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README.md
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# strava_py
Create artistic visualisations with your exercise data (Python version).
This is a port of the [R strava package](https://github.com/marcusvolz/strava) to Python.
## Installation
Install via pip:
```sh
python3 -m pip install pylast
```
For development:
```sh
git clone https://github.com/marcusvolz/strava_py
cd strava_py
pip install -e .
```
Then run from the terminal:
```sh
stravavis --help
```
## Examples
### Facets
A plot of activities as small multiples. The concept behind this plot was originally inspired by [Sisu](https://twitter.com/madewithsisu).
### Map
A map of activities viewed in plan.
### Elevations
A plot of activity elevation profiles as small multiples.
### Landscape
Elevation profiles superimposed.
### Calendar
Calendar heatmap showing daily activity distance, using the [calmap](https://pythonhosted.org/calmap/) package. Requires "activities.csv" from the bulk Strava export.
### Dumbbell plot
Activities shown as horizontal lines by time of day and day of year, facetted by year. Requires "activities.csv" from the bulk Strava export.
## How to use
### Bulk export from Strava
The process for downloading data is described on the Strava website here: [https://support.strava.com/hc/en-us/articles/216918437-Exporting-your-Data-and-Bulk-Export#Bulk], but in essence, do the following:
1. Log in to [Strava](https://www.strava.com/)
2. Select "[Settings](https://www.strava.com/settings/profile)" from the main drop-down menu at top right of the screen
3. Select "[My Account](https://www.strava.com/account)" from the navigation menu to the left of the screen.
4. Under the "[Download or Delete Your Account](https://www.strava.com/athlete/delete_your_account)" heading, click the "Get Started" button.
5. Under the "Download Request", heading, click the "Request Your Archive" button. ***Don't click anything else on that page, i.e. particularly not the "Request Account Deletion" button.***
6. Wait for an email to be sent
7. Click the link in email to download zipped folder containing activities
8. Unzip files
### Process the data
The main function for importing and processing activity files expects a path to a directory of unzipped GPX and / or FIT files. If required, the [fit2gpx](https://github.com/dodo-saba/fit2gpx) package provides useful tools for pre-processing bulk files exported from Strava, e.g. unzipping activity files (see Use Case 3: Strava Bulk Export Tools).
```python
df = process_data("<path to folder with GPX and / or FIT files>")
```
Some plots use the "activities.csv" file from the Strava bulk export zip. For those plots, create an "activities" dataframe using the following function:
```python
activities = process_activities("<path to activities.csv file>")
```
### Plot activities as small multiples
```python
plot_facets(df, output_file = 'plot.png')
```
### Plot activity map
```python
plot_map(df, lon_min=None, lon_max= None, lat_min=None, lat_max=None,
alpha=0.3, linewidth=0.3, output_file="map.png")
```
### Plot elevations
```python
plot_elevations(df, output_file = 'elevations.png')
```
### Plot landscape
```python
plot_landscape(df, output_file = 'landscape.png')
```
### Plot calendar
```python
plot_calendar(activities, year_min=2015, year_max=2017, max_dist=50,
fig_height=9, fig_width=15, output_file="calendar.png")
```
### Plot dumbbell
```python
plot_dumbbell(activities, year_min=2012, year_max=2015, local_timezone='Australia/Melbourne',
fig_height=34, fig_width=34, output_file="dumbbell.png")
```