DEPosit Dataset

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+kkuznets/crypto-sentiment-data-pipeline,prefect/flows/extract_load_data.py,2.x,3,3,1,3,0,0,0,0,0,0,0,1,375
+kkuznets/crypto-sentiment-data-pipeline,prefect/flows/main.py,2.x,1,0,0,,0,0,0,0,0,0,1,1,57
+kkuznets/crypto-sentiment-data-pipeline,prefect/flows/transform_data.py,2.x,2,2,1,3,0,0,0,0,0,0,0,1,136
+lisallreiber/biketheft_berlin,flows/extract_web-to-gcs.py,2.x,1,3,1,3,0,0,0,0,0,0,0,1,69
+lisallreiber/biketheft_berlin,flows/load_gcs-to-bq.py,2.x,1,3,1,3,0,0,0,0,0,0,0,1,100
+lisallreiber/biketheft_berlin,flows/setup.py,2.x,1,2,0,,0,0,0,0,0,0,1,1,61
+ozkary/data-engineering-mta-turnstile,Step3-Orchestration/flows/etl_web_to_gcs.py,2.x,2,5,0,,0,0,0,0,0,0,1,1,219
+ozkary/data-engineering-mta-turnstile,Step3-Orchestration/flows/main_flow-deployment.yaml,,,,,,,,,,,,,,70
+ozkary/data-engineering-mta-turnstile,Step3-Orchestration/flows/test_deployment.py,2.x,1,1,0,,0,0,0,0,0,1,1,1,42
+sanyassyed/DataEngineering_SFO_Eviction_Data_ETL_Pipeline,flows/create_prefect_blocks.py,unknown,0,0,0,,0,0,0,0,0,0,1,1,119
+sanyassyed/DataEngineering_SFO_Eviction_Data_ETL_Pipeline,flows/deploy_ingest.py,2.x,0,0,0,,0,0,0,0,0,0,1,1,29
+sanyassyed/DataEngineering_SFO_Eviction_Data_ETL_Pipeline,flows/ingest.py,2.x,2,6,1,3,0,0,0,0,0,0,0,1,290

README.md

@@ -0,0 +1,282 @@
+---
+license: cc-by-4.0
+language:
+- en
+pretty_name: DEPosit
+
+configs:
+- config_name: repositories
+  data_files:
+  - split: train
+    path: Data/filtered_DE_repositories.csv
+
+- config_name: commits
+  data_files:
+  - split: train
+    path: Data/DE_all_commits_details.csv
+
+- config_name: pull_requests
+  data_files:
+  - split: train
+    path: Data/DE_all_pr_details.csv
+
+- config_name: issues
+  data_files:
+  - split: train
+    path: Data/DE_all_issue_details.csv
+
+- config_name: issue_closers
+  data_files:
+  - split: train
+    path: Data/DE_all_issue_closers.csv
+
+- config_name: pr_reviews
+  data_files:
+  - split: train
+    path: Data/DE_all_pr_reviews_graphql.csv
+
+- config_name: ci_services
+  data_files:
+  - split: train
+    path: Data/DE_ci_services.csv
+
+- config_name: ci_file_commits
+  data_files:
+  - split: train
+    path: Data/DE_commits_per_ci_files.csv
+
+- config_name: github_actions_runs
+  data_files:
+  - split: train
+    path: Data/DE_repo_gha_runs_counts.csv
+
+- config_name: repo_interactions
+  data_files:
+  - split: train
+    path: Data/DE_repo_interactions.csv
+
+- config_name: repo_metrics
+  data_files:
+  - split: train
+    path: Data/DE_repo_metrics.csv
+
+- config_name: user_autonomy
+  data_files:
+  - split: train
+    path: Data/DE_user_autonomy.csv
+
+- config_name: pipeline_airflow
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_airflow_dag_features.csv
+
+- config_name: pipeline_beam
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_beam_pipeline_features.csv
+
+- config_name: pipeline_dagster
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_dagster_features.csv
+
+- config_name: pipeline_dbt_model
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_dbt_model_features.csv
+
+- config_name: pipeline_dbt_project_summary
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_dbt_project_summary.csv
+
+- config_name: pipeline_dlt
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_dlt_features.csv
+
+- config_name: pipeline_files
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_files.csv
+
+- config_name: pipeline_kedro
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_kedro_pipeline_features.csv
+
+- config_name: pipeline_luigi
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_luigi_task_features.csv
+
+- config_name: pipeline_prefect
+  data_files:
+  - split: train
+    path: Data/pipeline_artifacts/DE_pipeline_prefect_flow_features.csv
+---
+
+# DEPosit — Replication Package
+
+**DEPosit** (Data Engineering Pipeline Repositories) is a dataset of open-source GitHub repositories in the data-engineering pipeline ecosystem.
+
+The dataset contains a master cohort of **1,952 repositories** together with repository activity, commits, pull requests, issues, CI-service information, contributor metrics, and pipeline discovery and feature data.
+
+## Dataset (`Data/`)
+
+The Hugging Face Hub exposes each heterogeneous CSV table as a separate **configuration**. This prevents tables with different schemas from being incorrectly concatenated by the Dataset Viewer.
+
+| Configuration | File | Description |
+|---------------|------|-------------|
+| `repositories` | `filtered_DE_repositories.csv` | Master cohort (**1,952** repos) |
+| `commits` | `DE_all_commits_details.csv` | Commits per repository |
+| `pull_requests` | `DE_all_pr_details.csv` | Pull requests |
+| `issues` | `DE_all_issue_details.csv` | Issues |
+| `issue_closers` | `DE_all_issue_closers.csv` | Issue closer logins |
+| `pr_reviews` | `DE_all_pr_reviews_graphql.csv` | PR review / merge metadata (GraphQL) |
+| `ci_services` | `DE_ci_services.csv` | Detected CI services per repo |
+| `ci_file_commits` | `DE_commits_per_ci_files.csv` | Commits touching CI config paths |
+| `github_actions_runs` | `DE_repo_gha_runs_counts.csv` | GitHub Actions run counts |
+| `repo_interactions` | `DE_repo_interactions.csv` | Precomputed interaction-type metrics |
+| `repo_metrics` | `DE_repo_metrics.csv` | Repo-level activity aggregates |
+| `user_autonomy` | `DE_user_autonomy.csv` | Contributor autonomy per repo |
+| `pipeline_airflow` | `pipeline_artifacts/DE_pipeline_airflow_dag_features.csv` | Airflow pipeline features |
+| `pipeline_beam` | `pipeline_artifacts/DE_pipeline_beam_pipeline_features.csv` | Apache Beam pipeline features |
+| `pipeline_dagster` | `pipeline_artifacts/DE_pipeline_dagster_features.csv` | Dagster pipeline features |
+| `pipeline_dbt_model` | `pipeline_artifacts/DE_pipeline_dbt_model_features.csv` | dbt model features |
+| `pipeline_dbt_project_summary` | `pipeline_artifacts/DE_pipeline_dbt_project_summary.csv` | dbt project-level features |
+| `pipeline_dlt` | `pipeline_artifacts/DE_pipeline_dlt_features.csv` | dlt pipeline features |
+| `pipeline_files` | `pipeline_artifacts/DE_pipeline_files.csv` | Discovered pipeline files |
+| `pipeline_kedro` | `pipeline_artifacts/DE_pipeline_kedro_pipeline_features.csv` | Kedro pipeline features |
+| `pipeline_luigi` | `pipeline_artifacts/DE_pipeline_luigi_task_features.csv` | Luigi task features |
+| `pipeline_prefect` | `pipeline_artifacts/DE_pipeline_prefect_flow_features.csv` | Prefect flow features |
+
+The SQLite file `DE_pipeline_artifacts.db` is retained as a downloadable replication artifact and is not used by the Hugging Face Dataset Viewer.
+
+## Join Keys
+
+- `full_name` or `repo_name` (`owner/repo`) for repository-level and process tables.
+- `repo_full_name` for tables in `pipeline_artifacts/`.
+- `(repo_full_name, file_path)` links `DE_pipeline_files.csv` to the pipeline feature tables.
+
+## Loading Data from Hugging Face
+
+Each table can be loaded independently using its configuration name:
+
+```python
+from datasets import load_dataset
+
+repos = load_dataset("taher-ghaleb/DEPosit", "repositories")
+commits = load_dataset("taher-ghaleb/DEPosit", "commits")
+issues = load_dataset("taher-ghaleb/DEPosit", "issues")
+ci = load_dataset("taher-ghaleb/DEPosit", "ci_services")
+```
+
+To load pipeline feature tables:
+
+```python
+from datasets import load_dataset
+
+airflow = load_dataset("taher-ghaleb/DEPosit", "pipeline_airflow")
+dbt = load_dataset("taher-ghaleb/DEPosit", "pipeline_dbt_model")
+prefect = load_dataset("taher-ghaleb/DEPosit", "pipeline_prefect")
+```
+
+Each configuration represents one logical table with a consistent schema. The tables are intended to be joined for analysis using the keys described above.
+
+
+## Scripts (`Scripts/`)
+
+| Script | Role |
+|--------|------|
+| `collect_github_repos_for_SE4DE_topics.py` | Topic-based repo discovery → `Data/all_DE_repositories.csv` |
+| `get_repo_commits_pr_issues_contributors_for_SE4DE_repos.py` | Commits, PRs, issues, contributors |
+| `get_issue_closers_for_SE4DE_repos.py` | Issue closer events |
+| `get_pr_reviews_graphql_for_SE4DE_repos.py` | PR reviews / merges (GraphQL) |
+| `get_pr_reviews_rest_for_SE4DE_repos.py` | PR reviews (REST alternative) |
+| `collect_github_repos_commits_per_ci_files.py` | Commits on CI-related paths |
+| `get_gha_workflow_runs_for_SE4DE_repos.py` | GitHub Actions run counts |
+| `compute_interactions_for_SE4DE_repos.py` | `DE_repo_interactions.csv` |
+| `compute_user_autonomy_for_SE4DE_repos.py` | `DE_user_autonomy.csv` |
+| `collect_pipeline_artifacts.py` | Discover and parse pipeline files |
+| `backfill_ci_gha_from_runs.py` | Add GitHub Actions to `DE_ci_services.csv` when runs exist but path detection missed them |
+| `github_api.py`, `github_tokens.py` | Shared API session and token loading |
+| `pipeline_parsers/` | Framework-specific parsers |
+| `pipeline_schema.sql` | SQLite schema for pipeline collection |
+
+## Quick start (analyze the shipped data)
+
+```powershell
+py -m pip install -r requirements.txt
+```
+
+Open `Data/filtered_DE_repositories.csv` and join to other `Data/DE_*.csv` files on `full_name` / `repo_name`.
+
+## GitHub authentication (re-collection only)
+
+**Do not commit personal access tokens.** Scripts load credentials from (in order):
+
+1. `--token` / `--tokens` CLI flags (where supported)
+2. Environment variables: `GITHUB_TOKEN_SE4DE` (preferred) or `GITHUB_TOKEN`
+3. Optional local `.env` file — copy `.env.example` to `.env` and set your PAT
+
+```powershell
+copy .env.example .env
+# Edit .env and set GITHUB_TOKEN_SE4DE=<your-pat>
+
+# Or set for the current shell only:
+$env:GITHUB_TOKEN_SE4DE = "<your-pat>"
+```
+
+For heavy REST collection, rotate rate limits with comma-separated PATs:
+
+```powershell
+$env:GITHUB_TOKENS = "<pat1>,<pat2>"
+```
+
+Example:
+
+```powershell
+py Scripts/collect_pipeline_artifacts.py --token $env:GITHUB_TOKEN_SE4DE
+py Scripts/get_gha_workflow_runs_for_SE4DE_repos.py --token $env:GITHUB_TOKEN_SE4DE
+```
+
+Typical collection order: topic discovery → development history → derived metrics → pipeline artifacts → optional `backfill_ci_gha_from_runs.py`.
+
+Historical commit/PR text in `Data/*.csv` may contain third-party leaked tokens from upstream repos; these were redacted where detected. Re-run `Scripts/redact_leaked_tokens_in_data.py` after adding new CSV exports.
+
+## Layout
+
+```text
+ReplicationPackage/
+├── README.md
+├── LICENSE
+├── DATA_LICENSE
+├── .env.example
+├── requirements.txt
+├── Data/
+│   ├── filtered_DE_repositories.csv
+│   ├── DE_*.csv
+│   ├── DE_pipeline_artifacts.db
+│   └── pipeline_artifacts/
+└── Scripts/
+    ├── collect_*.py, get_*.py, compute_*.py
+    ├── collect_pipeline_artifacts.py
+    ├── backfill_ci_gha_from_runs.py
+    ├── github_api.py, github_tokens.py
+    └── pipeline_parsers/
+```
+
+## Citation
+
+If you use DEPosit, please cite:
+
+```bibtex
+@inproceedings{deposit2026,
+  title     = {DEPosit: A Dataset of Open-Source Repositories for Data Engineering Pipelines},
+  author    = {Gorjala, Bhavyalatha and Taher A. Ghaleb},
+  booktitle = {Proceedings of the 42nd IEEE International Conference on Software Maintenance and Evolution (ICSME)},
+  year      = {2026},
+  organization={IEEE}
+}
+```

