Delete data_generate.py

data_generate.py

@@ -1,98 +0,0 @@
-import os
-import subprocess
-import pandas as pd
-from datasets import Dataset
-
-def remove_repo(path):
-    subprocess.call(f'rm -rf {path}')
-
-def download_git_or_zip(url, target_folder)->None:
-    """
-    download git repo or zip file
-    under self.projects_path
-    """
-    
-    if url.startswith("https://github.com"):
-        subprocess.call(f"git clone {url}", cwd=target_folder, shell=True)
-    else:
-        subprocess.call(f"wget {url}", cwd=target_folder, shell=True)
-        zip_name = url.split('/')[-1]
-        subprocess.call(f"unzip {zip_name}", cwd=target_folder, shell=True)
-        subprocess.call(f"rm -rf {zip_name}", cwd=target_folder, shell=True)
-
-class data_generator:
-    def __init__(self):
-        self.dataset_columns = ["repo_name", "file_path", "content"]
-        self.important_extension = ['.c','.cpp','.cxx','.cc','cp','CPP','c++','.h','.hpp']
-        self.projects_path = "data/projects"
-        self.data_path = "data/opensource_dataset.csv"
-        
-        targets = [
-            ['Framework', 'fprime', "https://github.com/nasa/fprime"],
-            ['comm', 'asio', "https://github.com/boostorg/asio"],
-            ['parsing', 'tinyxml2', "https://github.com/leethomason/tinyxml2"],
-            ['parsing', 'inifile-cpp', "https://github.com/Rookfighter/inifile-cpp"],
-            ['numerical analysis', 'oneAPI-samples', "https://github.com/oneapi-src/oneAPI-samples"],
-            ['comm', 'rticonnextdds-examples', "https://d2vkrkwbbxbylk.cloudfront.net/sites/default/files/rti-examples/bundles/rticonnextdds-examples/rticonnextdds-examples.zip"],
-            ['comm', 'rticonnextdds-robot-helpers', "https://github.com/rticommunity/rticonnextdds-robot-helpers"],
-            ['comm', 'rticonnextdds-getting-started', "https://github.com/rticommunity/rticonnextdds-getting-started"],
-            ['comm', 'rticonnextdds-usecases', "https://github.com/rticommunity/rticonnextdds-usecases"],
-            ['xyz', 'PROJ', "https://github.com/OSGeo/PROJ"],
-        ]
-        self.targets = pd.DataFrame(targets, columns=('categori','target_lib','data_source'))
-
-        if not os.path.isdir(self.projects_path):
-            os.makedirs(self.projects_path, exist_ok=True)
-
-    def process_file(self, project_name:str, dir_name:str, file_path:str):
-        """Processes a single file"""
-
-        try:
-            with open(file_path, "r", encoding="utf-8") as file:
-                content = file.read()
-                if content.strip().startswith('\n/*\nWARNING: THIS FILE IS AUTO-GENERATED'):
-                    content=""
-                elif content.strip().startswith('/*\nWARNING: THIS FILE IS AUTO-GENERATED'):
-                    content=""
-                
-        except Exception:
-            content=""
-
-        return {
-            "repo_name": project_name.replace('/','_'),
-            "file_path": file_path,
-            "content": content,
-        }
-    
-    def read_repository_files(self, project_name:str)->pd.DataFrame:
-        """
-        project_name : str
-        repo_df : pd.DataFrame
-        """
-        repo_df = pd.DataFrame(columns=self.dataset_columns)
-        file_paths = []
-        pwd = os.path.join(self.projects_path, project_name)
-        for root, _, files in os.walk(pwd):
-            for file in files:
-                file_path = os.path.join(root, file)
-
-                if file.endswith(tuple(self.important_extension)):
-                    file_paths.append((os.path.dirname(root), file_path))
-        
-        print("#"*10, f"{project_name} Total file paths:{len(file_paths)}", "#"*10)
-
-        for i, (dir_name, file_path) in enumerate(file_paths):
-            file_content = self.process_file(project_name, dir_name, file_path)
-            assert isinstance(file_content, dict)
-            if file_content["content"] != "":
-                tmp_df = pd.DataFrame.from_dict([file_content])
-                repo_df = pd.concat([repo_df, tmp_df])
-        if len(repo_df)==0:
-            repo_df = {
-                "repo_name": project_name,
-                "file_path": "",
-                "content": "",
-            }
-            repo_df = pd.DataFrame.from_dict([repo_df])
-        assert isinstance(repo_df, pd.DataFrame)
-        return repo_df