https://github.com/quiteafancyemerald/geometry-dash-level-history-cli

This tool that allows you to graph or export level IDs from the game Geometry Dash on a monthly, weekly or yearly basis. It fetches approximate ID values attached to a certain date from the GDHistory API site.
https://github.com/quiteafancyemerald/geometry-dash-level-history-cli

gdscript geometry-dash geometrydash geometrydash-api python

Last synced: 1 day ago
JSON representation

This tool that allows you to graph or export level IDs from the game Geometry Dash on a monthly, weekly or yearly basis. It fetches approximate ID values attached to a certain date from the GDHistory API site.

• Host: GitHub
• URL: https://github.com/quiteafancyemerald/geometry-dash-level-history-cli
• Owner: QuiteAFancyEmerald
• License: mit
• Created: 2023-12-28T04:57:39.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-19T06:59:58.000Z (11 months ago)
• Last Synced: 2024-11-19T12:58:50.922Z (2 months ago)
• Topics: gdscript, geometry-dash, geometrydash, geometrydash-api, python
• Language: Python
• Homepage:
• Size: 66.4 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Geometry Dash ID History Graphing Utility

Upon researching for a video I created a tool that allows you to graph level IDs from the game Geometry Dash on a monthly, weekly or yearly basis. It fetches approximate ID values attached to a certain date from the GDHistory API site.

This tool uses **matplotlib** for the graph view and also supports an organized CSV export table for those who wish to export data.

**API:** https://history.geometrydash.eu/

**Interaction:** https://history.geometrydash.eu/api/v1/date/date/{random_date}

![Geometry ID History Graph Utility SS](example.png)

### Configuration

```

start_date = datetime(2013, 7, 1)

end_date = datetime.now()

date_list = [generate_random_date(date.year, date.month) for date in pd.date_range(start=start_date, end=end_date, freq='MS')]

```

### Setup

1) Clone this repository

2) Run `pip install -r requirements.txt`

3) Run either the main `run.py` file for a graph view or `spreadsheet.py` for a quick CSV export

4) Tweak the configuration as needed for use case