Scripts/backfill_ci_gha_from_runs.py

@@ -0,0 +1,119 @@
+"""
+Add GitHub Actions to DE_ci_services when gha_run_count > 0 but commit-path
+detection missed it (dynamic workflows, collection gaps).
+
+Does not fabricate DE_commits_per_ci_files rows; only updates ci_services_list.
+"""
+from __future__ import annotations
+
+import ast
+import csv
+import shutil
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+GHA = "GitHub Actions"
+
+
+def parse_services(raw: str) -> list[str]:
+    raw = (raw or "").strip()
+    if not raw:
+        return []
+    try:
+        val = ast.literal_eval(raw)
+        if isinstance(val, list):
+            return [str(x) for x in val]
+    except (SyntaxError, ValueError):
+        pass
+    return []
+
+
+def format_services(services: list[str]) -> str:
+    return str(services)
+
+
+def backfill_ci_file(
+    ci_path: Path,
+    runs_path: Path,
+    repos_path: Path,
+    cohort: set[str] | None,
+) -> dict[str, int]:
+    lang_by_repo = {}
+    if repos_path.is_file():
+        for r in csv.DictReader(open(repos_path, encoding="utf-8")):
+            lang_by_repo[r["full_name"]] = r.get("language") or ""
+
+    runs_by_repo = {}
+    for r in csv.DictReader(open(runs_path, encoding="utf-8")):
+        name = r["full_name"]
+        if cohort is not None and name not in cohort:
+            continue
+        count = int(r.get("gha_run_count") or 0)
+        if count > 0:
+            runs_by_repo[name] = count
+
+    fieldnames = None
+    rows = []
+    by_name = {}
+    for r in csv.DictReader(open(ci_path, encoding="utf-8")):
+        if fieldnames is None:
+            fieldnames = list(r.keys())
+        rows.append(r)
+        by_name[r["repo_name"]] = r
+
+    stats = {"updated": 0, "added": 0, "skipped_already": 0, "skipped_no_runs": 0}
+    for repo, _runs in sorted(runs_by_repo.items()):
+        row = by_name.get(repo)
+        if row is not None:
+            services = parse_services(row.get("ci_services_list", ""))
+            if GHA in services:
+                stats["skipped_already"] += 1
+                continue
+            services.append(GHA)
+            row["ci_services_list"] = format_services(services)
+            row["ci_services_count"] = str(len(services))
+            stats["updated"] += 1
+            continue
+
+        if fieldnames is None:
+            raise SystemExit(f"Missing CI header in {ci_path}")
+        new_row = {k: "" for k in fieldnames}
+        new_row["repo_name"] = repo
+        new_row["language"] = lang_by_repo.get(repo, "")
+        new_row["ci_services_count"] = "1"
+        new_row["ci_services_list"] = format_services([GHA])
+        rows.append(new_row)
+        by_name[repo] = new_row
+        stats["added"] += 1
+
+    backup = ci_path.with_suffix(ci_path.suffix + ".bak")
+    shutil.copy2(ci_path, backup)
+    with open(ci_path, "w", newline="", encoding="utf-8") as f:
+        w = csv.DictWriter(f, fieldnames=fieldnames, extrasaction="ignore")
+        w.writeheader()
+        w.writerows(rows)
+    return stats
+
+
+def main() -> None:
+    data_dir = ROOT / "Data"
+    cohort = {
+        r["full_name"]
+        for r in csv.DictReader(open(data_dir / "filtered_DE_repositories.csv", encoding="utf-8"))
+    }
+    targets = [(data_dir, cohort)]
+    for base, cohort_set in targets:
+        ci_path = base / "DE_ci_services.csv"
+        runs_path = base / "DE_repo_gha_runs_counts.csv"
+        repos_path = base / "filtered_DE_repositories.csv"
+        if not repos_path.is_file():
+            repos_path = base / "all_DE_repositories.csv"
+        if not ci_path.is_file() or not runs_path.is_file():
+            print(f"Skip {base}: missing ci or runs file")
+            continue
+        stats = backfill_ci_file(ci_path, runs_path, repos_path, cohort_set)
+        print(f"{base.name}: {stats} (backup: {ci_path.name}.bak)")
+
+
+if __name__ == "__main__":
+    main()

