activityio 0.0.3

Stability

Please note this package is still very much an alpha release, so breaking changes are likely.

Installation

The package is available on PyPI:

$ pip install activityio

Example Usage

There is a read function at the top-level of activityio that dispatches the appropriate reader based on file extension:

>>> import activityio as aio
>>> data = aio.read('example.srm')

NOTE substitute 'example.srm' with a path to your own activity file.

But you can also call sub-packages directly:

>>> from activityio import srm
>>> data = srm.read('example.srm')

data in the above example is a subclass of the pandas.DataFrame and provides some neat additional functionality. Most notably, certain columns are “magic” in that they return specific pandas.Series subclasses. These subclasses make unit-switching easy, and provide other useful methods:

>>> type(data)
<class 'activityio._types.activitydata.ActivityData'>

>>> data.head(5)
          temp  lap   dist  alt  cad  pwr  speed  hr
time
00:00:00  26.1    1  1.027   67    0    0  1.027  71
00:00:01  26.1    1  2.721   67    0    0  1.694  71
00:00:02  26.2    1  4.415   67    0    0  1.694  71
00:00:03  26.2    1  6.331   67    0    0  1.916  71
00:00:04  26.2    1  8.469   67    0    0  2.138  75

>>> data.normpwr()
249.54104255943844

>>> type(data.speed)
<class 'activityio._types.columns.Speed'>

>>> data.speed.base_unit
'm/s'
>>> data.speed.kph.mean()  # use a different unit
38.485063801685477

>>> data.dist.base_unit
'm'
>>> data.dist.miles[-1]
134.78580023361226

>>> data.alt.base_unit
'm'
>>> data.alt.ascent.sum()
1898.0
```

But NOTE you lose this functionality if you go changing column names

>>> data = data.rename(columns={'alt': 'altitude'})
>>> type(data.altitude)
<class 'pandas.core.series.Series'>

API Notes

The main package is composed of sub-packages that contain the reading logic for the file format after which they’re named. (e.g. activityio.fit is for parsing ANT/Garmin FIT files.)

The ultimate logic is defined in a _reading module, which provides two functions: gen_records and read_and_format.

• gen_records is a generator function for iterating over the data-points in a file. The rows of the data table if you like. A “record” is a dictionary object.

• read_and_format uses the above generator to return an ActivityData object.

read_and_format is available at the top-level of a sub-package aliased as read; so reading in a file looks like srm.read('path_to_file.srm'). gen_records is imported under the same name.

There are also some useful tools provided in module by the same name.