main.py

# run before creating map in main2.py to webscrape umd incident reports and put data into dataframes to feed into the map

from bs4 import BeautifulSoup
import requests
import csv

from incident import *
from analysis import *
from csvify import *
from maps_api import *
from datetime import *
from list import *

# webscrape and put data into a csv file called data.csv
csv_file = "data.csv"

# creates list of incidents across past 2 months
incidentlist = incidentListify()

# converts list to csv
csvify(incidentlist, csv_file)

# cleaning and putting webscraped data into a dataframe; use google maps geolocation api to get latitude and longitude data in a list 
# also, get formatted of addresses
df, lat_list, lon_list = create_dataframe(csv_file)

# creating lists to feed into the folium map
id_list = df['Incident ID'].tolist()
occ_time_list = df['Occurrence Time'].tolist()
rep_time_list = df['Report Time'].tolist()
type_list = df['Type'].tolist()
disposition_list = df['Disposition'].tolist()
address_list = df['Address'].tolist()   


# df.to_csv(r'api_avoider.csv') # specify path to write api_avoider to

print(df)