Scripts/collect_github_repos_commits_per_ci_files.py

@@ -0,0 +1,200 @@
+import requests
+import time
+import csv
+import os
+import sys
+import pandas as pd
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+token_index = 0
+last_request_time = {}  # Tracks last request time per token
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+
+def makeRequest(api_url, params):
+    global token_index
+    _ensure_auth()
+    num_tries = 0
+    max_tries = 3
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print(' -- Max retries reached. Exiting...', end='')
+            break
+        
+        # Find the first available token
+        available_token = None
+        current_time = time.time()
+        for i in range(len(authorization_headers)):
+            if i not in last_request_time or (current_time - last_request_time[i] >= 1):
+                available_token = i
+                break
+        
+        if available_token is None:
+            min_wait = min(last_request_time.values()) + 1 - current_time
+            time.sleep(max(min_wait, 1))
+            continue
+        
+        token_index = available_token
+        headers = authorization_headers[token_index]
+        last_request_time[token_index] = time.time()
+        
+        while True:
+            try:
+                response = requests.get(api_url, headers=headers, params=params, timeout=30)
+                break
+            except requests.exceptions.RequestException as e:
+                print(f' -- Request error: {e}. Retrying in 60 seconds...', end='')
+                time.sleep(60)
+            except Exception as e:
+                print(f' -- Another request error: {e}. Retrying in 60 seconds...', end='')
+                time.sleep(60)
+
+        if response.status_code == 200:
+            return response.json()
+        elif response.status_code == 403 and ('message' in response.json() and 'rate limit' in response.json()['message'].lower()):
+            last_request_time[token_index] = time.time()
+        elif response.status_code == 422 or response.status_code == 401:
+            return None
+        else:
+            print(f' -- Request failed with status code {response.status_code}. Retrying... ' + api_url, end='')
+            time.sleep(1)
+            
+def search_repo_commits_by_ci_file_path(repo_name, ci_file_path, csv_file, csv_writer):
+    '''
+    Perform a GitHub Search API query for commits per repository based on the path to a CI configuration file.
+    Write results directly to a file.
+    '''
+    GITHUB_API_URL = f'https://api.github.com/repos/{repo_name}/commits'
+    page = 1
+    per_page = 100
+    num_commits = 0
+    while True:
+        params = {
+            'path': ci_file_path,
+            'per_page': per_page,
+            'page': page,
+        }
+
+        data = makeRequest(GITHUB_API_URL, params)
+
+        if not data or len(data) == 0:
+            #print(f'No commits found.')
+            return num_commits
+
+        #print(f'  Page {page} for query: {GITHUB_API_URL}?path={ci_file_path}&per_page={per_page}&page={page}')
+
+        for commit in data:
+            num_commits += 1
+            commit_info = {
+                'repo_name': repo_name,
+                'configuration_file': ci_file_path,
+                'commit_sha': commit['sha'],
+                'parent_sha': ', '.join([parent['sha'] for parent in commit['parents']]) if commit['parents'] else '',
+                'commit_message': commit['commit']['message'].lstrip().rstrip().replace('\n', '\\n'),
+                'author_login': commit['author']['login'] if commit['author'] else '',
+                'author_name': commit['commit']['author']['name'],
+                'author_email': commit['commit']['author']['email'],
+                'author_date': commit['commit']['author']['date'],
+                'committer_login': commit['committer']['login'] if commit['committer'] else '',
+                'committer_name': commit['commit']['committer']['name'],
+                'committer_email': commit['commit']['committer']['email'],
+                'committer_date': commit['commit']['committer']['date'],
+                'comment_count': commit['commit']['comment_count']
+            }
+            csv_writer.writerow(commit_info.values())
+            csv_file.flush()
+        
+        if len(data) < per_page or page == 10:
+            break
+
+        page += 1
+
+    if page == 10 and len(data) == 100:
+        print('[This request has more than 1000 results]')
+    
+    return num_commits
+
+if __name__ == '__main__':
+    last_stopped_repo = 'immu0001/Udacity-Data-Engineer-nanodegree' # Last one for all services
+    
+    input_path = f'../Data/all_DE_repositories.csv'
+    commits_output_path = f'../Data/DE_commits_per_ci_files.csv'
+    repos_ci_output_path = f'../Data/DE_ci_services.csv'
+
+    ci_file_paths = {
+        # Keep in sync with ci-services.tex (ICSME data paper Table).
+        '.github/workflows': 'GitHub Actions',
+        '.travis.yml': 'Travis CI',
+        'circle.yml': 'CircleCI',
+        '.circleci/config.yml': 'CircleCI',
+        '.gitlab-ci.yml': 'GitLab',
+        '.appveyor.yml': 'AppVeyor',
+        'appveyor.yml': 'AppVeyor',
+        'azure-pipelines.yml': 'Azure Pipelines',
+        'bitbucket-pipelines.yml': 'Bitbucket',
+        '.cirrus.yml': 'Cirrus',
+        '.scrutinizer.yml': 'Scrutinizer CI',
+        'codeship-services.yml': 'Codeship',
+        '.semaphore/semaphore.yml': 'Semaphore',
+        'wercker.yml': 'Wercker',
+        'Jenkinsfile': 'Jenkins',
+        'bitrise.yml': 'Bitrise',
+        'bamboo.yml': 'Bamboo',
+        '.gocd.yaml': 'GoCD',
+        'codemagic.yaml': 'Codemagic',
+    }
+
+    first_commits_time_csv = True if not os.path.exists(commits_output_path) else False
+    commits_csv_file = open(commits_output_path, 'a', newline='', encoding='utf-8')
+    commits_csv_writer = csv.writer(commits_csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
+    if first_commits_time_csv:
+        commits_csv_writer.writerow(['repo_name', 'language', 'configuration_file', 'commit_sha', 'parent_sha', 'commit_message', 'author_login', 'author_name', 'author_email', 'author_date', 'committer_login', 'committer_name', 'committer_email', 'committer_date', 'comment_count'])
+        commits_csv_file.flush()
+
+    first_time_repos_ci_mapping_csv = True if not os.path.exists(repos_ci_output_path) else False
+    repos_ci_csv_file = open(repos_ci_output_path, 'a', newline='', encoding='utf-8')
+    repos_ci_csv_writer = csv.writer(repos_ci_csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
+    if first_time_repos_ci_mapping_csv:
+        repos_ci_csv_writer.writerow(['repo_name', 'language', 'ci_services_count', 'ci_services_list'] + list(ci_file_paths.keys()))
+        repos_ci_csv_file.flush()
+
+    chunksize = 1000
+    row_id = -1
+    search_started = False
+    print('Waiting to reach the last repo we stopped at last run...')
+    
+    for repos_df in pd.read_csv(input_path, chunksize=chunksize):
+        for _, repo in repos_df.iterrows():
+            row_id += 1
+
+            if last_stopped_repo == '' or repo['full_name'] == last_stopped_repo: # Last repo we stopped at last run
+                search_started = True
+            
+            if not search_started:
+                continue
+
+            print(f'{row_id+1}: {repo['full_name']}')
+            ci_services_commit_counts = []
+            ci_services_list = []
+            for ci_file_path, ci_service_name in ci_file_paths.items():
+                print(f'    -> {ci_file_path} ', end='')
+                num_commits = search_repo_commits_by_ci_file_path(repo['full_name'], ci_file_path, csv_file=commits_csv_file, csv_writer=commits_csv_writer)
+                ci_services_commit_counts.append(num_commits if num_commits > 0 else '')
+                ci_services_list += [ci_service_name] if num_commits > 0 and ci_service_name not in ci_services_list else []
+                print(f'[{num_commits}]' if num_commits > 0 else '')
+            
+            if len(ci_services_list) > 0:
+                repos_ci_csv_writer.writerow([repo['full_name'], repo['language'], len(ci_services_list), ci_services_list] + ci_services_commit_counts)
+                repos_ci_csv_file.flush()
+
+

