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""" |
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Data Manipulation class |
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""" |
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# package to facilitate operating system operations |
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import os |
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# package to facilitate os path manipulations |
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import pathlib |
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# package facilitating Data Frames manipulation |
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import pandas as pd |
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# package regular expressions |
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import re |
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class DataManipulator: |
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@staticmethod |
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def fn_apply_query_to_data_frame(local_logger, timmer, data_frame, extract_params): |
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timmer.start() |
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query_expression = '' |
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if extract_params['filter_to_apply'] == 'equal': |
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local_logger.debug('Will retain only values equal with "' |
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+ extract_params['filter_values'] + '" within the field "' |
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+ extract_params['column_to_filter'] + '"') |
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query_expression = '`' + extract_params['column_to_filter'] + '` == "' \ |
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+ extract_params['filter_values'] + '"' |
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elif extract_params['filter_to_apply'] == 'different': |
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local_logger.debug('Will retain only values different than "' |
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+ extract_params['filter_values'] + '" within the field "' |
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+ extract_params['column_to_filter'] + '"') |
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query_expression = '`' + extract_params['column_to_filter'] + '` != "' \ |
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+ extract_params['filter_values'] + '"' |
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elif extract_params['filter_to_apply'] == 'multiple_match': |
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local_logger.debug('Will retain only values equal with "' |
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+ extract_params['filter_values'] + '" within the field "' |
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+ extract_params['column_to_filter'] + '"') |
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query_expression = '`' + extract_params['column_to_filter'] + '` in ["' \ |
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+ '", "'.join(extract_params['filter_values'].values()) \ |
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+ '"]' |
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local_logger.debug('Query expression to apply is: ' + query_expression) |
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data_frame.query(query_expression, inplace = True) |
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timmer.stop() |
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return data_frame |
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def build_file_list(self, local_logger, timmer, given_input_file): |
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if re.search(r'(\*|\?)*', given_input_file): |
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local_logger.debug('Files pattern has been provided') |
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parent_directory = os.path.dirname(given_input_file) |
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# loading from a specific folder all files matching a given pattern into a file list |
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relevant_files_list = self.fn_build_relevant_file_list(local_logger, timmer, |
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parent_directory, |
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given_input_file) |
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else: |
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local_logger.debug('Specific file has been provided') |
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relevant_files_list = [given_input_file] |
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return relevant_files_list |
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@staticmethod |
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def fn_build_relevant_file_list(local_logger, timmer, in_folder, matching_pattern): |
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timmer.start() |
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local_logger.info('Will list all files within ' + in_folder |
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+ ' folder looking for ' + matching_pattern + ' as matching pattern') |
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list_files = [] |
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file_counter = 0 |
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if os.path.isdir(in_folder): |
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working_path = pathlib.Path(in_folder) |
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for current_file in working_path.iterdir(): |
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if current_file.is_file() and current_file.match(matching_pattern): |
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list_files.append(file_counter) |
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list_files[file_counter] = str(current_file.absolute()) |
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file_counter = file_counter + 1 |
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local_logger.info('Relevant CSV files from ' + in_folder + ' folder were identified!') |
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local_logger.info(list_files) |
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timmer.stop() |
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return list_files |
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def fn_drop_certain_columns(self, local_logger, timmer, working_dictionary): |
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for current_file in working_dictionary['files']: |
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# load all relevant files into a single data frame |
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df = self.fn_load_file_list_to_data_frame(local_logger, timmer, [current_file], |
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working_dictionary['csv_field_separator']) |
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save_necessary = False |
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for column_to_eliminate in working_dictionary['columns_to_eliminate']: |
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if column_to_eliminate in df: |
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df.drop(columns = column_to_eliminate, inplace = True) |
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save_necessary = True |
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if save_necessary: |
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self.fn_store_data_frame_to_file(local_logger, timmer, df, current_file, |
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working_dictionary['csv_field_separator']) |
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@staticmethod |
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def fn_load_file_list_to_data_frame(local_logger, timmer, file_list, csv_delimiter): |
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timmer.start() |
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combined_csv = pd.concat([pd.read_csv(filepath_or_buffer = current_file, |
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delimiter = csv_delimiter, |
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cache_dates = True, |
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index_col = None, |
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memory_map = True, |
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low_memory = False, |
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encoding = 'utf-8', |
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) for current_file in file_list]) |
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local_logger.info('All relevant files were merged into a Pandas Data Frame') |
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timmer.stop() |
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return combined_csv |
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@staticmethod |
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def fn_move_files(local_logger, timmer, source_folder, file_names, destination_folder): |
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timmer.start() |
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resulted_files = [] |
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for current_file in file_names: |
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new_file_name = current_file.replace(source_folder, destination_folder) |
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if new_file_name.is_file(): |
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os.replace(current_file, new_file_name) |
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local_logger.info('File ' + current_file |
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+ ' has just been been overwritten as ' + new_file_name) |
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else: |
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os.rename(current_file, new_file_name) |
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local_logger.info('File ' + current_file |
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+ ' has just been renamed as ' + new_file_name) |
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resulted_files.append(new_file_name) |
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timmer.stop() |
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return resulted_files |
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@staticmethod |
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def fn_store_data_frame_to_file(local_logger, timmer, input_data_frame, |
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destination_file_name, csv_delimiter): |
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timmer.start() |
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input_data_frame.to_csv(path_or_buf = destination_file_name, |
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sep = csv_delimiter, |
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header = True, |
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index = False, |
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encoding = 'utf-8') |
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local_logger.info('Data frame has just been saved to file "' + destination_file_name + '"') |
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timmer.stop() |
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danielgp /
db-extractor
