Skip to main content

# habitica-challenge-wrangler Data wrangling tool for quickly selecting a winner from [Habitica](https://habitica.com) Challenge CSV data.

## Installation

To install the latest release from [PyPI](https://pypi.python.org/pypi):

pip install habitica-challenge-wrangler

If you already have habitica-challenge-wrangler installed, then upgrade with:

pip install –upgrade habitica-challenge-wrangler

This application requires the [pandas library](http://pandas.pydata.org/), version 0.17.0 or higher. If you have trouble installing with pip, then I suggest you use one of the scientific Python distributions, such as [Anaconda](https://www.continuum.io/) (Linux, Mac, Windows), or [WinPython](https://winpython.github.io/) (Windows only).

## Usage

First, download your Habitica challenge CSV data from the Habitica website.

Then execute the pick-winner script, passing the downloaded CSV file name as a command line argument:

pick-winner –input-file my_challenge_data.csv

By default, the leaderboard showing the top 10 participants is displayed. The number of participants to display can be specified with the –leaderboard-rows option:

pick-winner –input-file my_challenge_data.csv –leaderboard-rows 5

The intermediate data products can optionally be written to a spreadsheet with the to-excel command:

pick-winner –input-file my_challenge_data.csv –to-excel

This will write a single excel file (the name is based on your input file name), with several sheets.

  • raw: The raw challenge data.

  • reshaped: The raw challenge data in a more flexible layout compared to the raw data.

  • placings: Participant placings in each task.

  • final scores: The complete final scores.

## Scoring

Each task is considered separately. Scores are ranked from first to last, with first place getting 1 point, second place getting 2 points, and so on through to last place.

For todos, a completed todo is treated as equal first place while incomplete todos are scored as equal last place.

Finally, the ranking scores are averaged for each participant. The participant with the highest average placing in each task is considered the winner.

### Tie Breaks

In the event of a tie for first place, the names of all tied participants are printed, and a random winner is selected.

Metadata

Release files for habitica-challenge-wrangler 2.0.0

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

Source distribution (sdist)

Source distribution for habitica-challenge-wrangler 2.0.0
File Size Uploaded Provenance
habitica-challenge-wrangler-2.0.0.tar.gz 9.5 kB Without provenance Details

Release files / habitica-challenge-wrangler-2.0.0.tar.gz

Download URL habitica-challenge-wrangler-2.0.0.tar.gz
Size 9.5 kB
Tags Source
SHA-256 checksum
How to use checksums
f78c93fe7ef785ab8cf43cf15f334d0bc8257017e1201acb9b9703ca6783131a
BLAKE2b-256 checksum
How to use checksums
2e727e2016521429df59bf3a5335a1c2552919e8148c36cf1d9fc80fc466c7c3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Security for habitica-challenge-wrangler 2.0.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

2.0.0 This release

1 release file No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page