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110 lines
3.1 KiB
Python
110 lines
3.1 KiB
Python
import re
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from prompt_techniques import LLM_prompt_data
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import csv
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import xml.etree.ElementTree as ET
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import json
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class ProcessTextFile():
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def __init__(self) -> None:
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pass
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def _load_csv_file(self, filename, items):
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all_lines = []
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all_lines.append(items)
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with open(filename, mode='r') as csv_file:
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csv_reader = csv.reader(csv_file, delimiter=';')
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line_count = 0
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for row in csv_reader:
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if line_count == 0:
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print(f'Column names are {", ".join(row)}')
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line_count += 1
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continue
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row_item = {}
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for item in items:
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row_item[item] = row[items[item]]
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all_lines.append(row_item)
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line_count += 1
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print(f'Processed {line_count} lines.')
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return all_lines
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def _load_xml_file(self, filename):
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root = ET.parse(filename)
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all_dicts = []
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parsed_dict = dict()
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for child in root.iter():
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if child.text.strip():
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parsed_dict[child.tag] = re.sub(' +', ' ', child.text.strip()).replace('\n ','\n')
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if len(parsed_dict) > 3:
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all_dicts.append(parsed_dict)
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parsed_dict = dict()
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return all_dicts
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def save(self):
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Exception("not implemented")
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pass
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def prepare_for_proces():
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pass
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class GherkinData(ProcessTextFile, LLM_prompt_data):
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def __init__(self) -> None:
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super().__init__()
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self.gherkin_list = self.load()
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def load(self):
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return super()._load_xml_file("input_dataset/input_dataset.xml")
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#save not implemented
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def get_all_acceptance_criteria(self):
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return self.gherkin_list
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def __str__(self):
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make_str = ""
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for scenario in self.gherkin_list:
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scenario_name = scenario["scenario_name"]
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content_acceptance_criteria = scenario["simplified"]
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manual = scenario["manual_translation"]
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make_str += "========================\n"
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make_str += scenario_name+"\n"
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make_str += "////////////////////////\n"
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make_str += content_acceptance_criteria+"\n"
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make_str += "========================\n"
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return make_str
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def __repr__(self) -> str:
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return self.__str__()
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class RimayData(ProcessTextFile, LLM_prompt_data):
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def __init__(self) -> None:
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super().__init__()
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#load not implemented
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def load(self):
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items = {"Req Segment": 2, "Rimay Pattern":12, "Rimay Structure":13, "Non-atomic requirement": 3, "Incomplete requirement": 4, "Incorrect order requirement": 5, "Coordination ambiguity": 6, "Not requirement": 7, "Incomplete condition": 8, "Incomplete system response":9, "Passive voice":10, "Not precise verb":11}
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return super()._load_csv_file("./generated_data/output_smells/generated_rimay.csv.csv.csv", items)
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def save(self):
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return super().save()
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def prepare_for_proces(self):
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return "Rimay data needs to be stripped and processed." |