Scripts/collect_github_repos_for_SE4DE_topics.py

@@ -0,0 +1,301 @@
+import requests
+import time
+import csv
+import os
+from datetime import datetime, timedelta
+import sys
+
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+token_index = 0
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+
+def makeRequest(api_url, params):
+    global token_index
+    _ensure_auth()
+    num_tries = 0
+    max_tries = 3
+
+    headers = authorization_headers[token_index]
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print('      Max retries reached. Exiting...')
+            break
+
+        while True:
+            try:
+                response = requests.get(api_url, headers=headers, params=params, timeout=30)
+                break
+            except requests.exceptions.RequestException as e:
+                print(f'Request error: {e}. Retrying in 60 seconds...')
+                time.sleep(60)
+            except Exception as e:
+                print(f'Another request error: {e}. Retrying in 60 seconds...')
+                time.sleep(60)
+        
+        if response.status_code == 200:
+            return response.json()
+        elif response.status_code == 403 and ('message' in response.json() and 'rate limit' in response.json()['message'].lower()):
+            token_index += 1
+            if token_index < len(authorization_headers):
+                print(f"Rate limit exceeded for GitHub token index[{token_index-1}]. Proceeding with index[{token_index}].")
+                headers = authorization_headers[token_index]
+            else:
+                reset_timestamp = int(response.headers.get('X-RateLimit-Reset', time.time() + 60))
+                current_timestamp = int(time.time())
+                wait_time = reset_timestamp - current_timestamp
+                print(f'      Rate limit exceeded. Waiting for {wait_time} seconds...')
+                time.sleep(wait_time + 1)
+                token_index = 0
+        elif response.status_code == 422:
+            return {'total_count': 0}
+        else:
+            print(f'      Request failed with status code {response.status_code}. Retrying... ' + api_url)
+            time.sleep(1)
+
+def extract_fields(data):    
+    # Fields to extract
+    fields = [
+        'id', 'full_name', 'language', 'size', 'has_issues', 'open_issues_count', 'has_projects',
+        'created_at', 'updated_at', 'pushed_at', 'watchers_count', 'archived', 'disabled',
+        'allow_forking', 'forks_count', 'is_template', 'visibility', 'default_branch',
+        'stargazers_count', 'owner_type', 'license_key', 'topics', 'description'
+    ]
+
+    flattened_fields = {
+        'owner': {'type': 'owner_type'},
+        'license': {'key': 'license_key'}
+    }
+
+    extracted = {field: data.get(field, '').strip() if isinstance(data.get(field, ''), str) else data.get(field, '') for field in fields if field and field not in ['owner_type', 'license_key']}
+
+    # Flatten nested fields
+    for key, subfields in flattened_fields.items():
+        if data.get(key) is not None:
+            for subfield, flat_name in subfields.items():
+                extracted[flat_name] = data[key].get(subfield, '')
+
+    # Handle list fields like 'topics' as comma-separated strings
+    if isinstance(extracted.get('topics'), list):
+        extracted['topics'] = ', '.join(extracted['topics'])
+
+    row = [extracted.get(field, '') for field in fields]
+    return row
+
+def search_repositories_by_topic_with_date_range(query, start_date, end_date, interval_days, csv_file, csv_writer, previous_repos):
+    GITHUB_API_URL = 'https://api.github.com/search/repositories'
+    page = 1
+
+    current_repos = set()
+    while True:
+        params = {
+            'q': f'{query} created:{start_date}..{end_date}',
+            'per_page': 100,
+            'page': page,
+        }
+        data = makeRequest(GITHUB_API_URL, params)
+
+        if not data:
+            break
+
+        total_count = data.get('total_count', 0)
+
+        if total_count == 0 and page == 1:
+            print(f'Total count {total_count}. No collection for this interval.')
+            return total_count
+
+        if total_count <= 1000 and page == 1:
+            print(f'Total count {total_count}. Now collecting pages:')
+
+        if total_count > 1000 and page == 1:
+            print(f'Total count {total_count} (>1000) for interval {interval_days}')
+            return total_count
+
+        print(f'    Page {page} for query: {query} from {start_date} to {end_date}')
+        items = data.get('items', [])
+        for item in items:
+            repo_name = item.get('full_name')
+            if repo_name not in previous_repos:
+                current_repos.add(repo_name)
+                data_row = extract_fields(item)
+                csv_writer.writerow(data_row)
+                csv_file.flush()
+        
+        if len(items) < 100:
+            break
+
+        page += 1
+
+    previous_repos.clear()
+    previous_repos.update(current_repos)
+    return total_count
+
+def get_hourly_intervals(total_count):
+    num_intervals = -(-total_count // 500)
+    minutes_per_interval, extra = divmod(24 * 60, num_intervals)
+    return [minutes_per_interval + (i < extra) for i in range(num_intervals)]
+
+def split_search_by_datetime(query, start_date, end_date, interval_days, csv_file, csv_writer):
+    previous_repos = set()
+    start = datetime.strptime(start_date, '%Y-%m-%dT%H:%M:%S')
+    end = datetime.strptime(end_date, '%Y-%m-%dT%H:%M:%S')
+    original_interval = interval_days
+
+    while start < end:
+        next_end = min(start + (timedelta(days=interval_days) - timedelta(seconds=1)), end)
+        print(f'Checking repositories from {start.strftime("%Y-%m-%dT%H:%M:%S")} to {next_end.strftime("%Y-%m-%dT%H:%M:%S")}')
+        total_count = search_repositories_by_topic_with_date_range(
+                query,
+                start.strftime('%Y-%m-%dT%H:%M:%S'),
+                next_end.strftime('%Y-%m-%dT%H:%M:%S'),
+                interval_days,
+                csv_file,
+                csv_writer,
+                previous_repos
+            )
+
+        if total_count and total_count > 1000:  # If total_count exceeds 1000, reduce interval
+            reduced_interval = interval_days
+            while total_count > 1000:
+                reduced_interval = max(reduced_interval // 2, 1)
+                print(f'Reducing interval to {reduced_interval} day{'s' if reduced_interval > 1 else ''} for query: {query}')
+                next_end = min(start + (timedelta(days=reduced_interval) - timedelta(seconds=1)), end)
+                print(f'Checking repositories from {start.strftime("%Y-%m-%dT%H:%M:%S")} to {next_end.strftime("%Y-%m-%dT%H:%M:%S")}')
+                total_count = search_repositories_by_topic_with_date_range(
+                    query,
+                    start.strftime('%Y-%m-%dT%H:%M:%S'),
+                    next_end.strftime('%Y-%m-%dT%H:%M:%S'),
+                    interval_days,
+                    csv_file,
+                    csv_writer,
+                    previous_repos
+                )
+                if reduced_interval == 1:
+                    if total_count > 1000:
+                        # Split the day into multiple sub-intervals (every hour)
+                        sub_intervals = get_hourly_intervals(total_count)
+                        hour_start = start
+                        for sub_interval in sub_intervals:
+                            hour_end = hour_start + (timedelta(minutes=sub_interval) - timedelta(seconds=1))
+                            print(f'Checking repositories every {sub_interval/60} hours: from {hour_start.strftime("%Y-%m-%dT%H:%M:%S")} to {hour_end.strftime("%Y-%m-%dT%H:%M:%S")}')
+                            total_count = search_repositories_by_topic_with_date_range(
+                                query,
+                                hour_start.strftime('%Y-%m-%dT%H:%M:%S'),
+                                hour_end.strftime('%Y-%m-%dT%H:%M:%S'),
+                                interval_days,
+                                csv_file,
+                                csv_writer,
+                                previous_repos
+                            )
+                            hour_start = hour_end + timedelta(seconds=1)
+
+        # Restore the original interval for the next iteration
+        interval_days = original_interval
+        start = next_end + timedelta(seconds=1)
+
+def collect_repos_for_all_topics(data_path, search_criteria, start_year, end_year, interval_days):
+    for criterion, criterion_values in search_criteria.items():
+        for criterion_value in criterion_values:
+            query = f'{criterion}:{criterion_value} stars:>=5 fork:false archived:false'
+
+            output_file_name = f'{data_path}/{criterion}_{criterion_value}_{csv_file_suffix}'
+            csv_output_file_path = output_file_name + '.csv'
+            first_time_csv = not os.path.exists(csv_output_file_path)
+            csv_file = open(csv_output_file_path, 'a', newline='', encoding='utf-8')
+            csv_writer = csv.writer(csv_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
+            if first_time_csv:
+                csv_writer.writerow(['id', 'full_name', 'language', 'size', 'has_issues', 'open_issues_count', 'has_projects', 'created_at', 'updated_at', 'pushed_at', 'watchers_count', 'archived', 'disabled', 'allow_forking', 'forks_count', 'is_template', 'visibility', 'default_branch', 'stargazers_count', 'owner_type', 'license_key', 'topics', 'description'])
+
+            print(f'Starting search for {criterion} "{criterion_value}" from {start_year} to {end_year - 1}.')
+            for year in range(start_year, end_year):
+                year_start_date = f'{year}-01-01T00:00:00'
+                year_end_date = f'{year}-04-30T23:59:59' if year == 2026 else f'{year}-12-31T23:59:59'
+
+                split_search_by_datetime(
+                    query,
+                    year_start_date,
+                    year_end_date,
+                    interval_days=interval_days,
+                    csv_file=csv_file,
+                    csv_writer=csv_writer
+                )
+            csv_file.close()
+            print(f'Finished search for {criterion} "{criterion_value}". Results saved to {csv_output_file_path}.')
+
+def combine_csv_files(input_folder, output_file, deduplicate_by='full_name'):
+    """
+    Combine all CSV files in a folder into one CSV file.
+
+    Args:
+        input_folder (str): Folder containing CSV files
+        output_file (str): Output combined CSV file
+        deduplicate_by (str): Column used for deduplication
+    """
+
+    combined_rows = []
+    seen = set()
+    header = None
+
+    csv_files = [f for f in os.listdir(input_folder) if f.endswith('.csv')]
+
+    print(f'\nFound {len(csv_files)} CSV files to combine.')
+
+    for file_name in csv_files:
+        file_path = os.path.join(input_folder, file_name)
+
+        print(f'Reading: {file_name}')
+
+        with open(file_path, 'r', encoding='utf-8') as csv_file:
+            reader = csv.DictReader(csv_file)
+
+            # Save header once
+            if header is None:
+                header = reader.fieldnames
+
+            for row in reader:
+                unique_value = row.get(deduplicate_by)
+
+                if unique_value not in seen:
+                    seen.add(unique_value)
+                    combined_rows.append(row)
+
+    # Write combined file
+    with open(output_file, 'w', newline='', encoding='utf-8') as out_file:
+        writer = csv.DictWriter(out_file, fieldnames=header)
+        writer.writeheader()
+        writer.writerows(combined_rows)
+
+    print(f'\nCombined CSV saved to: {output_file}')
+    print(f'Total unique repositories: {len(combined_rows)}')
+    
+if __name__ == '__main__':
+    # Define your search criteria here
+    search_criteria = {
+        'topic': ['etl', 'etl-pipeline', 'etl-framework', 'elt', 'data-engineering', 'data-engineering-pipeline', 'data-integration', 'airflow', 'data-pipeline', 'data-pipelines', 'data-orchestrator', 'workflow-orchestration'], # Add more topics as needed 
+    }
+
+    data_path = '../Data'
+    if not os.path.exists(data_path):
+        os.mkdir(data_path)
+
+    start_year = 2008
+    end_year   = 2026
+    interval_days = 128 # Starting with 128 days, adjust if needed
+    csv_file_suffix = '2008-01-01_2026-04-30'
+    
+    # Start the collection for all topics
+    collect_repos_for_all_topics(data_path, search_criteria, start_year, end_year, interval_days)
+
+    # Combine all generated CSV files
+    combine_csv_files(data_path, f'{data_path}/all_DE_repositories.csv', deduplicate_by='full_name')

