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import altair as alt
import streamlit as st
import pandas as pd
import strava
from utils import find_default_publish_start_end_date
st.set_page_config(
page_title="Streamlit Activities analysis for Strava",
page_icon=":safety_pin:",
)
strava_header = strava.header()
st.header(":safety_pin: Streamlit Strava activities analysis")
strava_auth = strava.authenticate(header=strava_header, stop_if_unauthenticated=False)
if strava_auth is None:
st.markdown("Click the \"Connect with Strava\" button at the top to login with your Strava account and get started.")
st.stop()
# analysis on shoes
st.divider()
st.header("Display shoes analysis")
if 'athlete' not in st.session_state:
athlete = strava.get_athlete_detail(strava_auth)
st.session_state.athlete = athlete
if 'dict_shoes' not in st.session_state:
shoes = strava.get_shoes(st.session_state.athlete)
dict_shoes = {shoe["name"]: shoe["converted_distance"] for shoe in shoes}
st.session_state.dict_shoes = dict_shoes
all_shoes_names = st.session_state.dict_shoes.keys()
selected_shoes = st.multiselect(
label="Select columns to plot",
options=all_shoes_names,
)
distances = [st.session_state.dict_shoes[shoe_name] for shoe_name in selected_shoes]
if selected_shoes:
chart_data = pd.DataFrame({
'index':selected_shoes,
'kilometers':distances
})
st.bar_chart(chart_data)
else:
st.write("No column(s) selected")
# get activities on a period
st.divider()
st.header("Display zones on a period")
default_start_date, default_end_date = find_default_publish_start_end_date()
col_start_date, col_end_date = st.columns(2)
with col_start_date:
st.date_input("Start date", value=default_start_date, key="start_date")
with col_end_date:
st.date_input("End date", value=default_end_date, key="end_date")
if st.session_state.start_date > st.session_state.end_date:
st.error("Error: End date must fall after start date.")
else:
st.session_state.activities = strava.get_activities_on_period(strava_auth, [], st.session_state.start_date, st.session_state.end_date, 1)
st.write(f"You got {len(st.session_state.activities)} activities")
activities_zones = {}
for activity in st.session_state.activities:
if not activity["has_heartrate"]:
continue
try:
st.session_state.activity_zones = strava.get_activity_zones(strava_auth, activity["id"])[0]["distribution_buckets"]
except Exception as e:
st.write(e)
if not activities_zones:
activities_zones = {idx: zone["time"] // 60 for idx, zone in enumerate(st.session_state.activity_zones)}
else:
for idx, zone in enumerate(st.session_state.activity_zones):
activities_zones[idx] += (zone["time"] // 60)
zones_label = ["zone 1", "zone 2", "zone 3", "zone 4", "zone 5"]
zones_df = pd.DataFrame({
'zones': zones_label,
'minutes': activities_zones.values()
})
scale = alt.Scale(
domain=zones_label,
range=["#008000", "#ffcf3e", "#f67200", "#ee1010", "#3f2204"],
)
color = alt.Color("zones:N", scale=scale)
bars = (
alt.Chart(zones_df)
.mark_bar()
.encode(
x="zones",
y="minutes",
color=color,
)
)
st.altair_chart(bars, theme="streamlit", use_container_width=True) |