maxgrinev

6 ms·

1.
by maxgrinev 1y ago
Great questions! Let me break this down: Target audience: 1) Enterprise IT teams who already know SQL/YAML - they can build complex integrations after ~1 hour of training using our examples, no prior Python needed 2) Modern data teams
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by maxgrinev 1y ago
Thank you for such an insightful suggestion and deep dive into the code - this is amazing feedback! I'll definitely switch to the ${{}} syntax you suggested. Quick clarification on _expression: we intentionally use two templating syste
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by maxgrinev 1y ago
Good catch! Yes, recalculating metrics across all historical data every run would be expensive in Snowflake. I chose this example for simplicity to show how the three operations work together, but you're absolutely right about the inef
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Dynamic YAML with Python computed properties for fusing API workflows and SQL(sequor.dev)
13 points by maxgrinev 1y ago|10 comments
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by maxgrinev 1y ago
Dynamic YAML with computed properties could have applications beyond API integrations. We use Python since it's familiar to data engineers, but our original prototype with JavaScript had even more compact syntax. Would love feedback on
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by maxgrinev 1y ago
You're right about the abstraction concern. The vast majority of the workflow stays in structured YAML - Python is only needed for two specific points: constructing HTTP request bodies and parsing JSON responses. These are inherently d
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by maxgrinev 1y ago
Totally understand - you want clean, unified data for business insights, not another integration tool to maintain. Sequor actually grew out of our Master Data Management (MDM) work where data cleaning and deduplication are core challenges.
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by maxgrinev 1y ago
Great question! Rate limiting and concurrency are absolutely critical for production API integrations. Here's how Sequor handles these challenges: Rate Limiting: * Built-in rate limiting controls at the source level (requests per secon
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by maxgrinev 1y ago
Thank you for pointing this out! I wasn't aware of Arazzo before. It does look very similar indeed. I'll definitely look more into it and see how we might align with their format or adapt it to Sequor's capabilities and execu
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by maxgrinev 1y ago
Fair point - 'intuitive' is subjective and depends on your background. Let me explain where each technology fits: HTTP request configuration (URL, headers, parameters) is pretty intuitive and similar to Postman that most people kn
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by maxgrinev 1y ago
The Python here is doing exactly what it should - extracting nested data and flattening it into proper relational tables. Most of the 'Python' is actually just the return statement defining table schemas. The schema can be defined
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by maxgrinev 1y ago
Thank you for letting me know! I'm not seeing any issues on my end - both https://docs.sequor.dev/ and https://sequor.dev/ are loading fine for me. This might be a temporary issue or could be related t
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Build API integrations with SQL and YAML – no SaaS lock-in, no drag-and-drop UIs(github.com)
50 points by maxgrinev 1y ago|24 comments
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by maxgrinev 1y ago
Thanks for the feedback! You're absolutely right that API maintenance is inherently challenging - that's actually one of the core problems we're trying to address. The key difference with Sequor is who maintains the integrati
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Show HN: Sequor – dbt for API Integration(sequor.dev)
2 points by maxgrinev 1y ago|2 comments
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by maxgrinev 13y ago
Interesting...
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Do You Really Need SQL to Do It All in Cassandra?(maxgrinev.com)
7 points by maxgrinev 16y ago|0 comments