Google-play-reviews-scraper

Scraping reviews left on any app from the GPlay store

Disclaimer

This code is meant to be used for educational purposes and I take no responsibility for what you do with the code.

Code

Let's import the libraries needed

# Find app package names at https://www.fileplanet.com/apk
# Google play scraper library https://github.com/facundoolano/google-play-scraper

from google_play_scraper import app
from google_play_scraper import Sort, reviews, reviews_all
import pandas as pd
import csv
import os, glob

Create a function to extract the comments

def extract_comments(language, country, app_package_name):
    it = iter(range(1,6)) # to iterate the following loop over the selected star ratings
    for x in it: # (1,6) being star ratings from 1 to 5
        result = reviews_all(
            app_package_name,
            sleep_milliseconds=0, # defaults to 0
            lang=language, # defaults to 'en'
            country=country, # defaults to 'us'
            sort=Sort.NEWEST, # defaults to Sort.MOST_RELEVANT
            filter_score_with=x # defaults to None(means all score)
        )
    
        if result == []: # Skips x value in case there are no reviews at this score
            continue
        else:
            toCSV = result
            # Add line saying if result for x=x are 0, then skip to next value of x
            keys = toCSV[0].keys()
            filename = 'reviews_' + language + '_' + str(x) + '.csv' # eg. 'reviews_it_5.csv'
        with open(filename, 'w', encoding='utf8', newline='') as output_file:
            dict_writer = csv.DictWriter(output_file, fieldnames=toCSV[0].keys())
            dict_writer.writeheader()
            dict_writer.writerows(toCSV)

The above code creates a separate CSV for each star rating

Merge all the created CSVs into one

# Merge CSVs in one
# https://blog.softhints.com/how-to-merge-multiple-csv-files-with-python/

path_1 = ''
path_2 = 'D:/Your location of choice'

def merge_CSVs(language):
    filename = 'reviews_' + language
    all_files = glob.glob(os.path.join(path_1, filename + '*.csv'))
    df_from_each_file = (pd.read_csv(f, sep=',') for f in all_files)
    df_merged = pd.concat(df_from_each_file, ignore_index=True)
    df_merged.to_csv(path_2 + '/All_reviews_' + language + '.csv', index=False)

Let's add a language column

# Add language column
def add_language(language):
    filename = 'All_reviews_' + language + '.csv'
    all_reviews_df = pd.read_csv(path_2 + '/' + filename)
    all_reviews_df['language'] = language
    all_reviews_df.insert(loc=len(all_reviews_df.columns), column='platform', value='Android') # adding platform column
    all_reviews_df.insert(3, 'title', '') # adding title column to make df equal to iOS df
    all_reviews_df.rename(columns={'at': 'date'}, inplace=True) # changing column name from 'at' to 'date'
    return all_reviews_df, filename

Let's export the results as a CSV

# Export results to csv
def export(all_reviews_df, filename):
    all_reviews_df.to_csv(path_2 + '/' + filename, index=False)

And delete remaining single CSVs

# Delete remaining single rating files
def remove_single_CSVs():
    all_single_ratings = glob.glob(os.path.join(path_1, 'reviews*.csv'))
    for x in all_single_ratings:
      os.remove(x)

And this is the master function which directs how the other functions should flow

# Master command
def master_command(language, country, app_package_name):
    extract_comments(language, country, app_package_name)
    merge_CSVs(language)
    all_reviews_df, filename = add_language(language)
    export(all_reviews_df, filename)
    remove_single_CSVs()   

So we start it all by inputting the desired app package name here

master_command('en', 'US', 'com.spotify.music') # (language, country, package name)

As an example we have the Spotify package name inputted. However, you can of course put in any package name. You can usually find it in the URL, and it's the part that starts with com as in the example below