json-streamer
json-buffet
json-streamer | json-buffet | |
---|---|---|
2 | 2 | |
215 | 0 | |
- | - | |
2.4 | 3.0 | |
about 1 year ago | about 1 year ago | |
Python | C++ | |
MIT License | MIT License |
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json-streamer
- Processing large JSON datasets by streaming
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Analyzing multi-gigabyte JSON files locally
Might be useful for some - https://github.com/kashifrazzaqui/json-streamer
json-buffet
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Analyzing multi-gigabyte JSON files locally
And here's the code: https://github.com/multiversal-ventures/json-buffet
The API isn't the best. I'd have preferred an iterator based solution as opposed to this callback based one. But we worked with what rapidjson gave us for the proof of concept.
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
Ha! Thanks to you, Today I found out how big those uncompressed JSON files really are (the data wasn't accessible to me, so i shared the tool with my colleague and he was the one who ran the queries on his laptop): https://www.dolthub.com/blog/2022-09-02-a-trillion-prices/ .
And yep, it was more or less they way you did with ijson. I found ijson just a day after I finished the prototype. Rapidjson would probably be faster. Especially after enabling SIMD. But the indexing was a one time thing.
We have open sourced the codebase. Here's the link: https://github.com/multiversal-ventures/json-buffet . Since this was a quick and dirty prototype, comments were sparse. I have updated the Readme, and added a sample json-fetcher. Hope this is more useful for you.
Another unwritten TODO was to nudge the data providers towards a more streaming friendly compression formats - and then just create an index to fetch the data directly from their compressed archives. That would have saved everyone a LOT of $$$.
What are some alternatives?
ijson
japronto - Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
python-slugify - Returns unicode slugs
semi_index - Implementation of the JSON semi-index described in the paper "Semi-Indexing Semi-Structured Data in Tiny Space"
awesome-slugify - Python flexible slugify function
is2 - embedded RESTy http(s) server library from Edgio
python-nameparser - A simple Python module for parsing human names into their individual components
reddit_mining
Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
json_benchmark - Python JSON benchmarking and "correctness".
pydantic - Data validation using Python type hints
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing