https://github.com/anthonybench/datapeek
Peek summary of datafile in a succinct, opinionated manner.
https://github.com/anthonybench/datapeek
cli data data-analysis
Last synced: 4 months ago
JSON representation
Peek summary of datafile in a succinct, opinionated manner.
- Host: GitHub
- URL: https://github.com/anthonybench/datapeek
- Owner: anthonybench
- License: gpl-3.0
- Created: 2022-12-25T23:18:56.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-05-23T22:56:17.000Z (about 1 year ago)
- Last Synced: 2025-08-31T09:33:37.894Z (10 months ago)
- Topics: cli, data, data-analysis
- Language: Python
- Homepage: https://pypi.org/project/sleepydatapeek/
- Size: 76.2 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# **sleepydatapeek**
*A quick way to peek at local datafiles.*
## **Welcome to sleepydatapeek!**
One often needs to spit out a configurable preview of a data file. It would also be nice if said tool could detect and read several formats automatically.\
**`sleepydatapeek`** has entered the chat!
Quickly summarize data files of type:
- `csv`
- `parquet`
- `json`
- `pkl`
- `xlsx`
And glance metadata for files:
- `pdf`
- `png`
- `jpg`|`jpeg`
> ℹ️ Note that this tool presumes format by file extension. If you leave out extensions, or give csv data a `.json` extension for funsies, then you're being silly.
> ℹ️ Due to how metadata formats vary across file types, how metadata is presented varies.
> ℹ️ For further configuration options, see the [sleepyconfig](#sleepyconfig) section below.
## **Get Started 🚀**
```sh
pip install sleepydatapeek
pip install --upgrade sleepydatapeek
python -m sleepydatapeek --help
python -m sleepydatapeek data.csv
python -m sleepydatapeek doc.pdf
```
## **Usage ⚙**
Set a function in your shell environment to run a script like:
```sh
alias datapeek='python -m sleepydatapeek'
```
Presuming you've named said macro `datapeek`, print the help message:
```sh
$ datapeek data.xlsx
════════════════════ data.xlsx ════════════════════
Unnamed: 0 CustomerID ProductName Quantity OrderDate Price
-- ------------ ------------ ------------- ---------- ----------- -------
0 0 101 Laptop 2 2023-10-26 1200
1 1 102 Mouse 1 2023-10-26 25
2 2 103 Keyboard 1 2023-10-27 50
3 3 104 Monitor 1 2023-10-27 300
4 4 105 Headphones 3 2023-10-28 80
═══Summary Stats
╭──────────────┬─────────────────╮
│ Index Column │ (no_name):int64 │
├──────────────┼─────────────────┤
│ Row Count │ 30 │
├──────────────┼─────────────────┤
│ Column Count │ 6 │
├──────────────┼─────────────────┤
│ Memory Usage │ < 0.00 bytes │
╰──────────────┴─────────────────╯
═══Schema
╭─────────────┬────────╮
│ Unnamed: 0 │ int64 │
├─────────────┼────────┤
│ CustomerID │ int64 │
├─────────────┼────────┤
│ ProductName │ object │
├─────────────┼────────┤
│ Quantity │ int64 │
├─────────────┼────────┤
│ OrderDate │ object │
├─────────────┼────────┤
│ Price │ int64 │
╰─────────────┴────────╯
═══════════════════════════════════════════════════
```
Optionally, you can also get group-by counts for distinct values of a given column:
```sh
$ datapeek test.xlsx --groupby-count-column=ProductName
# typical output (elided)
═══Groupby Counts
(row counts for distinct values of ProductName)
╭──────────────┬───╮
│ Laptop │ 3 │
├──────────────┼───┤
│ Mouse │ 3 │
├──────────────┼───┤
│ Keyboard │ 3 │
├──────────────┼───┤
│ Monitor │ 3 │
├──────────────┼───┤
│ Headphones │ 3 │
├──────────────┼───┤
│ USB Drive │ 3 │
├──────────────┼───┤
│ Printer │ 3 │
├──────────────┼───┤
│ Webcam │ 3 │
├──────────────┼───┤
│ Speakers │ 3 │
├──────────────┼───┤
│ External HDD │ 3 │
╰──────────────┴───╯
═══════════════════════════════════════════════════
```
You can check metadata for certain file types too:
```txt
$ datapeek resume.pdf
📄test.pdf
╭──────────────┬─────────────────────────────────╮
│ CreationDate │ D:20250306111007-06'00' │
├──────────────┼─────────────────────────────────┤
│ Creator │ Adobe InDesign 20.1 (Macintosh) │
├──────────────┼─────────────────────────────────┤
│ ModDate │ D:20250306111048-06'00' │
├──────────────┼─────────────────────────────────┤
│ Producer │ Adobe PDF Library 17.0 │
├──────────────┼─────────────────────────────────┤
│ Trapped │ /False │
├──────────────┼─────────────────────────────────┤
│ Length │ 48 pages │
╰──────────────┴─────────────────────────────────╯
```
## **SleepyConfig**
You can personalize a few aspects of datapeek's behavior via a file strictly named `~/.sleepyconfig/params.yml`. Paste the following into said file, and tinker to your liking:
```yml
datapeek_sample_size: 5
datapeek_table_style: 'rounded_grid'
datapeek_max_terminal_width: 80
```
All other *sleepytools* use this file as well. Browse [my PyPI](https://pypi.org/user/sleepyboy/) if you're interested!
## **Technologies 🧰**
- [Pandas](https://pandas.pydata.org/docs/)
- [Tabulate](https://pypi.org/project/tabulate/)
- [Typer](https://typer.tiangolo.com/)
- [PyArrow](https://arrow.apache.org/docs/python/index.html)
- [openpyxl](https://pypi.org/project/openpyxl/)
- [PyPDF2](https://pypdf2.readthedocs.io/en/stable/)
- [PIllow](https://pypi.org/project/pillow/)
## **Contribute 🤝**
If you have thoughts on how to make the tool more pragmatic, submit a PR 😊.
To add support for more data/file types:
1. append extension name to `supported_formats` in `sleepydatapeek_toolchain.params.py`
2. add detection logic branch to the `main` function in `sleepydatapeek_toolchain/command_logic.py`
3. update this readme
## **License, Stats, Author 📜**
See [License](LICENSE) for the full license text.
This package was authored by *Isaac Yep*. \
👉 [GitHub](https://github.com/anthonybench/datapeek) \
👉 [PyPI](https://pypi.org/project/sleepydatapeek/)