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Python package to generate ugly real-looking csvs.

Project description

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Python package to automatically uglify CSVs. Why? To improve the testing capabilities of pipelines that must be able to support strongly malformed input data.

All the malformation automated here are non-destructive, meaning they introduce confusion in the data but do not any information.

The inspiration for the automated malformation are all from real-life CSVs (sigh)

Humans will always surprise us with the ever-new malformed input data, but hey, we can try to best ruining the test CSVs!

How do I install this package?

As usual, just download it using pip:

pip install ugly_csv_generator

Tests Coverage

Since some software handling coverages sometime get slightly different results, here’s three of them:

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Python package to generate ugly real-looking csvs.

Usage example

To ruin a CSV you can use the following snippet. In the following example we use a tool to generate a random sanitized csv.

from random_csv_generator import random_csv
from ugly_csv_generator import uglify

csv = random_csv(5) # CSV with 5 lines
csv = csv[csv.columns[:3]] # We will use only the first 3 columns for this example
ugly = uglify(csv)

The initial CSV will look something like:

region province surname
Puglia Lecce Righetti
Campania Napoli Govoni
Emilia Romagna Reggio Emilia Vichi
Lombardia Lecco Costa
Umbria Perugia Fabbro

The result uglified CSV will look something like this:

0 1 2 3 4 5
nan nan nan nan nan nan
region-1 region region 0 province surname nan
nan nan nan nan nan nan
nan nan nan nan nan nan
nan nan nan nan nan nan
nan region nan province surname nan
nan region nan province surname nan
nan Puglia nan Lecce Righetti nan
nan Campania nan Napoli Govoni nan
nan Emilia Romagna nan Reggio Emilia Vichi nan
nan Lombardia nan Lecco Costa nan
nan Umbria nan Perugia Fabbro nan
nan nan nan nan nan nan
nan nan nan nan nan nan

The uglify method offers numerous keyword parameters, since the library is currently in quick evolution if you are interested in them just check out the code documentation.

Project details

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