Datui is a terminal UI for exploring tabular data. See it on [GitHub](https://github.com/derekwisong/datui).

Point Datui at a file or URL (S3, GCS, or HTTP) and you get a keyboard-driven terminal view. Hive-partitioned directories work too!

Scroll, create charts, query, filter, sort, pivot, export, and analyze your data.

```
# view a hive-partitioned dataset
datui --hive s3://my-bucket/dataset

# explore a single local file (parquet, csv, excel, etc.)
datui /my/local/file/.parquet
```

It's powered by the Polars streaming API under the hood, so evaluation is lazy, to minimize egress and maximize performance.

Supports Parquet, CSV, JSON, NDJSON, Avro, Arrow, ORC, Excel.

## Python Module

I often want to debug a python application where I'm working on Polars `DataFrame` (and `LazyFrame`) instances. 

[I created a python wrapper](https://derekwisong.github.io/datui/latest/user-guide/python-module.html) so that I could launch Datui interactively from within a python terminal session.

```python
import polars as pl
import datui

# From a LazyFrame (e.g. scan)
lf = pl.scan_csv("data.csv")
datui.view(lf)
```

You can `pip install datui` to get going! It will also include the main `datui` binary application.

## Quick Install (Mac and Linux)

```
curl -fsSL https://raw.githubusercontent.com/derekwisong/datui/main/scripts/install/install.sh | sh
```

See the [install guide](https://derekwisong.github.io/datui/latest/getting-started/installation.html) or [README.md](https://github.com/derekwisong/datui/blob/main/README.md) for more!


## Disclosure

*This software's code is partially AI-generated.*

If anyone cares, I wrote the initial version containing most of the core by hand. The machines helped color in the lines!

I made Datui to effortlessly explore partitioned engine data logs on S3