Discover reviews on "json api to postgres with python etl" based on Reddit discussions and experiences.
Last updated: September 6, 2024 at 11:33 AM
Summary of Reddit Comments on "json api to Postgres with python etl"
Tools and Best Practices for ETL Process
- When choosing between different methods, it is advised to test them for speed: "Try both, see which one is fastest."
- Using SQL directly for appending tables can be efficient: "Is there a reason you cannot do it directly in SQL?"
- It is generally recommended to fetch and insert data table by table for efficiency and better memory management.
- For generating scripts, language models like ChatGPT can be useful: "For this kind of thing, LLMs, including ChatGPT, are very good at this."
- Tools such as
[psycopg](https://www.amazon.com/American-Duos/dp/B000UERE3M/ref=sr_1_1?dib=eyJ2IjoiMSJ9.pN80oGRsMUt6l8HOw5fHu0lyVAHc5sVdi6XuKY6S4yQnHzavjH-BHfSwnvifukXO_W05S--0-6I4EdiIUIAmnxi9yyoAO3dxNh566FMPhoSYPPYnagB_q4--aHW8EUiaV_BCtmCKZdjqUhSQ990GqOMn2ZthIWD7sLu1BRY_xb6uFppZKHvcb7r-sXzoniwR9oyDOeXOLCfr7-JplR0TawnZ_b87ZqcIGUnr4FzV9Po.vozOSa2h77N3tgrXie_M2UBRTlv0AhDPeTpXo9J-71w&dib_tag=se&keywords=psycopg&qid=1725622381&sr=8-1&tag=redditrevie08-20)fetch methods likefetchallorfetchmanyand batch insert withexecutemanycan enhance efficiency.
Environment Setup for Integration Tests
- Suggested setting up a local environment with tools like MinIO container and Postgres in Docker compose for integration tests.
- Using orchestration tools like Dagster can help in making the process environment aware.
Environment Configuration and Management
- Recommended book for handling such questions: Release It!
- Configuration setup across different environments - local, staging, prod, QA, dev - with tools like LocalStack for local testing.
- Query on the necessity and priority of setting up such processes: "Would it be agreed that setting up a process like this is a high priority?"
Tool Recommendations
- psycopg2 and SQL Alchemy are suggested tools for working with Postgres in Python ETL.
- SQL Alchemy's capability to dump a Pandas DataFrame into a Postgres database without defining a schema on the Postgres side is highlighted.
Pagination in API Responses
- Discussion on handling pagination in API responses like the presence of a
cursorfield. - Reference to handling pagination in Apache Solr.
Debugging
- Suggestions on debugging by printing the returned
datato understand the output.
These comments provide insights into tools, best practices, environment setup, configuration management, and debugging techniques related to ETL processes involving JSON API to Postgres integration using Python.
