block7.py

def googletrends_queries(keywords, geo, loops=3, wait=10, csv='trends.csv'):
    # Perform searches
    print('Number of queries to do: ', len(keywords) * len(geo))

    # Prepare containers
    trends = dict.fromkeys(geo)
    errors_list = []
    cnt = 1

    # Start loops
    for g in geo:
        trends[g] = {}
        for k in keywords:
            try:
                time.sleep(wait)
                pytrends.build_payload([k], timeframe='all', geo=g, gprop='')
                trends[g][k] = pytrends.interest_over_time()[k]
                #print(cnt, 'Success: ', g, k)

            except:
                print(cnt, ') Error: ', g, ' & ', k)
                errors_list.append([g,k])
            cnt+=1

            
    ### Redo searches with errors
    if len(errors_list) > 0:
        print('\nStart errors:')

        for t in range(1,loops+1):

            if len(errors_list) > 0:
                print('Loop ', t, ': ', len(errors_list), 'errors')

                for i in errors_list:
                    g = i[0]  # 1st element geo
                    k = i[1]  # 2nd element keyword
                    try:
                        time.sleep(wait)
                        pytrends.build_payload([k], timeframe='all', 
                                               geo=g, gprop='')
                        trends[g][k] = pytrends.interest_over_time()[k]
                        errors_list.remove([g,k])  # remove from list of errors
                        #print('Success: ', g, k)
                    except:
                        #print('*** Error: ', g, ' & ', k)
                        pass
    print('\nDone -', len(errors_list), 'errors left')
    
    ### Save dataframe
    dict_of_trends = {g: pd.DataFrame(k) for g,k in trends.items()}
    data_df = pd.concat(dict_of_trends, axis=1)
    data_df.to_csv(csv,index=False)
    display(data_df.head()) # Check data
    
    return data_df