code: from copy import deepcopy
  import asyncio
  import json
  
  import pandas as pd
  import streamlit as st
  from structlog import get_logger
  
  from helpers import (
      fromtimestamp,
      show_weather,
      WeatherItem,
      gather_one_call_weather_data,
      clean_time,
  )
  
  log = get_logger()
  st.set_page_config(
      layout="wide",
      page_title="Peak Weather: 4,000 Footers",
      page_icon=":mountain:",
  )
  
  
  @st.cache(ttl=60 * 60)
  def load_data(lat_lon_pairs: list) -> list:
      """Function to fetch Open Weather data and cache results
  
      Args:
          lat_lon_pairs (list): Destinations to get data for
  
      Returns:
          list: List of dictionaries which are json responses from open weather
      """
      log.info("Start Load Data")
      data = asyncio.run(gather_one_call_weather_data(lat_lon_pairs))
      log.info("Returning Load Data")
      return data
  
  
  @st.cache()
  def load_metadata() -> pd.DataFrame:
      """Function to read mountain lat, lon, and other metadata and cache results
  
      Returns:
          pd.DataFrame: df containing information for 48 mountains
      """
      df = pd.read_csv("./data/mountains.csv")
      df = df.sort_values("name")
      return df
  
  
  def get_mtn_anchor(mountain: str) -> str:
      anchor = mountain.lower().replace(" ", "-")
      return f"[{mountain}](#{anchor})"
  
  
  def main():
      """Main Streamlit App Entrypoint"""
      st.title(
          ":sunny::mountain::rainbow: Peak Weather of the 4,000 Footers :rainbow::mountain::sunny:"
      )
      st.header(":umbrella: You can't stop the rain, but you can spot it! :umbrella:")
      with st.expander("Expand for Basic App Information:"):
          st.markdown(
              """\
  # Peak Weather: New Hampshire's 4,000 Footers
  
  Built to give you a dashboard view of the next few hours' forecast for New Hampshire's 48 4,000 ft mountains.
  Gonna rain on the Kinsmans?
  Is it snowing on Washington?
  Should I hike Owl's Head?
  
  Powered by [Streamlit](https://docs.streamlit.io/) + [Open Weather API](https://openweathermap.org/api).
  Specifically, Streamlit runs the web interactinos and OpenWeather provides the data.
  
  Built with :heart: from [Gar's Bar](https://tech.gerardbentley.com) by Gerard Bentley
  """
          )
      with st.spinner("Loading Mountain List"):
          base_mountains = load_metadata()
  
      with st.expander("Expand for Basic Mountain Information: "):
          st.dataframe(base_mountains)
  
      with st.spinner("Fetching Weather Data"):
          lat_lon_pairs = zip(base_mountains.lat, base_mountains.lon)
          cached_responses = load_data(lat_lon_pairs)
          weather_responses = deepcopy(cached_responses)
  
      first_response = weather_responses[0]
      log.info("Weather Response", first_response=first_response)
      if "current" not in first_response:
          st.error(
              """\
  ### Oof...
  
  Open Weather API can't be reached for data at the moment.
  Apologies, feel free to check back soon."""
          )
      st.write(
          f"## Time: {fromtimestamp(first_response['current']['dt']).strftime('%I:%M:%S %p, %b %d %Y')}"
      )
      table = []
  
      table.append("| Mountains |  |  |")
      table.append("|---|---|---|")
      for left, middle, right in zip(
          base_mountains.name[::3], base_mountains.name[1::3], base_mountains.name[2::3]
      ):
          table.append(
              f"| {get_mtn_anchor(left)} | {get_mtn_anchor(middle)} | {get_mtn_anchor(right)} |"
          )
      st.markdown("\n".join(table))
  
      for mountain, response in zip(base_mountains.name, weather_responses):
          st.write("-" * 88)
          st.write(f"#### {mountain}")
          st.write(f"({response['lat']}, {response['lon']})")
          st.write(f"Weather {clean_time(response['current']['dt'])}: ")
          current_temperature = round(response["current"]["temp"], 1)
          st.metric("Temp (F)", current_temperature, 0.0)
          for weather in response["current"]["weather"]:
              weather_item = WeatherItem(**weather)
              show_weather(weather_item)
  
          with st.expander("Expand for future forecast:"):
              for col, entry in zip(st.columns(5), response["hourly"][1:]):
                  col.write(f"{clean_time(entry['dt'])}")
                  temperature = round(entry["temp"], 1)
                  col.metric(
                      "Temp (F)", temperature, round(temperature - current_temperature, 1)
                  )
                  for weather in entry["weather"]:
                      weather_item = WeatherItem(**weather)
                      show_weather(weather_item, col)
                  current_temperature = temperature
              alerts = response.get("alerts")
              if alerts is not None:
                  for alert in alerts:
                      body = (
                          f"### Alert From {alert['sender_name']}: {alert['event']}",
                          f"Duration: {fromtimestamp(alert['start'])} - {fromtimestamp(alert['end'])}",
                          alert["description"],
                          f"Tags: {'; '.join(alert['tags'])}",
                      )
  
                      st.warning("\n".join(body))
  
  
  if __name__ == "__main__":
      main()
  
apis: pandas.read_csv