import pandas as pd
from pandas import json_normalize

count = 0
url_base = 'https://store.steampowered.com/appreviews/393380?json=1&cursor='
#36734

#first pass
url = urllib.request.urlopen("https://store.steampowered.com/appreviews/393380?json=1&cursor=*")
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df1 = json_normalize(data['reviews'])
count += 20
print(next_cursor)
print(count)


#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#next pass
url_temp = url_base+next_cursor
url = urllib.request.urlopen(url_temp)
data = json.loads(url.read().decode())
next_cursor = data['cursor']
df2 = json_normalize(data['reviews'])
df1 = pd.concat([df1, df2])
count += 20
print(next_cursor)
print(count)

#send df to csv
df1.to_csv('file_name.csv')