Current collected state Current
Observed since 20 Oct, 22:14 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Agentic Data Engineering tools and protocols (MCP, stdio, sse, FastAPI, etc)
conda create -p venv python==3.11 -y
conda activate venv/
docker compose up
python mcp_server/stdio/mcp_server.py
python mcp_client/stdio/mcp_client.py
python mcp_server/sse/mcp_server.py
uvicorn mcp_client.sse.mcp_client:app --reload --port 3030
Upload all CSVs from the `data` folder into MySQL. Use filenames as table names.
Upload `customers.json` from the `data` folder to the `test_data` collection in the `coke` database.
Set `is_active = 0` for users where `age > 60` in the `users` table.
Update all documents in the MongoDB database "coke" inside the "coke_collection1" collection where the customer_id is 101. Set the name field to "Manmeet".
Create a new S3 bucket for staging reports and log the creation in Jira.
Move all data from `raw-bucket/sales/` to `processed-bucket/sales-clean/`.
Run this every day at 8 AM:
import pandas as pd
df = pd.read_csv("s3://raw-bucket/sales.csv")
df.to_csv("s3://processed-bucket/cleaned_sales.csv")
Raise a Jira ticket for uploading sales data and verifying transformation completeness.
Enjoy Coding!
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.1.0 | 15 Jun 2025 | 14 |
This describes our collected data; it is not a security assessment.
Shared repository data · GitHub
Observed since 20 Oct, 22:14 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:f20e4c69c19044273420a9286713339e969c1244b6c06122a9e00e7f1c3b2fae