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