Mercurial > repos > devteam > column_maker
view column_maker.py @ 8:227e82286a0e draft
"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/column_maker commit c623e4b9f6dd6ff4b88d9386f3b0a0cb497e0a0e"
author | devteam |
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date | Wed, 24 Feb 2021 05:19:12 +0000 |
parents | e7c273e8d4d6 |
children | 33b81f9ea109 |
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#!/usr/bin/env python """ This tool takes a tab-delimited textfile as input and creates another column in the file which is the result of a computation performed on every row in the original file. The tool will skip over invalid lines within the file, informing the user about the number of lines skipped. """ import argparse import json import re import sys # functions that may be used in the compute expression from math import ( # noqa: F401 ceil, exp, floor, log, log10, sqrt ) from numpy import format_float_positional # noqa: F401 parser = argparse.ArgumentParser() parser.add_argument('input', type=argparse.FileType('r'), help="input file") parser.add_argument('output', type=argparse.FileType('wt'), help="output file") parser.add_argument('cond', nargs='?', type=str, help="expression") parser.add_argument('columns', nargs='?', type=int, help="number of columns") parser.add_argument('column_types', nargs='?', type=str, help="comma separated list of column types") parser.add_argument('--round', action="store_true", help="round result") parser.add_argument('--avoid_scientific_notation', action="store_true", help="avoid scientific notation") parser.add_argument('--header_new_column_name', default=None, type=str, help="First line of input is a header line with column " "names and this should become the name of the new " "column") parser.add_argument('--load_json', default=None, type=argparse.FileType('r'), help="overwrite parsed arguments from json file") args = parser.parse_args() argparse_dict = vars(args) if args.load_json: json_dict = json.load(args.load_json) argparse_dict.update(json_dict) fh = argparse_dict['input'] out = argparse_dict['output'] expr = argparse_dict['cond'] round_result = argparse_dict['round'] avoid_scientific_notation = argparse_dict['avoid_scientific_notation'] if argparse_dict['header_new_column_name'] is not None: header_line = fh.readline().strip('\n') out.write( '{0}\t{1}\n'.format( header_line, argparse_dict['header_new_column_name'] ) ) try: in_columns = int(argparse_dict['columns']) if in_columns < 1: # To be considered tabular, data must have at least one column. raise ValueError except Exception: if not fh.readline(): # empty file content is ok and should produce empty output out.close() sys.exit() sys.exit("Missing or invalid 'columns' metadata value, click the pencil icon in the history item and select the Auto-detect option to correct it. This tool can only be used with tab-delimited data.") try: in_column_types = argparse_dict['column_types'].split(',') except Exception: sys.exit("Missing or invalid 'column_types' metadata value, click the pencil icon in the history item and select the Auto-detect option to correct it. This tool can only be used with tab-delimited data.") if len(in_column_types) != in_columns: sys.exit("The 'columns' metadata setting does not conform to the 'column_types' metadata setting, click the pencil icon in the history item and select the Auto-detect option to correct it. This tool can only be used with tab-delimited data.") operators = 'is|not|or|and' builtin_and_math_functions = 'abs|all|any|bin|chr|cmp|complex|divmod|float|bool|hex|int|len|long|max|min|oct|ord|pow|range|reversed|round|sorted|str|sum|type|unichr|unicode|log|log10|exp|sqrt|ceil|floor' string_and_list_methods = [name for name in dir('') + dir([]) if not name.startswith('_')] whitelist = r"^([c0-9\+\-\*\/\(\)\.\'\"><=,:! ]|%s|%s|%s)*$" % (operators, builtin_and_math_functions, '|'.join(string_and_list_methods)) if not re.compile(whitelist).match(expr): sys.exit("Invalid expression") if avoid_scientific_notation: expr = "format_float_positional(%s)" % expr # Prepare the column variable names and wrappers for column data types cols, type_casts = [], [] for col in range(1, in_columns + 1): col_name = "c%d" % col cols.append(col_name) col_type = in_column_types[col - 1].strip() if not round_result and col_type == 'int': col_type = 'float' type_cast = "%s(%s)" % (col_type, col_name) type_casts.append(type_cast) col_str = ', '.join(cols) # 'c1, c2, c3, c4' type_cast_str = ', '.join(type_casts) # 'str(c1), int(c2), int(c3), str(c4)' assign = "%s = line.split('\\t')" % col_str if len(cols) == 1: # Single column, unpacking by assignment won't work assign += '[0]' wrap = "%s = %s" % (col_str, type_cast_str) skipped_lines = 0 first_invalid_line = 0 invalid_line = None lines_kept = 0 total_lines = 0 # Read input file, skipping invalid lines, and perform computation that will result in a new column code = ''' for i, line in enumerate(fh): total_lines += 1 line = line.rstrip('\\r\\n') if not line or line.startswith('#'): skipped_lines += 1 if not invalid_line: first_invalid_line = i + 1 invalid_line = line continue try: %s %s new_val = %s if round_result: new_val = int(round(new_val)) new_line = line + '\\t' + str(new_val) + "\\n" out.write(new_line) lines_kept += 1 except Exception: skipped_lines += 1 if not invalid_line: first_invalid_line = i + 1 invalid_line = line fh.close() ''' % (assign, wrap, expr) valid_expr = True try: exec(code) except Exception as e: out.close() if str(e).startswith('invalid syntax'): valid_expr = False sys.exit('Expression "%s" likely invalid. See tool tips, syntax and examples.' % expr) else: sys.exit(str(e)) if valid_expr: out.close() valid_lines = total_lines - skipped_lines print('Creating column %d with expression %s' % (in_columns + 1, expr)) if valid_lines > 0: print('kept %4.2f%% of %d lines.' % (100.0 * lines_kept / valid_lines, total_lines)) else: print('Possible invalid expression "%s" or non-existent column referenced. See tool tips, syntax and examples.' % expr) if skipped_lines > 0: print('Skipped %d invalid lines starting at line #%d: "%s"' % (skipped_lines, first_invalid_line, invalid_line))