Scripts/collect_pipeline_artifacts.py

@@ -0,0 +1,667 @@
+#!/usr/bin/env python3
+"""
+collect_pipeline_artifacts.py
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Discovers and parses data-engineering pipeline artifact files for DEPosit
+repositories listed in Data/all_DE_repositories.csv (or a --repos subset).
+
+Usage
+-----
+    python collect_pipeline_artifacts.py \\
+        --token <GITHUB_PAT> \\
+        [--db Data/DE_pipeline_artifacts.db] \\
+        [--repos-csv Data/all_DE_repositories.csv] \\
+        [--repos owner/repo ...]              # optional subset
+        [--fresh]                             # reprocess all repos from scratch
+        [--workers 1]
+
+Set GITHUB_TOKEN_SE4DE (or use --token / .env); see github_tokens.py and .env.example.
+
+Pipeline
+--------
+For each repository:
+1. Fetch the full git tree (one API call via /git/trees?recursive=1).
+2. Filter blob paths against the artifact-type patterns in pipeline_parsers.
+3. Confirm ambiguous path matches with content-level signals.
+4. Fetch file content (base64-decoded from the Blobs API).
+5. Route to the appropriate parser and insert features into SQLite.
+6. Mirror each finished repository to CSV files under Data/pipeline_artifacts/.
+
+Rate-limit budget
+-----------------
+- /git/trees: 1 call per repo.
+- /git/blobs: 1 call per matched file.
+- GitHub authenticated REST API: 5,000 req/hr.
+The script sleeps when the remaining budget falls below a configurable
+threshold and retries after the reset window.
+"""
+
+import argparse
+import base64
+import csv
+import logging
+import os
+import re
+import sqlite3
+import sys
+import threading
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+
+import requests
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+ROOT_DIR = SCRIPT_DIR.parent
+DEFAULT_DB = ROOT_DIR / "Data" / "DE_pipeline_artifacts.db"
+DEFAULT_REPOS_CSV = ROOT_DIR / "Data" / "filtered_DE_repositories.csv"
+DEFAULT_CSV_DIR = ROOT_DIR / "Data" / "pipeline_artifacts"
+
+# SQLite table -> CSV filename (one file per feature table)
+CSV_EXPORT_TABLES: dict[str, str] = {
+    "pipeline_files": "DE_pipeline_files.csv",
+    "airflow_dag_features": "DE_pipeline_airflow_dag_features.csv",
+    "dbt_model_features": "DE_pipeline_dbt_model_features.csv",
+    "dbt_project_summary": "DE_pipeline_dbt_project_summary.csv",
+    "prefect_flow_features": "DE_pipeline_prefect_flow_features.csv",
+    "dagster_features": "DE_pipeline_dagster_features.csv",
+    "luigi_task_features": "DE_pipeline_luigi_task_features.csv",
+    "kedro_pipeline_features": "DE_pipeline_kedro_pipeline_features.csv",
+    "beam_pipeline_features": "DE_pipeline_beam_pipeline_features.csv",
+    "dlt_features": "DE_pipeline_dlt_features.csv",
+}
+
+# ── Local parsers ─────────────────────────────────────────────────────────────
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from pipeline_parsers import ARTIFACT_PATTERNS, CONTENT_SIGNALS
+from pipeline_parsers.airflow_parser  import extract as extract_airflow
+from pipeline_parsers.dbt_parser      import (extract_model as extract_dbt_model,
+                                               extract_project as extract_dbt_project,
+                                               extract_schema as extract_dbt_schema)
+from pipeline_parsers.prefect_parser  import extract as extract_prefect
+from pipeline_parsers.dagster_parser  import extract as extract_dagster
+from pipeline_parsers.other_parsers   import (extract_luigi, extract_kedro,
+                                               extract_kedro_catalog,
+                                               extract_beam, extract_dlt)
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s %(levelname)-8s %(message)s",
+    datefmt="%H:%M:%S",
+)
+log = logging.getLogger(__name__)
+
+# ── Constants ─────────────────────────────────────────────────────────────────
+_MAX_FILE_BYTES = 500_000  # skip files larger than this (likely generated)
+_MAX_FILES_PER_REPO = 2_000  # guard against repos with enormous dags/ dirs
+
+# Pre-compile all path patterns
+_COMPILED_PATTERNS: dict[str, list[re.Pattern]] = {
+    atype: [re.compile(p) for p in pats]
+    for atype, pats in ARTIFACT_PATTERNS.items()
+}
+
+
+# ── GitHub API helpers ────────────────────────────────────────────────────────
+from github_api import GITHUB_API, GitHubSession  # noqa: E402
+from github_tokens import add_github_token_args, resolve_token  # noqa: E402
+
+
+def _fetch_tree(session: GitHubSession, owner: str, repo: str
+                ) -> tuple[list[dict] | None, str]:
+    """Return (blob entries, tree_status) from the default branch recursive tree."""
+    url = f"{GITHUB_API}/repos/{owner}/{repo}/git/trees/HEAD?recursive=1"
+    resp = session.get(url)
+    if resp.status_code == 404:
+        log.warning("%s/%s: 404 on tree fetch", owner, repo)
+        return None, "404"
+    if resp.status_code == 409:
+        log.warning("%s/%s: empty repo", owner, repo)
+        return None, "empty"
+    if resp.status_code != 200:
+        return None, f"http_{resp.status_code}"
+    data = resp.json()
+    status = "truncated" if data.get("truncated") else "ok"
+    if status == "truncated":
+        log.warning("%s/%s: tree truncated (very large repo)", owner, repo)
+    blobs = [e for e in data.get("tree", []) if e.get("type") == "blob"]
+    return blobs, status
+
+
+def _fetch_blob(session: GitHubSession, owner: str, repo: str,
+                sha: str) -> str | None:
+    """Return decoded text content of a git blob, or None on failure."""
+    url = f"{GITHUB_API}/repos/{owner}/{repo}/git/blobs/{sha}"
+    resp = session.get(url)
+    if resp.status_code != 200:
+        return None
+    data = resp.json()
+    if data.get("encoding") != "base64":
+        return None
+    try:
+        return base64.b64decode(data["content"]).decode("utf-8", errors="replace")
+    except Exception:
+        return None
+
+
+# ── Artifact type detection ───────────────────────────────────────────────────
+
+def _classify_path(file_path: str) -> str | None:
+    """Return the artifact type for a file path, or None if no match."""
+    for atype, patterns in _COMPILED_PATTERNS.items():
+        for pat in patterns:
+            if pat.search(file_path):
+                return atype
+    return None
+
+
+def _confirm_with_content(artifact_type: str, raw_bytes: bytes) -> bool:
+    """
+    For path-ambiguous types, verify that the file content contains at
+    least one expected signal.  Types with an empty signal list always pass.
+    """
+    signals = CONTENT_SIGNALS.get(artifact_type, [])
+    if not signals:
+        return True
+    return any(sig in raw_bytes for sig in signals)
+
+
+# ── SQLite helpers ────────────────────────────────────────────────────────────
+
+def load_repos_from_csv(
+    csv_path: Path,
+    subset: list[str] | None = None,
+    *,
+    include_archived: bool = False,
+) -> list[str]:
+    """
+    Load owner/repo names from all_DE_repositories.csv.
+
+    Expects columns: full_name (required), archived, disabled (optional booleans).
+    By default skips archived/disabled rows; deduplicates by full_name.
+    """
+    if not csv_path.is_file():
+        raise FileNotFoundError(f"Repository list not found: {csv_path}")
+
+    def _is_true(value: str | None) -> bool:
+        return (value or "").strip().lower() in ("true", "1", "yes")
+
+    seen: set[str] = set()
+    repos: list[str] = []
+    with open(csv_path, encoding="utf-8", newline="") as f:
+        reader = csv.DictReader(f)
+        if not reader.fieldnames or "full_name" not in reader.fieldnames:
+            raise ValueError(f"{csv_path} must contain a full_name column")
+        for row in reader:
+            name = (row.get("full_name") or "").strip()
+            if not name or name in seen:
+                continue
+            if "/" not in name or name.count("/") != 1:
+                log.warning("Skipping invalid full_name: %r", name)
+                continue
+            if not include_archived and (
+                _is_true(row.get("archived")) or _is_true(row.get("disabled"))
+            ):
+                continue
+            seen.add(name)
+            repos.append(name)
+
+    repos.sort()
+    if subset:
+        allowed = {
+            r.strip()
+            for r in subset
+            if r.strip() and "/" in r and r.count("/") == 1
+        }
+        repos = [r for r in repos if r in allowed]
+        extra = sorted(allowed - set(repos))
+        if extra:
+            log.info("Adding %d repo(s) from --repos not in CSV: %s",
+                     len(extra), ", ".join(extra[:5]))
+            repos = sorted(set(repos) | set(extra))
+    return repos
+
+
+def _migrate_db(conn: sqlite3.Connection) -> None:
+    """Apply additive schema changes to existing DE_pipeline_artifacts.db files."""
+    cols = {
+        row[1]
+        for row in conn.execute("PRAGMA table_info(dbt_model_features)").fetchall()
+    }
+    if cols and "has_tests" not in cols:
+        conn.execute("ALTER TABLE dbt_model_features ADD COLUMN has_tests INTEGER")
+        log.info("Migrated dbt_model_features: added has_tests column")
+    conn.execute(
+        """
+        CREATE TABLE IF NOT EXISTS repo_scan_status (
+            repo_full_name       TEXT PRIMARY KEY,
+            artifact_file_count  INTEGER NOT NULL,
+            tree_status          TEXT,
+            scanned_at           TEXT NOT NULL
+        )
+        """
+    )
+
+
+def _mark_repo_scanned(
+    conn: sqlite3.Connection,
+    repo: str,
+    artifact_count: int,
+    tree_status: str,
+) -> None:
+    conn.execute(
+        """
+        INSERT OR REPLACE INTO repo_scan_status
+        (repo_full_name, artifact_file_count, tree_status, scanned_at)
+        VALUES (?, ?, ?, ?)
+        """,
+        (repo, artifact_count, tree_status,
+         datetime.now(timezone.utc).isoformat()),
+    )
+
+
+def _init_db(db_path: Path) -> sqlite3.Connection:
+    db_path.parent.mkdir(parents=True, exist_ok=True)
+    schema = SCRIPT_DIR / "pipeline_schema.sql"
+    conn = sqlite3.connect(str(db_path))
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode=WAL")
+    conn.execute("PRAGMA synchronous=NORMAL")
+    if schema.exists():
+        conn.executescript(schema.read_text())
+    _migrate_db(conn)
+    conn.commit()
+    return conn
+
+
+class PipelineCsvExporter:
+    """Keep per-table CSV files in sync with SQLite (one repo at a time)."""
+
+    def __init__(self, csv_dir: Path) -> None:
+        self.csv_dir = Path(csv_dir)
+        self.csv_dir.mkdir(parents=True, exist_ok=True)
+        self._lock = threading.Lock()
+        self._columns_cache: dict[str, list[str]] = {}
+
+    def reset_all(self) -> None:
+        with self._lock:
+            for filename in CSV_EXPORT_TABLES.values():
+                path = self.csv_dir / filename
+                if path.exists():
+                    path.unlink()
+
+    def _columns(self, conn: sqlite3.Connection, table: str) -> list[str]:
+        if table not in self._columns_cache:
+            rows = conn.execute(f"PRAGMA table_info({table})").fetchall()
+            self._columns_cache[table] = [
+                r[1] for r in rows if r[1] != "id"
+            ]
+        return self._columns_cache[table]
+
+    def _read_rows(self, path: Path) -> list[dict[str, str]]:
+        if not path.exists():
+            return []
+        with open(path, encoding="utf-8", newline="") as f:
+            return list(csv.DictReader(f))
+
+    def sync_repo(self, conn: sqlite3.Connection, repo: str) -> None:
+        """Replace all CSV rows for repo with current SQLite contents."""
+        with self._lock:
+            for table, filename in CSV_EXPORT_TABLES.items():
+                cols = self._columns(conn, table)
+                if not cols:
+                    continue
+                col_list = ", ".join(cols)
+                new_rows = conn.execute(
+                    f"SELECT {col_list} FROM {table} WHERE repo_full_name = ?",
+                    (repo,),
+                ).fetchall()
+                new_dicts = [dict(row) for row in new_rows]
+
+                out_path = self.csv_dir / filename
+                kept = [
+                    row for row in self._read_rows(out_path)
+                    if row.get("repo_full_name") != repo
+                ]
+                if not kept and not new_dicts and not out_path.exists():
+                    continue
+                fieldnames = list(kept[0].keys()) if kept else cols
+
+                with open(out_path, "w", encoding="utf-8", newline="") as f:
+                    writer = csv.DictWriter(f, fieldnames=fieldnames, extrasaction="ignore")
+                    writer.writeheader()
+                    for row in kept:
+                        writer.writerow(row)
