PostProcessing.py

import pandas as pd

class ResponseTable:

    def __init__(self, response_json):

        self.response_object = response_json

        self.df_field_responses = pd.DataFrame(
            columns=[[
                'requested_url',
                'final_url',
                'device_type',
                'first_contentful_paint_ms',
                'first_contentful_paint_cat',
                'pct_first_contentful_paint_fast',
                'pct_first_contentful_paint_average',
                'pct_first_contentful_paint_slow',
            ]]
        )

        self.df_field_responses = self.create_field_data_table()

# Need to create two tables (one for FIELD data and one for LAB data)
    def create_field_data_table(self):
            for (url, i) in zip(
                self.response_object['mobile'].keys(),
                range(0, len(self.response_object['mobile'].keys()))
            ):
                try:
                    print('Trying to insert response for url:', url)

                    # We reuse this below when selecting data from the response
                    fcp_loading = self.response_object['mobile'][url]['loadingExperience']['metrics']['FIRST_CONTENTFUL_PAINT_MS']

                    # --MOBILE--:
                    # Fill urls
                    self.df_field_responses.loc[i, 'requested_url'] = \
                        self.response_object['mobile'][url]['lighthouseResult']['requestedUrl']
                    self.df_field_responses.loc[i, 'final_url'] =\
                        self.response_object['mobile'][url]['lighthouseResult']['finalUrl']

                    # Fill device type
                    self.df_field_responses.loc[i, 'device_type'] = 'mobile'

                    # Fill loading experience
                    self.df_field_responses.loc[i, 'first_contentful_paint_ms'] = \
                        fcp_loading['percentile']
                    self.df_field_responses.loc[i, 'first_contentful_paint_cat'] = \
                        fcp_loading['category']

                    # Fill proportions
                    self.df_field_responses.loc[i, 'pct_first_contentful_paint_fast'] = \
                        fcp_loading['distributions'][0]['proportion']
                    self.df_field_responses.loc[i, 'pct_first_contentful_paint_average'] = \
                        fcp_loading['distributions'][1]['proportion']
                    self.df_field_responses.loc[i, 'pct_first_contentful_paint_slow'] = \
                        fcp_loading['distributions'][2]['proportion']

                    print('Inserted for row {}: {}'.format(i, self.df_field_responses.loc[i]))

                except Exception as e:
                    print('Error:', e)
                    print('Filling row with Error for row: {}; url: {}'.format(i, url))

                    # Fill in 'Error' for row if a field couldn't be found
                    self.df_field_responses.loc[i] = \
                        ['Error' for i in range(0, len(self.df_field_responses.columns))]

            return self.df_field_responses.reset_index(drop=True)