets present under
the Settings tab. The data from the sample bucket travel-sample is used
in this blueprint.
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