+                    for row in new_dicts:
+                        writer.writerow({k: row.get(k) for k in fieldnames})
+
+
+def _already_processed(conn: sqlite3.Connection, repo: str) -> bool:
+    row = conn.execute(
+        "SELECT 1 FROM repo_scan_status WHERE repo_full_name = ? LIMIT 1",
+        (repo,),
+    ).fetchone()
+    if row is not None:
+        return True
+    # Legacy runs before repo_scan_status: treat repos with pipeline_files as done
+    return conn.execute(
+        "SELECT 1 FROM pipeline_files WHERE repo_full_name = ? LIMIT 1",
+        (repo,),
+    ).fetchone() is not None
+
+
+def _insert_file_record(conn: sqlite3.Connection, repo: str, path: str,
+                        atype: str, sha: str, size: int) -> None:
+    conn.execute(
+        """INSERT OR IGNORE INTO pipeline_files
+           (repo_full_name, file_path, artifact_type, file_sha,
+            file_size_bytes, collected_at)
+           VALUES (?, ?, ?, ?, ?, ?)""",
+        (repo, path, atype, sha, size,
+         datetime.now(timezone.utc).isoformat()),
+    )
+
+
+def _set_parse_error(conn: sqlite3.Connection, repo: str, path: str,
+                     error: str | None) -> None:
+    """parse_error lives on pipeline_files, not on per-artifact feature tables."""
+    if not error:
+        return
+    conn.execute(
+        "UPDATE pipeline_files SET parse_error = ? "
+        "WHERE repo_full_name = ? AND file_path = ?",
+        (error, repo, path),
+    )
+
+
+def _insert_features(conn: sqlite3.Connection, table: str,
+                     repo: str, path: str, features: dict) -> None:
+    parse_error = features.pop("parse_error", None)
+    features = {k: v for k, v in features.items() if v is not None}
+    if not features:
+        _set_parse_error(conn, repo, path, parse_error)
+        return
+    features["repo_full_name"] = repo
+    features["file_path"]      = path
+    cols = ", ".join(features.keys())
+    placeholders = ", ".join("?" * len(features))
+    conn.execute(
+        f"INSERT OR REPLACE INTO {table} ({cols}) VALUES ({placeholders})",
+        list(features.values()),
+    )
+    _set_parse_error(conn, repo, path, parse_error)
+
+
+# ── Per-artifact dispatch ─────────────────────────────────────────────────────
+
+def _process_file(conn: sqlite3.Connection, session: GitHubSession,
+                  owner: str, repo: str, repo_full: str,
+                  entry: dict, artifact_type: str) -> None:
+    path = entry["path"]
+    sha  = entry["sha"]
+    size = entry.get("size", 0)
+
+    if size > _MAX_FILE_BYTES:
+        log.debug("%s: %s too large (%d bytes), skipping", repo_full, path, size)
+        return
+
+    content = _fetch_blob(session, owner, repo, sha)
+    if content is None:
+        return
+
+    raw = content.encode("utf-8", errors="replace")
+    if not _confirm_with_content(artifact_type, raw):
+        return   # path matched but content signals absent
+
+    _insert_file_record(conn, repo_full, path, artifact_type, sha, size)
+
+    try:
+        if artifact_type == "airflow_dag":
+            for dag_features in extract_airflow(content, path):
+                _insert_features(conn, "airflow_dag_features",
+                                 repo_full, path, dag_features)
+
+        elif artifact_type == "dbt_model":
+            f = extract_dbt_model(content, path)
+            _insert_features(conn, "dbt_model_features", repo_full, path, f)
+
+        elif artifact_type == "dbt_schema":
+            fname = Path(path).name.lower()
+            if fname in ("dbt_project.yml", "dbt_project.yaml"):
+                f = extract_dbt_project(content, path)
+                parse_error = f.pop("parse_error", None)
+                f = {k: v for k, v in f.items() if v is not None}
+                if f:
+                    f["repo_full_name"] = repo_full
+                    cols = ", ".join(f.keys())
+                    placeholders = ", ".join("?" * len(f))
+                    conn.execute(
+                        f"INSERT OR REPLACE INTO dbt_project_summary "
+                        f"({cols}) VALUES ({placeholders})",
+                        list(f.values()),
+                    )
+                _set_parse_error(conn, repo_full, path, parse_error)
+            else:
+                # schema.yml: per-model test coverage merged into model rows
+                coverage = extract_dbt_schema(content, path)
+                for model_name, has_tests in coverage.items():
+                    updated = conn.execute(
+                        """UPDATE dbt_model_features
+                           SET has_tests = ?
+                           WHERE repo_full_name = ? AND model_name = ?""",
+                        (has_tests, repo_full, model_name),
+                    ).rowcount
+                    if updated == 0:
+                        log.debug(
+                            "%s schema.yml: no dbt_model_features row for model %s",
+                            repo_full,
+                            model_name,
+                        )
+
+        elif artifact_type == "prefect_flow":
+            f = extract_prefect(content, path)
+            _insert_features(conn, "prefect_flow_features", repo_full, path, f)
+
+        elif artifact_type == "dagster":
+            f = extract_dagster(content, path)
+            _insert_features(conn, "dagster_features", repo_full, path, f)
+
+        elif artifact_type == "luigi":
+            f = extract_luigi(content, path)
+            _insert_features(conn, "luigi_task_features", repo_full, path, f)
+
+        elif artifact_type == "kedro":
+            fname = Path(path).name.lower()
+            if "catalog" in fname and fname.endswith((".yml", ".yaml")):
+                f = extract_kedro_catalog(content, path)
+            else:
+                f = extract_kedro(content, path)
+            _insert_features(conn, "kedro_pipeline_features", repo_full, path, f)
+
+        elif artifact_type == "beam":
+            f = extract_beam(content, path)
+            _insert_features(conn, "beam_pipeline_features", repo_full, path, f)
+
+        elif artifact_type == "dlt":
+            f = extract_dlt(content, path)
+            _insert_features(conn, "dlt_features", repo_full, path, f)
+
+    except Exception as exc:  # noqa: BLE001
+        log.error("%s %s: feature extraction failed: %s", repo_full, path, exc)
+        _set_parse_error(conn, repo_full, path, str(exc))
+
+
+# ── Main collection loop ──────────────────────────────────────────────────────
+
+def collect_repo(conn: sqlite3.Connection, session: GitHubSession,
+                 repo_full: str,
+                 csv_exporter: PipelineCsvExporter | None = None,
+                 *, progress_idx: int | None = None,
+                 progress_total: int | None = None) -> None:
+    owner, repo = repo_full.split("/", 1)
+    if progress_idx is not None and progress_total is not None:
+        log.info("[%d/%d] Processing %s", progress_idx, progress_total, repo_full)
+    else:
+        log.info("Processing %s", repo_full)
+
+    blobs, tree_status = _fetch_tree(session, owner, repo)
+    if blobs is None:
+        _mark_repo_scanned(conn, repo_full, 0, tree_status)
+        conn.commit()
+        if csv_exporter is not None:
+            csv_exporter.sync_repo(conn, repo_full)
+        return
+
+    matched: list[tuple[dict, str]] = []
+    for entry in blobs:
+        atype = _classify_path(entry["path"])
+        if atype:
+            matched.append((entry, atype))
+
+    if len(matched) > _MAX_FILES_PER_REPO:
+        log.warning("%s: %d matched files, capping at %d",
+                    repo_full, len(matched), _MAX_FILES_PER_REPO)
+        matched = matched[:_MAX_FILES_PER_REPO]
+
+    if progress_idx is not None and progress_total is not None:
+        log.info("  [%d/%d] %d pipeline artifact files found",
+                 progress_idx, progress_total, len(matched))
+    else:
+        log.info("  %d pipeline artifact files found", len(matched))
+    for entry, atype in matched:
+        _process_file(conn, session, owner, repo, repo_full, entry, atype)
+
+    _mark_repo_scanned(conn, repo_full, len(matched), tree_status)
+    conn.commit()
+    if csv_exporter is not None:
+        csv_exporter.sync_repo(conn, repo_full)
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser(
+        description="Collect pipeline artifact features for DEPosit repositories."
+    )
+    ap.add_argument(
+        "--db",
+        default=str(DEFAULT_DB),
+        help=f"SQLite output database (default: {DEFAULT_DB.relative_to(ROOT_DIR)})",
+    )
+    add_github_token_args(ap)
+    ap.add_argument(
+        "--repos-csv",
+        default=str(DEFAULT_REPOS_CSV),
+        help=f"Repository cohort CSV with full_name column (default: {DEFAULT_REPOS_CSV.name})",
+    )
+    ap.add_argument(
+        "--repos",
+        nargs="*",
+        help="Optional subset of owner/repo names (must appear in --repos-csv unless given alone)",
+    )
+    ap.add_argument(
+        "--include-archived",
+        action="store_true",
+        help="Also process repositories marked archived or disabled in the CSV",
+    )
+    ap.add_argument(
+        "--fresh",
+        action="store_true",
+        help="Reprocess every repo from scratch (default: skip repos already in the DB).",
+    )
+    ap.add_argument("--workers", type=int, default=1,
+                    help="Parallel worker threads (default 1; each uses its own API session).")
+    ap.add_argument(
+        "--csv-dir",
+        default=str(DEFAULT_CSV_DIR),
+        help=f"Directory for pipeline CSV exports (default: {DEFAULT_CSV_DIR.relative_to(ROOT_DIR)})",
+    )
+    ap.add_argument(
+        "--no-csv",
+        action="store_true",
+        help="Skip CSV export (SQLite only).",
+    )
+    args = ap.parse_args()
+
+    token = resolve_token(args.token, args.tokens)
+    if not token:
+        ap.error(
+            "GitHub token required: pass --token, set GITHUB_TOKEN_SE4DE, "
+            "or copy .env.example to .env"
+        )
+
+    db_path = Path(args.db)
+    csv_path = Path(args.repos_csv)
+
+    conn = _init_db(db_path)
+    repos = load_repos_from_csv(
+        csv_path,
+        subset=args.repos or None,
+        include_archived=args.include_archived,
+    )
+
+    if not repos:
+        ap.error(f"No repositories to process from {csv_path}")
+
+    csv_exporter = None
+    if not args.no_csv:
+        csv_exporter = PipelineCsvExporter(Path(args.csv_dir))
+        if args.fresh:
+            csv_exporter.reset_all()
+            log.info("CSV export: %s (cleared for --fresh)", args.csv_dir)
+        else:
+            log.info("CSV export: %s (synced per repo)", args.csv_dir)
+
+    log.info("Repository list: %s (%d repos)", csv_path, len(repos))
+    log.info("Output database: %s", db_path)
+    total = len(repos)
+    log.info("Total repos in queue: %d", total)
+
+    if args.workers > 1:
+        from concurrent.futures import ThreadPoolExecutor
+
+        def _worker(item: tuple[int, str]) -> None:
+            idx, repo = item
+            c = sqlite3.connect(str(db_path))
+            c.row_factory = sqlite3.Row
+            c.execute("PRAGMA journal_mode=WAL")
+            if not args.fresh and _already_processed(c, repo):
+                log.info("[%d/%d] Skipping %s (already processed)", idx, total, repo)
+                c.close()
+                return
+            session = GitHubSession(token)
+            try:
+                collect_repo(
+                    c, session, repo, csv_exporter,
+                    progress_idx=idx, progress_total=total,
+                )
+            except requests.RequestException as exc:
+                log.error("[%d/%d] %s: network/API error (retry on next run): %s",
+                          idx, total, repo, exc)
+            finally:
+                c.close()
+
+        work_items = list(enumerate(repos, 1))
+        with ThreadPoolExecutor(max_workers=args.workers) as pool:
+            pool.map(_worker, work_items)
+    else:
+        session = GitHubSession(token)
+        for idx, repo in enumerate(repos, 1):
+            if not args.fresh and _already_processed(conn, repo):
+                log.info("[%d/%d] Skipping %s (already processed)", idx, total, repo)
+                continue
+            try:
+                collect_repo(
+                    conn, session, repo, csv_exporter,
+                    progress_idx=idx, progress_total=total,
+                )
+            except requests.RequestException as exc:
+                log.error("[%d/%d] %s: network/API error (retry on next run): %s",
+                          idx, total, repo, exc)
+                conn.rollback()
+
+    conn.close()
+    log.info("Done.")
+
+
+if __name__ == "__main__":
+    main()

