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Releases: GoldenCheetah/sweatpy

0.25.0

01 Feb 12:15
56016e7
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[0.25.0] - 2022-02-01

Added

  • Added full support for parsing fit, tcx and gpx courses. Some of the functionality was already working, this release makes it complete.

0.24.0

16 Dec 14:10
27b3bb7
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[0.24.0] - 2021-12-16

Added

  • Adds processing of resting heartrate to athlete model from FIT files.

Fixed

  • Adds fixes for processing age and heigh to athlete model from FIT files.

0.23.2

13 Dec 10:24
567999d
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[0.23.2] - 2021-12-13

Fixed

  • Fixes parsing the activity_class attribute on the athlete model returned by read_fit(metadata=True). It should now handle all possible values.

0.23.1

11 Nov 14:29
19a1e49
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[0.23.1] - 2021-11-11

Fixed

  • Some FIT files contain records with duplicate field names of which only 1 was not null. Added code to make sure that the non null value was picked.

0.23.0

01 Nov 18:48
7ec400e
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[0.23.0] - 2021-11-01

Changed

  • Updated dependency versions. Most notable is scikit-learn to ">= 0.23.1".

Deprecated

  • Python 3.6 support will be dropped in a next release as it is nearing EOL and some dependencies like scikit-learn already do not support it in their latest releases.

0.22.1

19 Oct 18:01
eed6b34
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[0.22.1] - 2021-10-19

Fixed

  • Relax Athlete model validation because it raised errors for some FIT files.

0.22.0

19 Oct 11:24
3cf3c86
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[0.22.0] - 2021-10-19

Added

  • When metadata=True is passed to sweat.read_fit() the response now includes an "athlete" key that contains an Athlete model with information about the athlete.

Fixed

  • Suunto hrv samples that consist of only 1 value are now properly handled and do not raise a TypeError anymore.

0.21.0

22 Apr 13:00
b93fdb2
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[0.21.0] - 2021-04-22

Added

  • Adds testing for Python 3.10
  • read_tcx() now supports a metadata=True kwarg that will return device data.

0.20.3

20 Apr 17:16
23f7ea6
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[0.20.3] - 2021-04-20

Fixed

  • sweat.read_fit() now supports integer column names.

0.20.2

16 Apr 12:43
d5fda3b
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[0.20.2] - 2021-04-16

Fixed

  • read_fit() now handles summary data correctly when there is no data