import pandas as pd
import requests
from geopy.geocoders import Nominatim
from geopy.location import Location
import datetime
import seaborn as sns
import matplotlib.pyplot as plt

def sunrise_time(location_name: str, date: str|None|tuple[str,str] = None) -> list[dict[str, str]]:
    nominatim = Nominatim(user_agent="CMU_Bootcamp")
    geo: Location | None = nominatim.geocode(location_name)
    if not geo:
        raise KeyError("Location not found")
    params = {
        "lng": geo.longitude,
        "lat": geo.latitude
    }

    if isinstance(date, tuple):
        params["date_start"] = date[0],
        params["date_end"] = date[1]
    else:
        params["date"] = date if date else "today"

    out = requests.get(
        "https://api.sunrisesunset.io/json",
        params
    )
    j = out.json()['results']
    res = j if isinstance(j, list) else [j]
    return [{
        "sunrise": r["sunrise"],
        "sunset": r["sunset"],
        "date": r["date"]
    } for r in res]

def dayLength(sunrise: str, sunset: str) -> float:
    sr = datetime.datetime.strptime(sunrise, "%I:%M:%S %p")
    ss = datetime.datetime.strptime(sunset, "%I:%M:%S %p")
    srhr = round(sr.hour + sr.minute/60, 1)
    sshr = round(ss.hour + ss.minute/60, 1)
    length = sshr - srhr
    return round(length, 1)

location = "5000 Forbes Ave, Pittsburgh"
print("Running checks...")
try:
    compare_date = "2024-08-02"
    a = sunrise_time("Juneau, Alaska", compare_date)
    b = sunrise_time("Miami, Florida", compare_date)
    print(f"Juneau, Alaska {a[0]["sunrise"]}\nMiami, Florida {b[0]["sunrise"]}")
    df = pd.DataFrame(sunrise_time("Seattle, Washington", ("2023-01-01", "2023-12-31")))
    print(f"Latest: {df["sunrise"].max()} | Earliest: {df["sunrise"].min()}")
    df = df.assign(dayLengthInHours=df.apply(lambda row: dayLength(row["sunrise"], row["sunset"]), axis=1))
    print(f"Longest: {df["dayLengthInHours"].max()} | Shortest: {df['dayLengthInHours'].min()}")
    # ax = sns.lineplot(data=df["dayLengthInHours"])
    # ax.set(xlabel="", ylabel="", xticklabels=[])
    # plt.show()
    df = df.assign(month=df.apply(lambda row: datetime.datetime.strptime(row["date"], "%Y-%m-%d").strftime("%B"), axis=1))
    print(df)
    avgs: dict[str, float] = {}
    for month in df["month"].unique():
        this_month = pd.DataFrame(df[df["month"] == month])
        total = this_month["dayLengthInHours"].astype(float).sum()
        avg = round(total / len(this_month), 1)
        avgs[month] = avg
    # ax = sns.barplot(data=avgs)
    # ax.tick_params(axis="x", rotation=45)
    # plt.show()
    print("Passed!")
except:
    print("Failed :(")