import os
from pathlib import Path

import numpy as np
import pandas as pd
import streamlit as st

from athai.data_utils import cached_download_csv


st.title("Uber pickups in NYC")

DATE_COLUMN = "date/time"
DATA_URL = (
    "https://s3-us-west-2.amazonaws.com/"
    "streamlit-demo-data/uber-raw-data-sep14.csv.gz"
)

DATA_PATH = Path(os.environ.get("APP_DATA"))


@st.cache_resource
def load_data(nrows):
    data = cached_download_csv(DATA_PATH, DATA_URL, nrows=nrows)

    def lowercase(x):
        return str(x).lower()

    data.rename(lowercase, axis="columns", inplace=True)
    data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])
    return data


data_load_state = st.text("Loading data...")
data = load_data(10000)
data_load_state.text("Done! (using st.cache)")

if st.checkbox("Show raw data"):
    st.subheader("Raw data")
    st.write(data)

st.subheader("Number of pickups by hour")
hist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0, 24))[
    0
]
st.bar_chart(hist_values)

# Some number in the range 0-23
hour_to_filter = st.slider("hour", 0, 23, 17)
filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]

st.subheader("Map of all pickups at %s:00" % hour_to_filter)
st.map(filtered_data)

uploaded_file = st.file_uploader("Choose a file")
if uploaded_file is not None:
    st.write(uploaded_file.name)
    bytes_data = uploaded_file.getvalue()
    st.write(len(bytes_data), "bytes")


st.markdown("![Kitty](./app/static/cat.jpeg)")