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Faster & simpler CSV replacement for Python.

Project description

Faster-than-CSV

screenshot

Library Speed
Pandas read_csv() 20.09
NumPy fromfile() 3.88
NumPy genfromtxt() 4.00
NumPy loadtxt() 1.26
csv (std lib) 0.40
csv (list) 0.38
csv (map) 0.37
Faster_than_csv 0.09
  • This CSV Lib is ~200 Lines of Code.
  • Benchmarks run on Docker from Dockerfile on this repo.
  • Speed is IRL time to complete 10000 CSV Parsings.
  • Lines Of Code counted using CLOC.
  • Direct dependencies of the package when ready to run.
  • Benchmarks run on Docker from Dockerfile on this repo.
  • Stats as of year 2019.
  • x86_64 64Bit AMD, SSD, Arch Linux.

Use

import faster_than_csv as csv

csv.csv2list("example.csv")                     # See Docs for more info.
                                                # Custom Separators supported.
csv.csv2json("example.csv", indentation=4)      # CSV to JSON, Pretty-Printed.

csv.csv2htmltable("example.csv")                # CSV to HTML+CSS Table (No JavaScript).

csv.read_clipboard()                            # CSV from the Clipboard.

csv.diff_csvs("example.csv", "anotherfile.csv") # Diff optimized for CSVs.
  • Input: CSV, TSV, Clipboard, File, Custom.
  • Output: CSV, TSV, HTML, JSON, NDJSON, Diff, File, Custom.

csv2dict()

Description: Takes a path of a CSV file string, process CSV and returns a list of dictionaries. This is very similar to pandas.read_csv(filename).

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: Data from the CSV, dict type.

read_clipboard()

Description: Reads CSV string from Clipboard, process CSV and returns a list of dictionaries. This is very similar to pandas.read_clipboard(). This works on Linux, Mac, Windows.

Arguments:

  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: Data from the CSV, dict type.

csv2json()

Description: Takes a path of a CSV file string, process CSV and returns JSON.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.
  • indentation Pretty-Printed or Minified JSON output, int type, optional, 0 is Minified, 4 is Pretty-Printed, you can use any integer to adjust the indentation.

Returns: Data from the CSV as JSON Minified Single-line string computer-friendly, str type.

csv2ndjson()

Description: Takes a path of a CSV file string, process CSV and returns NDJSON.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • ndjson_file_path path of the NDJSON file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: None. Data from the CSV as NDJSON https://github.com/ndjson/ndjson-spec, str type.

csv2htmltable()

Description: Takes a path of a CSV file string, process CSV and returns the data rendered on HTML Table.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: Data from the CSV as HTML Table, str type, raw HTML (no style at all).

csv2htmlfile()

Description: Takes a path of a CSV file string, process CSV and returns the data rendered on HTML Table.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • csv_file_path path of the HTML file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: Data from the CSV as HTML Table, str type, human-friendly, ready for display (basic style so is usable).

csv2tsv()

Description: Takes a path of a CSV file string, process CSV and returns a TSV.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Returns: Data from the CSV as TSV, str type.

csv2custom()

Description: Takes a path of a CSV file string, process CSV and returns the data rendered as Custom formatted values.

Arguments:

  • csv_file_path path of the CSV file, str type, required, must not be empty string.
  • has_header Set to True for CSV with Header, bool type, optional, defaults to True.
  • separator Separator character of the CSV data, str type, optional, defaults to ',', must not be empty string.
  • quote Quote character of the CSV data, str type, optional, defaults to '"', must not be empty string.
  • skipInitialSpace Set to True to ignore empty blank whitespace at the start of the CSV file, bool type, optional, defaults to False since is not technically valid.

Examples:

  • csv2custom(separator="💩") :arrow_right: Poo Separated Values.

Returns: Data from the CSV as Custom formatted values, str type.

diff_csvs()

Description: Takes 2 paths of 2 CSV files, process CSV and returns the Diff of the 2 CSV.

Arguments:

  • csv_file_path0 path of the CSV file, str type, required, must not be empty string.
  • csv_file_path1 path of the CSV file, str type, required, must not be empty string.

Returns: Diff.

For more Examples check the Examples and Tests.

Instead of having a pair of functions with a lot of arguments that you should provide to make it work, we have tiny functions with very few arguments that do one thing and do it as fast as possible.

Install

  • pip install faster_than_csv

Docker

  • Make a quick test drive on Docker!.
$ ./build-docker.sh
$ ./run-docker.sh
$ ./run-benchmark.sh  # Inside Docker.

Dependencies

  • None

Platforms

  • ✅ Linux
  • ✅ Windows
  • ✅ Mac
  • ✅ Android
  • ✅ Raspberry Pi
  • ✅ BSD

Requisites

  • Python 3.
  • GCC.
  • 64 Bit.

Windows

  • If installation fails on Windows, just use the Source Code:

win-compile

FAQ

  • Whats the idea, inspiration, reason, etc ?.

Feel free to Fork, Clone, Download, Improve, Reimplement, Play with this Open Source. Make it 10 times faster, 10 times smaller.

  • This requires Cython ?.

No.

  • This runs on PyPy ?.

No.

  • This runs on Python2 ?.

I dunno. (Not supported)

  • Developer Documentation ?.

Yes. (Zip because GitHub marks the Repo as being JavaScript)

  • How can I Install it ?.

https://github.com/juancarlospaco/faster-than-csv/releases

If you dont understand how to install it, you can just download, extract, put the files on the same folder as your *.py file and you are good to go.

  • How can be faster than NumPy ?.

I dunno.

  • How can be faster than Pandas ?.

I dunno.

  • Why needs 64Bit ?.

Maybe it works on 32Bit, but is not supported, integer sizes are too small, and performance can be worse.

  • Why needs Python 3 ?.

Maybe it works on Python 2, but is not supported, and performance can be worse, we suggest to migrate to Python3.

  • Can I wrap the functions on a try: except: block ?.

Functions do not have internal try: except: blocks, so you can wrap them inside try: except: blocks if you need very resilient code.

  • PIP fails to install or fails build the wheel ?.

Add at the end of the PIP install command:

--isolated --disable-pip-version-check --no-cache-dir --no-binary :all:

Not my Bug.

  • How to Build the project ?.

build.sh

  • How to Package the project ?.

package.sh

  • This requires Nimble ?.

No.

  • Whats the unit of measurement for speed ?.

Unmmodified raw output of Python timeit module.

Please send Pull Request to Python to improve the output of timeit.

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