plotme

scatter plot all the things in all the folders automatically but only if there have been changes

Description

Plotme takes tabular data (e.g. excel) and outputs interactive scatter plots. It is a command line tool written in python. It uses json files to configure the plots. It is for technical and non-techncial folks.

Features

• save the plot's configuration/definition with the data (plot_info.json)
• pass-through to plotly
  • scatter plot
    • mode (markers or lines)
    • marker_symbols
    • constant lines
    • error bars
    • axes kwargs
  • pio.templates
• auto-detect data files (xls, xlsx, csv only)
• supported data files: xls, xlsx, csv, txt
• filter data files (include and exclude)
• filter folders (include and exclude)
• only re-generate plots if data or plot_info has changed, (-f to force re-generate)
• pre-process
• post-process (max, min, avg)
• specify data_root using argument or current directory
• finds plot_info files at any depth in the folder tree
• validation plot_info.json using jsonschema

Install options

• download exe from releases (windows only)
• install using pipx from source (recommended if you want system wide availability)
  • pipx install git+https://github.com/3mcloud/plotme.git
• install to active python environment from source:
  • SSH: python -m pip install git+ssh://[email protected]/3mcloud/plotme.git
  • HTTPS: python -m pip install https://github.com/3mcloud/plotme.git

How to use

• from command line: plotme(.exe) -h to see arguments
• from file explorer:
  1. move to data directory or above
  2. run once to generate a template of the plot_info.json
  3. modify the template as needed
  4. run again to generate plot(s)

Contribute

unimplemented ideas, in order of priority

0. sign exe and add to releases
1. create better tests
2. use folder/file name for default plot title
3. Hierarchical plot_info based on folder structure
4. yml support
5. pkl data file support
6. 3D plots
7. plot_info linter

Develop

1. clone
2. Navigate into the folder or open the folder with your favorite python IDE
3. create conda env conda create -n plotme python=3.13
4. activate env conda activate plotme
5. install as -e package python -m pip install -e . - Note the dot at the end, it's important

Build windows exe

1. follow Develop instructions
2. choco install visualstudio2019buildtools (needed to compile orderedset)
3. pip install nuitka orderedset zstandard
4. python -m nuitka plotme --onefile --standalone --include-package=plotly --include-package-data=plotly --nofollow-import-to=module_name=pytest --msvc=latest

Test

1. follow Develop instructions
2. Install packages to run automated tests python -m pip install -e .[test]
3. run tests