vaccine_avaliablity.py

import json

# import os
from datetime import date

import pandas as pd
import requests
import streamlit as st

today = date.today()
today_date = today.strftime("%d-%m-%Y")  # dd/mm/YY

st.set_page_config(
    page_title="Vaccine Avaliablity",
    page_icon=":syringe:",
    layout="wide",
    initial_sidebar_state="collapsed",
)

st.markdown("# Slots availability for COVID Vaccine :syringe::syringe:")

"""
 Source: [Github](https://github.com/misalraj/vaccine_availability_info) :star:
"""

df_states = pd.read_csv("data/states.csv")
states_list = df_states["state_name"].to_list()

st.text(" \n\n")  # break line

left_column_1, center_column_1, right_column_1 = st.columns(3)

with left_column_1:
    selected_state = st.selectbox(
        "Select State",
        options=sorted(states_list),
    )

df_district_all = pd.read_csv("data/districts.csv")
df_district = df_district_all.loc[df_district_all["state_name"] == selected_state]
district_list = df_district["district_name"].tolist()

with center_column_1:
    selected_district = st.selectbox(
        "Select District",
        options=sorted(district_list),
    )

district_id = df_district_all.loc[
    df_district_all["district_name"] == selected_district, "district_id"
].item()

try:
    URL = "https://cdn-api.co-vin.in/api/v2/appointment/ \
    sessions/public/calendarByDistrict?district_id={}&date={}".format(
        district_id, today_date
    )
    res = requests.get(URL)

    calender_df = pd.DataFrame(json.loads(res.text)["centers"])
    district_pincode_list = calender_df.loc[
        calender_df["district_name"] == selected_district, "pincode"
    ]

    calender_df["from"] = pd.to_datetime(calender_df["from"]).dt.strftime("%H:%M")
    calender_df["to"] = pd.to_datetime(calender_df["to"]).dt.strftime("%H:%M")
    calender_df["Timing"] = calender_df["from"] + " - " + calender_df["to"]
    calender_df.rename(
        columns={
            "name": "Name",
            "pincode": "Pincode",
            "fee_type": "Fee type",
            "vaccine_fees": "Vaccine charge",
        },
        inplace=True,
    )

    new_df = calender_df.explode("sessions")
    new_df["Min Age Limit"] = new_df.sessions.apply(lambda x: x["min_age_limit"])
    new_df["Available Capacity"] = new_df.sessions.apply(
        lambda x: x["available_capacity"]
    )
    new_df["Date"] = new_df.sessions.apply(lambda x: x["date"])

    if "vaccine_fees" in new_df.columns:
        new_df = new_df[
            [
                "Date",
                "Available Capacity",
                "Min Age Limit",
                "Name",
                "Pincode",
                "Timing",
                "Fee type",
                "Vaccine charge",
            ]
        ]
    else:
        new_df = new_df[
            [
                "Date",
                "Available Capacity",
                "Min Age Limit",
                "Name",
                "Pincode",
                "Timing",
                "Fee type",
            ]
        ]

    selected_pincode = None

    with right_column_1:
        min_age_limit = st.radio("Min age limit", [18, 45])

    agree = st.checkbox("Filter by Pincode")

    if agree:
        selected_pincode = st.selectbox(
            "Select Pincode",
            options=sorted(set(district_pincode_list.tolist())),
        )
        calender_df_pin = new_df[new_df["Pincode"] == selected_pincode]
        st.info(
            "Results: "
            + "Pincode"
            + ": "
            + str(selected_pincode)
            + ",   "
            + str(selected_district)
            + ", "
            + str(selected_state)
        )
        calender_df_age1 = None
        if min_age_limit == 18:
            calender_df_age1 = calender_df_pin[
                calender_df_pin["Min Age Limit"] == min_age_limit
            ]
            if calender_df_age1.empty:
                st.table(calender_df_age1)
            else:
                st.table(new_df)
        elif min_age_limit == 45:
            calender_df_age1 = calender_df_pin[
                calender_df_pin["Min Age Limit"] == min_age_limit
            ]
            st.table(calender_df_age1)
    else:
        st.info("Results: " + str(selected_district) + ", " + str(selected_state))
        calender_df_age2 = None
        if min_age_limit == 18:
            calender_df_age2 = new_df[new_df["Min Age Limit"] == min_age_limit]
            if calender_df_age2.empty:
                st.table(calender_df_age2)
            else:
                st.table(new_df)
        elif min_age_limit == 45:
            calender_df_age2 = new_df[new_df["Min Age Limit"] == min_age_limit]
            st.table(calender_df_age2)

except Exception:
    st.error("Unable to fetch data. Try after a few minutes")
    # st.error(e)