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CHANGELOG.md

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Changelog

0.7.0 (2022-02-25)

Improvements

  • Reduce memory usage by carrying each dataset as a pandas DataFrame with no additional copies (#21)
  • Simplify the namespaces in Save and SaveSeries (#22)

Testing

  • Update test cases affected by changes to namespaces

0.6.0 (2022-02-25)

New features

  • Load files asynchronously to reduce runtime (#16)
  • Support gzip-compressed save files (.gz extension)

Issues fixed

  • Deduplicate pawn data by adding and using new columns in the pawn dataframe: tale_date, current_record, is_humanoid_colonist (#20)

Improvements

  • Bump coverage from 6.3.1 to 6.3.2 (#19)
  • Remove functions and tests related to XML element removal, which can be spun off into a save file size reduction tool if desired
  • Remove obsolete, custom ignore rules from .gitignore

Testing

  • Move the test-related config data from config.json to pytest fixtures to simplify the project structure
  • Replace the single save file with a series of compressed save files to test the SaveSeries class and the time-series analysis features
  • Modify the GitHub Actions workflow to run the pytest test cases asynchronously first, halting on the first error, allowing for quicker feedback in the case of a problem
  • Update test cases to reflect changes to test input data, test configuration, and the usage of the new pytest fixtures

0.5.0 (2022-02-15)

New features

  • Use data from a series of save files to produce time-series datasets and visualizations
  • Each dataset is extracted from a series of save files and stored in pandas DataFrames internally
  • The in-game time is extracted from each save file and added to the data model for use as a time dimension
  • Null handling logic passes a None value into the pandas DataFrame when data is missing, such as missing plant age, pawn ambient temperature, or pawn first name

Improvements

  • Reduce memory usage by deleting the XML root element as soon as possible after instantiating a Save object
  • Bump pandas to 1.4.1
  • Bump pytest to 7.0.1
  • Configure flake8 errors to halt the GitHub Actions build process
  • Clean up code style issues raised by flake8

Notes

Example chart generated from 167 save files:
Example line chart visualizing flora population by species over time

Performance for large file sets:
During testing, the latest version was able to process 167 sequential save files in 124 seconds. This allows users with a large number of saves to load them all without too long of a wait. This could be sped up further by refactoring the SaveSeries class to initialize its Save objects asynchronously.

0.4.0 (2022-02-11)

Improvements

  • Implement a Save class with a namespace for accessing key data points and datasets
Save.data
├───datasets
│   ├───mod
│   │   ├───dataframe
│   │   └───dictionary_list
│   ├───pawn
│   │   ├───dataframe
│   │   └───dictionary_list
│   ├───plant
│   │   ├───dataframe
│   │   └───dictionary_list
│   └───weather
│       ├───dataframe
│       └───dictionary_list
├───file_size
├───game_version
├───path
└───root
  • The pandas DataFrame containing plant information for the save file can be accessed through Save.data.datasets.plant.dataframe. The namespace is created using bunch.
  • Consolidate all functions related to loading or modifying save data in the Save class
  • Bump plotly to 5.6.0

0.3.0 (2022-02-09)

New features

  • Count of every living plant species
  • Distribution chart that visualizes the current growth progress of living plants
  • Pawn environment ambient temperature
  • Current weather conditions

Improvements

  • Configure dependabot alerts
  • Use the tmp_path pytest fixture for test data storage, allowing parallel processing of test cases with file I/O

0.2.0 (2022-02-05)

New features

  • HTML report with summary information:
    • Game version
    • Save file size
    • List of installed mods
    • Pawn information
    • Flora presence and growth statistics

Testing

  • Use coverage to measure the code coverage during pytest execution and require 100% code coverage (coverage documentation)
  • Add test cases to increase overall test coverage from 48% (v0.1.0) to 100% (v0.2.0)

0.1.0 (2022-02-02)

New features

  • Python-based ELT solution that extracts meaningful information from XML data as structured data that can be easily turned into reports, visualizations, and metrics