Scripts/compute_interactions_for_SE4DE_repos.py

@@ -0,0 +1,236 @@
+"""
+compute_interactions_for_SE4DE_repos.py
+-----------------------------------------
+Computes the five interaction types from Table 4 of Das et al. (EASE 2022)
+per repo, broken down by artifact type (commits / issues / pull_requests).
+
+Interaction types:
+  Contribution  — author != committer on a commit
+  Maintenance   — non-creator merged/closed an artifact
+  Process       — creator interacted with a maintainer (proxy: artifact
+                  closed/merged by someone else)
+  Review        — commenter != creator (proxy: review events + inline comments)
+  Discussion    — two non-creators commented on the same artifact (proxy:
+                  review activity on PRs with >1 distinct reviewer)
+
+Lookup dicts are built from the smaller files (pr_reviews, issue_closers).
+The larger files (commits, prs, issues) are streamed one row at a time.
+
+Reads:
+  ../Data/DE_all_commits_details.csv
+  ../Data/DE_all_pr_details.csv
+  ../Data/DE_all_pr_reviews_graphql.csv
+  ../Data/DE_all_issue_details.csv
+  ../Data/DE_all_issue_closers.csv
+
+Writes:
+  ../Data/DE_repo_interactions.csv
+"""
+
+import csv
+import sys
+from collections import defaultdict
+
+
+def set_csv_field_size_limit():
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+
+
+def count_data_rows(csv_path):
+    """Count logical CSV records, not physical newlines."""
+    set_csv_field_size_limit()
+    with open(csv_path, 'r', encoding='utf-8', newline='') as f:
+        return sum(1 for _ in csv.reader(f)) - 1
+
+
+def load_merger_lookup(pr_reviews_csv):
+    """
+    Build (full_name, pr_number) -> (merger_login, num_reviewers,
+    num_review_events) from pr_reviews. Loaded fully — smaller file.
+    """
+    set_csv_field_size_limit()
+    lookup = {}
+    with open(pr_reviews_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                pr_number = int(row['pr_number'])
+            except (ValueError, KeyError):
+                continue
+            try:
+                num_reviewers   = int(row.get('num_reviewers', 0) or 0)
+                num_review_events = int(row.get('num_review_events', 0) or 0)
+            except ValueError:
+                num_reviewers, num_review_events = 0, 0
+            lookup[(full_name, pr_number)] = (
+                row.get('merger_login', '').strip(),
+                num_reviewers,
+                num_review_events,
+            )
+    return lookup
+
+
+def load_closer_lookup(issue_closers_csv):
+    """
+    Build (full_name, issue_number) -> (opener_login, closer_login).
+    Loaded fully — lightweight columns.
+    """
+    set_csv_field_size_limit()
+    lookup = {}
+    with open(issue_closers_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                issue_number = int(row['issue_number'])
+            except (ValueError, KeyError):
+                continue
+            lookup[(full_name, issue_number)] = (
+                row.get('opener_login', '').strip(),
+                row.get('closer_login', '').strip(),
+            )
+    return lookup
+
+
+def iter_csv(csv_path):
+    """Stream rows from a CSV file one at a time."""
+    set_csv_field_size_limit()
+    with open(csv_path, newline='', encoding='utf-8') as f:
+        yield from csv.DictReader(f)
+
+
+if __name__ == '__main__':
+    commits_csv    = '../Data/DE_all_commits_details.csv'
+    prs_csv        = '../Data/DE_all_pr_details.csv'
+    pr_reviews_csv = '../Data/DE_all_pr_reviews_graphql.csv'
+    issues_csv     = '../Data/DE_all_issue_details.csv'
+    closers_csv    = '../Data/DE_all_issue_closers.csv'
+    output_csv     = '../Data/DE_repo_interactions.csv'
+
+    print('Building merger lookup from pr_reviews ...')
+    merger_lookup = load_merger_lookup(pr_reviews_csv)
+    print(f'  {len(merger_lookup):,} PR merger entries loaded.')
+
+    print('Building closer lookup from issue_closers ...')
+    closer_lookup = load_closer_lookup(closers_csv)
+    print(f'  {len(closer_lookup):,} issue closer entries loaded.')
+
+    # counts[full_name][interaction_type] = int
+    counts = defaultdict(lambda: defaultdict(int))
+
+    # ------------------------------------------------------------------ Commits
+    print('Counting rows in commits file...')
+    total_commits = count_data_rows(commits_csv)
+    print(f'  Streaming {total_commits:,} commit rows ...')
+
+    for idx, row in enumerate(iter_csv(commits_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_commits:,} commits processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        author    = row.get('author_login', '').strip()
+        committer = row.get('committer_login', '').strip()
+
+        # Contribution: someone other than author committed the work
+        if author and committer and author != committer:
+            counts[full_name]['contribution_commits'] += 1
+
+    # ------------------------------------------------------------------ PRs
+    print('Counting rows in pr_details file...')
+    total_prs = count_data_rows(prs_csv)
+    print(f'  Streaming {total_prs:,} PR rows ...')
+
+    for idx, row in enumerate(iter_csv(prs_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_prs:,} PRs processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        try:
+            pr_number = int(row.get('pr_number', ''))
+        except ValueError:
+            continue
+        author    = row.get('user_login', '').strip()
+        merged_at = row.get('merged_at', '').strip()
+        is_merged = bool(merged_at)
+
+        merger, num_reviewers, num_review_events = \
+            merger_lookup.get((full_name, pr_number), ('', 0, 0))
+
+        if is_merged and merger and author and merger != author:
+            # Maintenance: non-author merged the PR
+            counts[full_name]['maintenance_prs'] += 1
+            # Process: author interacted with the maintainer who merged it
+            counts[full_name]['process_prs'] += 1
+
+        # Review: any review activity on the PR
+        counts[full_name]['review_prs'] += num_review_events
+
+        # Discussion: review activity when >1 distinct reviewer
+        if num_reviewers >= 2:
+            counts[full_name]['discussion_prs'] += num_review_events
+
+    # ------------------------------------------------------------------ Issues
+    print('Counting rows in issue_details file...')
+    total_issues = count_data_rows(issues_csv)
+    print(f'  Streaming {total_issues:,} issue rows ...')
+
+    for idx, row in enumerate(iter_csv(issues_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_issues:,} issues processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        try:
+            issue_number = int(row.get('issue_number', ''))
+        except ValueError:
+            continue
+        opener = row.get('user_login', '').strip()
+        state  = row.get('state', '').strip()
+        try:
+            comment_count = int(row.get('comments', 0) or 0)
+        except ValueError:
+            comment_count = 0
+
+        _, closer = closer_lookup.get((full_name, issue_number), ('', ''))
+
+        if state == 'closed' and closer and opener and closer != opener:
+            # Maintenance: non-creator closed the issue
+            counts[full_name]['maintenance_issues'] += 1
+            # Process: creator interacted with the maintainer who closed it
+            counts[full_name]['process_issues'] += 1
+
+        # Review proxy: total comments on issues
+        counts[full_name]['review_issues'] += comment_count
+
+        # Discussion proxy: comments on issues involving a non-creator
+        if closer and closer != opener and comment_count > 0:
+            counts[full_name]['discussion_issues'] += comment_count
+
+    # ------------------------------------------------------------------ Write
+    all_repos = set(counts.keys())
+    print(f'Writing {len(all_repos):,} repo records to {output_csv} ...')
+
+    fieldnames = [
+        'full_name',
+        'contribution_commits',
+        'maintenance_issues', 'process_issues', 'review_issues', 'discussion_issues',
+        'maintenance_prs',    'process_prs',    'review_prs',    'discussion_prs',
+    ]
+
+    with open(output_csv, 'w', newline='', encoding='utf-8') as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        writer.writeheader()
+        for fn in sorted(all_repos):
+            c = counts[fn]
+            writer.writerow({
+                'full_name':            fn,
+                'contribution_commits': c['contribution_commits'],
+                'maintenance_issues':   c['maintenance_issues'],
+                'process_issues':       c['process_issues'],
+                'review_issues':        c['review_issues'],
+                'discussion_issues':    c['discussion_issues'],
+                'maintenance_prs':      c['maintenance_prs'],
+                'process_prs':          c['process_prs'],
+                'review_prs':           c['review_prs'],
+                'discussion_prs':       c['discussion_prs'],
+            })
+
+    print(f'Done. Output: {output_csv}')

