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FrameX

FrameX is a light-weight, dataset fetching library for fast prototyping, tutorial creation, and experimenting. FrameX has currently over 80 datasets available.

Built on top of Polars.

Installation

To get started, install the library with:

pip install framex

Usage

Python

import framex as fx

Loading datasets

iris = fx.load("iris")

which returns a polars DataFrame
Therefore, you can use all the polars functions and methods on the returned DataFrame.

iris.head()

shape: (5, 5)
┌──────────────┬─────────────┬──────────────┬─────────────┬─────────┐
│ sepal_length ┆ sepal_width ┆ petal_length ┆ petal_width ┆ species │
│ ---          ┆ ---         ┆ ---          ┆ ---         ┆ ---     │
│ f32          ┆ f32         ┆ f32          ┆ f32         ┆ str     │
╞══════════════╪═════════════╪══════════════╪═════════════╪═════════╡
│ 5.1          ┆ 3.5         ┆ 1.4          ┆ 0.2         ┆ setosa  │
│ 4.9          ┆ 3.0         ┆ 1.4          ┆ 0.2         ┆ setosa  │
│ 4.7          ┆ 3.2         ┆ 1.3          ┆ 0.2         ┆ setosa  │
│ 4.6          ┆ 3.1         ┆ 1.5          ┆ 0.2         ┆ setosa  │
│ 5.0          ┆ 3.6         ┆ 1.4          ┆ 0.2         ┆ setosa  │
└──────────────┴─────────────┴──────────────┴─────────────┴─────────┘

iris = fx.load("iris", lazy=True)

which returns a polars LazyFrame

Both these operations create local copies of the datasets by default cache=True.

Available datasets

To see the list of available datasets, run:

fx.available()

{'remote': ['iris', 'mpg', 'netflix', 'starbucks', 'titanic'], 'local': ['titanic']}

PS, shorthened for clarity

which returns a dictionary of both locally and remotely available datasets.

To see only local or remote datasets, run:

fx.available("local")
fx.available("remote")

{'local': ['titanic']}
{'remote': ['iris', 'mpg', 'netflix', 'starbucks', 'titanic']}

Getting information on Datasets

To get information on a dataset, run:

fx.about("mpg") # basically the same as `fx.about("mpg", mode="print")`

which will print the information on the dataset as the following:

NAME    : mpg
SOURCE  : https://www.kaggle.com/datasets/uciml/autompg-dataset
LICENSE : CC0: Public Domain
ORIGIN  : Kaggle
OG NAME : autompg-dataset

Or you can get the information as a single row polars.DataFrame by running:

row = fx.about("mpg", mode="row")
print(row)

which will print the information on the dataset ASCII art as the following:

shape: (1, 4)
┌──────┬─────────────────────────────────┬────────────────────┬────────┐       
│ name ┆ source                          ┆ license            ┆ origin │       
│ ---  ┆ ---                             ┆ ---                ┆ ---    │       
│ str  ┆ str                             ┆ str                ┆ str    │       
╞══════╪═════════════════════════════════╪════════════════════╪════════╡       
│ mpg  ┆ https://www.kaggle.com/dataset… ┆ CC0: Public Domain ┆ Kaggle │       
└──────┴─────────────────────────────────┴────────────────────┴────────┘

or you can simply treat row as a polars DataFrame in your code.

Getting Dataset URLs

In case you need the file links.

url_pokemon = fx.get_url("pokemon")

by default, the format is " feather".

Optionally, you can specify the format of the dataset.

url_pokemon_csv = fx.get_url("pokemon", format="csv")

CLI

framex CLI has a slight overhead of around 400 milliseconds due to imports. However, operations still take less than a second, unless bottlenecked by the download speed.

TO see all the available commands, run:

fx -h

Banner

get

Get a single dataset (to the current directory):

fx get iris

or get multiple datasets:

fx get iris mpg titanic

which will download dataset(s) to the current directory.

to get the datasets into cache directory:

fx get iris mpg titanic --cache

or to a specific directory:

fx get iris mpg titanic --dir data

list

To get the name of the available datasets on the remote server.

fx list

this will list all available datasets on the remote server.

to get the names of the available datasets that includes "dia"

fx list dia

Locally available datasets: (feather, parquet, csv, other)

Remote datasets:
diamonds

about

To get information on a dataset or datasets, run:

fx about mpg iris

show

To show a preview of a single dataset

fx show iris

describe

To describe (or summarize) a dataset

fx describe iris

For more parameters

fx get --help

bring

Bring a dataset to the current directory from cache:

fx bring iris

or bring multiple datasets:

fx bring iris mpg titanic

which will bring dataset(s) to the current directory from cache directory.

Release files for framex 1.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for framex 1.0.3
File	Size	Uploaded
framex-1.0.3.tar.gz	16.2 kB	Jul 19, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for framex 1.0.3
File	Interpreter	ABI	Platform	Reset
framex-1.0.3-py3-none-any.whl 19.4 kB Jul 19, 2025	Python 3	none	any	Details

Total release size: 35.6 kB

Release files / framex-1.0.3.tar.gz

Download URL	framex-1.0.3.tar.gz
Size	16.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`a11731ca1e77a45cbe3f7db3399771579d401bc5b4ed8fd2d783c69032ef7d27`
BLAKE2b-256 checksum How to use checksums	`6dd3f1cbb92498977e4522954633456ea1c9d1d04334199d03937968d887f98b`
Upload date	Jul 19, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.8.5 CPython/3.12.8 Windows/11`

Release files / framex-1.0.3-py3-none-any.whl

Download URL	framex-1.0.3-py3-none-any.whl
Size	19.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`568ed2d5ca4dd749648e7a94f86af1ac1f9bd19432e57ef21b9e25b43744bff7`
BLAKE2b-256 checksum How to use checksums	`bfd69d188b7312a448289751551e99aad0936d2b0b6a6ed1ce703d3011c42729`
Upload date	Jul 19, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.8.5 CPython/3.12.8 Windows/11`