#!/usr/bin/env python3

import requests
from bs4 import BeautifulSoup
import pandas as pd

# URLs to parse
modra_URL = "https://www.modra.si/skladi-in-podskladi/"
infond_URL = "https://www.infond.si/tecajnica-vzajemnih-skladov"

# Fake headers, otherwise Modra won't work
headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}


###############################################################################
# Parse Modra Zavarovalnica
#

a = requests.get(modra_URL, headers = headers)

df_list = pd.read_html(a.text, thousands=None)
df = df_list[0]

# Rename Columns
df.rename(columns = {'VEP ? Vrednost enote premoženja':'VEP', 'Sklad':'SKLAD'}, inplace = True)

# Drop all columns except the ones we want
df = df.filter(['SKLAD', 'VEP'])

# Drop all rows except the ones we want
subset = df[(df["SKLAD"]=="Dinamični podsklad") | (df["SKLAD"] =="Zajamčeni podsklad") ]



###############################################################################
# Parse Sava Infond Skladi
#

a = requests.get(infond_URL, headers = headers)
df_list = pd.read_html(a.text, thousands=None)


# Drop all columns except the ones we want
df_list[0] = df_list[0].filter(['SKLAD', 'VEP'])

# Cleanup the "SKLAD" name
a = df_list[0].at[23,'SKLAD']
df_list[0].at[23,'SKLAD'] = a.split()[0]+' '+a.split()[1]
df_list[0].at[23,'VEP'] = a.split()[2]

a = df_list[0].at[15,'SKLAD']
df_list[0].at[15,'SKLAD'] = a.split()[0]+' '+a.split()[1]
df_list[0].at[15,'VEP'] = a.split()[2]


# Drop all rows except the ones we want
df = df_list[0]
subset1 = df[(df["SKLAD"]=="Infond Defensive") | (df["SKLAD"] =="Infond Technology") ]



###############################################################################
# Create new datatable and output it
#

output_table = pd.concat([subset, subset1], axis=0)
output_table = output_table.reset_index(drop=True)
print(output_table)