30 releases

0.9.0 Oct 17, 2024
0.8.13 Jul 19, 2024
0.8.9 Feb 10, 2024
0.8.8 Oct 2, 2023
0.7.0 Nov 25, 2022

#1005 in Parser implementations

Download history 211/week @ 2024-08-05 225/week @ 2024-08-12 289/week @ 2024-08-19 48/week @ 2024-08-26 27/week @ 2024-09-02 216/week @ 2024-09-09 125/week @ 2024-09-16 182/week @ 2024-09-23 111/week @ 2024-09-30 192/week @ 2024-10-07 485/week @ 2024-10-14 202/week @ 2024-10-21 161/week @ 2024-10-28 162/week @ 2024-11-04 116/week @ 2024-11-11 106/week @ 2024-11-18

580 downloads per month
Used in 3 crates (2 directly)

MIT license

2.5MB
4.5K SLoC

Library to python version.

Python docs


lib.rs:

Converts CSV files into XLSX/SQLITE/POSTGRESQL/PARQUET fast.

Aims

  • Thorough type guessing of CSV columns, so there is no need to configure types of each field. Scans whole file first to make sure all types in a column are consistent. Can detect over 30 date/time formats as well as JSON data.
  • Quick conversions/type guessing (uses rust underneath). Uses fast methods specific for each output format:
    • copy for postgres
    • Prepared statements for sqlite using c API.
    • Arrow reader for parquet
    • Write only mode for libxlsxwriter
  • Tries to limit errors when inserting data into database by resorting to "text" if type guessing can't determine a more specific type.
  • When inserting into existing databases automatically migrate schema of target to allow for new data (evolve option).
  • Memory efficient. All csvs and outputs are streamed so all conversions should take up very little memory.
  • Gather stats and information about CSV files into datapacakge.json file which can use it for customizing conversion.

Drawbacks

  • CSV files currently need header rows.
  • Whole file needs to be on disk as whole CSV is analyzed therefore files are read twice.

Dependencies

~10–30MB
~433K SLoC