My goal is to build tools which enable working with large-scale ML datasets in the browser. The browser is critical for building compelling UIs, but previous parquet js libraries had gone abandoned.
Apache Parquet is a very complicated format. It has 22 data types, 9 encodings, 8 compression codecs. However, I can confidently say that Hyparquet is now the most conformant parquet parser in existence. It can open all the parquet files: more than PyArrow and DuckDB. I dare you to find a file that Hyparquet can’t open!
Hyparquet is MIT licensed, and there is a demo github page which can open parquet files in the browser with no backend server.
My goal is to build tools which enable working with large-scale ML datasets in the browser. The browser is critical for building compelling UIs, but previous parquet js libraries had gone abandoned.
Apache Parquet is a very complicated format. It has 22 data types, 9 encodings, 8 compression codecs. However, I can confidently say that Hyparquet is now the most conformant parquet parser in existence. It can open all the parquet files: more than PyArrow and DuckDB. I dare you to find a file that Hyparquet can’t open!
Hyparquet is MIT licensed, and there is a demo github page which can open parquet files in the browser with no backend server.