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https://github.com/juancarlospaco/faster-than-csv
Faster CSV for Python
https://github.com/juancarlospaco/faster-than-csv
csv csv-data csv-parser csv-parsing csv-to-html csv-to-json cython faster-than-csv process-csv python python3 speed speedup static-memory-allocation static-typing tabular-data tsv tsv-parser type-safe
Last synced: 3 months ago
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Faster CSV for Python
- Host: GitHub
- URL: https://github.com/juancarlospaco/faster-than-csv
- Owner: juancarlospaco
- License: mit
- Created: 2018-11-14T15:06:07.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-01-18T17:59:04.000Z (about 3 years ago)
- Last Synced: 2024-10-15T00:53:26.621Z (3 months ago)
- Topics: csv, csv-data, csv-parser, csv-parsing, csv-to-html, csv-to-json, cython, faster-than-csv, process-csv, python, python3, speed, speedup, static-memory-allocation, static-typing, tabular-data, tsv, tsv-parser, type-safe
- Language: Python
- Homepage: https://juancarlospaco.github.io/faster-than-csv
- Size: 15.5 MB
- Stars: 99
- Watchers: 5
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Faster-than-CSV
[](https://youtu.be/QiKwnlyhKrk?t=5)
| Library | Time (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 | `0.08` |
- This CSV Lib is ~300 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](https://github.com/AlDanial/cloc).
- Direct dependencies of the package when ready to run.
- Benchmarks run on Docker from Dockerfile on this repo.
- Stats as of year 2021.
- x86_64 64Bit AMD, SSD, Arch Artix Linux.
# Use
```python
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, URL, 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.
- `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.
**Returns:**
Data from the CSV, `dict` type.
# csv2list()
**Description:**
Takes a path of a CSV file string, process CSV and returns a list.
**Arguments:**
- `csv_file_path` path of the CSV file, `str` type, required, must not be empty string.
- `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.
**Returns:**
Data from the CSV, `list` 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:**
- `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.
**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.
- `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.
- `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.
- `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.
**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, defaults to `""`, if its empty string then No file is written.
- `html_file_path` path of the CSV file, `str` type, optional, can be empty string.
- `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.
- `header_html` HTML Header, `str` type, optional, defaults to Bulma CSS, can be empty string.
**Returns:**
Data from the CSV as HTML Table, `str` type, raw HTML (no style at all).
# csv2karax()
**Description:**
Takes a path of a CSV file string, process CSV and returns the data rendered as a [Karax](https://github.com/karaxnim/karax#karax) HTML Table.
**Arguments:**
- `csv_file_path` path of the CSV file, `str` type, required, must not be empty string.
- `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.
**Returns:** Karax DSL, `str` type.
# csv2terminal()
**Description:**
Takes a path of a CSV file string, process CSV and prints to terminal a colored prety-printed table.
**Arguments:**
- `csv_file_path` path of the CSV file, `str` type, required, must not be empty string, defaults to `""`, if its empty string then No file is written.
- `column_width` column width of the wider column, required, `int` type, must not be `0`, must not be negative.
- `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.
**Returns:** None.
# csv2xml()
**Description:**
Takes a path of a CSV file string, process CSV and returns a Valid XML string.
Output is guaranteed to be always Valid XML.
**Arguments:**
- `csv_file_path` path of the CSV file, `str` type, required, must not be empty string.
- `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.
- `header_xml` XML Header of the XML string, `str` type, optional, can be empty string, defaults to `"\n"`.
**Returns:** XML, `str` type.
# tsv2csv()
**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.
- `separator1` Separator character of the CSV data, `str` type, optional, must not be empty string.
- `separator2` Separator character of the CSV data, `str` type, optional, must not be empty string.
- `quote` Quote character of the CSV data, `str` type, optional, defaults to `'"'`, must not be empty string.
**Returns:**
Data from the CSV as TSV, `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, file must exist.
- `csv_file_path1` path of the CSV file, `str` type, required, must not be empty string, file must exist.
**Returns:** Diff.
[**For more Examples check the Examples and Tests.**](https://github.com/juancarlospaco/faster-than-csv/blob/master/examples/example.py)
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!.
```bash
$ ./build-docker.sh
$ ./run-docker.sh
$ ./run-benchmark.sh # Inside Docker.
```
# Dependencies
- **None**
# Platforms
- ✅ Linux
- ✅ Windows
- ✅ Mac
- ✅ Android
- ✅ Raspberry Pi
- ✅ BSD
# Requisites
- Python 3.6+ 64Bit.
# Windows
- If installation fails on Windows, just use the Source Code:
- Git Clone and Compile on Windows 10 on just 2 commands!.
- [Alternatively you can try Docker for Windows.](https://docs.docker.com/docker-for-windows)
- [Alternatively you can try WSL for Windows.](https://docs.microsoft.com/en-us/windows/wsl/about)
- **The file extension must be `.pyd`, NOT `.dll`.**
# Stars
# Contributors
- [SekouDiaoNlp](https://github.com/SekouDiaoNlp)
# 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.](http://tonsky.me/blog/disenchantment)
- This requires Cython ?.
No.
- This runs on PyPy ?.
No.
- This runs on Python2 ?.
I dunno. (Not supported)
- 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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