Scripts/compute_user_autonomy_for_SE4DE_repos.py

@@ -0,0 +1,244 @@
+"""
+compute_user_autonomy_for_SE4DE_repos.py
+-----------------------------------------
+Classifies each (full_name, user_login) pair as:
+  Maintainer   — merged/closed at least one artifact opened by another user
+  Autonomous   — self-committed majority of commits AND/OR self-merged majority of PRs
+  Dependent    — others committed/merged majority of their work
+
+Mirrors Table 5 of Das et al. (EASE 2022).
+
+Lookup dicts are built from the smaller files (pr_reviews, issue_closers).
+The larger files (commits, prs, issues) are streamed one row at a time.
+
+Reads:
+  ../Data/DE_all_commits_details.csv
+  ../Data/DE_all_pr_details.csv
+  ../Data/DE_all_pr_reviews_graphql.csv
+  ../Data/DE_all_issue_details.csv
+  ../Data/DE_all_issue_closers.csv
+
+Writes:
+  ../Data/DE_user_autonomy.csv
+"""
+
+import csv
+import sys
+from collections import defaultdict
+
+MAJORITY = 0.5
+
+
+def set_csv_field_size_limit():
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+
+
+def count_data_rows(csv_path):
+    """Count logical CSV records, not physical newlines."""
+    set_csv_field_size_limit()
+    with open(csv_path, 'r', encoding='utf-8', newline='') as f:
+        return sum(1 for _ in csv.reader(f)) - 1
+
+
+def load_merger_lookup(pr_reviews_csv):
+    """
+    Build (full_name, pr_number) -> merger_login from pr_reviews.
+    Loaded fully — smaller than the main PR file.
+    """
+    set_csv_field_size_limit()
+    lookup = {}
+    with open(pr_reviews_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                pr_number = int(row['pr_number'])
+            except (ValueError, KeyError):
+                continue
+            lookup[(full_name, pr_number)] = row.get('merger_login', '').strip()
+    return lookup
+
+
+def load_closer_lookup(issue_closers_csv):
+    """
+    Build (full_name, issue_number) -> (opener_login, closer_login) from issue_closers.
+    Loaded fully — same row count as issues but lightweight columns.
+    """
+    set_csv_field_size_limit()
+    lookup = {}
+    with open(issue_closers_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                issue_number = int(row['issue_number'])
+            except (ValueError, KeyError):
+                continue
+            lookup[(full_name, issue_number)] = (
+                row.get('opener_login', '').strip(),
+                row.get('closer_login', '').strip(),
+            )
+    return lookup
+
+
+def iter_csv(csv_path):
+    """Stream rows from a CSV file one at a time."""
+    set_csv_field_size_limit()
+    with open(csv_path, newline='', encoding='utf-8') as f:
+        yield from csv.DictReader(f)
+
+
+def classify_user(s):
+    """
+    s: defaultdict(int) of stats for one (full_name, user_login) pair.
+
+    Maintainer:  closed/merged at least one artifact created by someone else.
+    Autonomous:  self-committed majority of own commits AND/OR
+                 self-merged majority of own PRs.
+    Dependent:   others committed/merged majority of their work.
+    Unknown:     no meaningful activity recorded.
+    """
+    maintainer_actions = (
+        s['prs_merged_by_user']
+        + s['issues_closed_by_user']
+        + s['commits_committed_others']
+    )
+    if maintainer_actions > 0:
+        return 'Maintainer'
+
+    commits_authored = s['commits_authored']
+    commits_self     = s['commits_self_committed']
+    prs_opened       = s['prs_opened']
+    prs_self_merged  = s['prs_self_merged']
+
+    commit_auto = commits_authored > 0 and (commits_self / commits_authored) > MAJORITY
+    pr_auto     = prs_opened > 0 and (prs_self_merged / prs_opened) > MAJORITY
+
+    if commit_auto or pr_auto:
+        return 'Autonomous'
+    if commits_authored > 0 or prs_opened > 0:
+        return 'Dependent'
+    return 'Unknown'
+
+
+if __name__ == '__main__':
+    commits_csv      = '../Data/DE_all_commits_details.csv'
+    prs_csv          = '../Data/DE_all_pr_details.csv'
+    pr_reviews_csv   = '../Data/DE_all_pr_reviews_graphql.csv'
+    issues_csv       = '../Data/DE_all_issue_details.csv'
+    closers_csv      = '../Data/DE_all_issue_closers.csv'
+    output_csv       = '../Data/DE_user_autonomy.csv'
+
+    print('Building merger lookup from pr_reviews ...')
+    merger_lookup = load_merger_lookup(pr_reviews_csv)
+    print(f'  {len(merger_lookup):,} PR merger entries loaded.')
+
+    print('Building closer lookup from issue_closers ...')
+    closer_lookup = load_closer_lookup(closers_csv)
+    print(f'  {len(closer_lookup):,} issue closer entries loaded.')
+
+    # stats[(full_name, user_login)] = defaultdict(int)
+    stats = defaultdict(lambda: defaultdict(int))
+
+    # ------------------------------------------------------------------ Commits
+    print('Counting rows in commits file...')
+    total_commits = count_data_rows(commits_csv)
+    print(f'  Streaming {total_commits:,} commit rows ...')
+
+    for idx, row in enumerate(iter_csv(commits_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_commits:,} commits processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        author    = row.get('author_login', '').strip()
+        committer = row.get('committer_login', '').strip()
+
+        if author:
+            stats[(full_name, author)]['commits_authored'] += 1
+            if author == committer:
+                stats[(full_name, author)]['commits_self_committed'] += 1
+        if committer and committer != author and author:
+            stats[(full_name, committer)]['commits_committed_others'] += 1
+
+    # ------------------------------------------------------------------ PRs
+    print('Counting rows in pr_details file...')
+    total_prs = count_data_rows(prs_csv)
+    print(f'  Streaming {total_prs:,} PR rows ...')
+
+    for idx, row in enumerate(iter_csv(prs_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_prs:,} PRs processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        try:
+            pr_number = int(row.get('pr_number', ''))
+        except ValueError:
+            continue
+        author    = row.get('user_login', '').strip()
+        merged_at = row.get('merged_at', '').strip()
+        is_merged = bool(merged_at)
+
+        merger = merger_lookup.get((full_name, pr_number), '')
+
+        if author:
+            stats[(full_name, author)]['prs_opened'] += 1
+            if is_merged and merger == author:
+                stats[(full_name, author)]['prs_self_merged'] += 1
+        if merger and is_merged and merger != author:
+            stats[(full_name, merger)]['prs_merged_by_user'] += 1
+
+    # ------------------------------------------------------------------ Issues
+    print('Counting rows in issue_details file...')
+    total_issues = count_data_rows(issues_csv)
+    print(f'  Streaming {total_issues:,} issue rows ...')
+
+    for idx, row in enumerate(iter_csv(issues_csv), 1):
+        if idx % 100_000 == 0:
+            print(f'    {idx:,}/{total_issues:,} issues processed ...')
+
+        full_name = row.get('full_name', '').strip()
+        try:
+            issue_number = int(row.get('issue_number', ''))
+        except ValueError:
+            continue
+        opener = row.get('user_login', '').strip()
+        state  = row.get('state', '').strip()
+
+        if opener:
+            stats[(full_name, opener)]['issues_opened'] += 1
+
+        if state == 'closed':
+            _, closer = closer_lookup.get((full_name, issue_number), ('', ''))
+            if closer and closer != opener:
+                stats[(full_name, closer)]['issues_closed_by_user'] += 1
+
+    # ------------------------------------------------------------------ Write
+    print(f'Writing {len(stats):,} user-repo records to {output_csv} ...')
+
+    fieldnames = [
+        'full_name', 'user_login',
+        'commits_authored', 'commits_self_committed',
+        'prs_opened', 'prs_self_merged',
+        'prs_merged_by_user',
+        'issues_opened', 'issues_closed_by_user',
+        'commits_committed_others',
+        'autonomy_class',
+    ]
+
+    with open(output_csv, 'w', newline='', encoding='utf-8') as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        writer.writeheader()
+        for (full_name, user_login), s in sorted(stats.items()):
+            writer.writerow({
+                'full_name':                full_name,
+                'user_login':               user_login,
+                'commits_authored':         s['commits_authored'],
+                'commits_self_committed':   s['commits_self_committed'],
+                'prs_opened':               s['prs_opened'],
+                'prs_self_merged':          s['prs_self_merged'],
+                'prs_merged_by_user':       s['prs_merged_by_user'],
+                'issues_opened':            s['issues_opened'],
+                'issues_closed_by_user':    s['issues_closed_by_user'],
+                'commits_committed_others': s['commits_committed_others'],
+                'autonomy_class':           classify_user(s),
+            })
+
+    print(f'Done. Output: {output_csv}')

Scripts/get_gha_workflow_runs_for_SE4DE_repos.py

@@ -0,0 +1,66 @@
+import argparse
+import time
+from pathlib import Path
+
+import pandas as pd
+import requests
+
+from github_tokens import add_github_token_args, primary_token
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+DATA_DIR = SCRIPT_DIR.parent / "Data"
+OUTPUT_FILE = DATA_DIR / "DE_repo_gha_runs_counts.csv"
+COHORT_CSV = DATA_DIR / "filtered_DE_repositories.csv"
+
+
+def count_gha_runs(owner: str, repo: str, token: str) -> int | None:
+    headers = {"Authorization": f"Bearer {token}"}
+    url = f"https://api.github.com/repos/{owner}/{repo}/actions/runs"
+    params = {"per_page": 1}
+    try:
+        response = requests.get(url, headers=headers, params=params, timeout=30)
+        if response.status_code != 200:
+            return None
+        return response.json().get("total_count", 0)
+    except requests.RequestException as exc:
+        print(f"Error for {owner}/{repo}: {exc}")
+        return None
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser(description="Count GitHub Actions runs per repository.")
+    add_github_token_args(ap)
+    args = ap.parse_args()
+    token = primary_token(args.token, args.tokens)
+
+    df = pd.read_csv(COHORT_CSV)
+    processed: set[str] = set()
+    if OUTPUT_FILE.is_file():
+        processed = set(pd.read_csv(OUTPUT_FILE)["full_name"])
+
+    for idx, row in df.iterrows():
+        repo_name = row["full_name"]
+        if repo_name in processed:
+            print(f"[{idx + 1}/{len(df)}] Skipping {repo_name}")
+            continue
+
+        owner, repo = repo_name.split("/", 1)
+        gha_count = count_gha_runs(owner, repo, token)
+        print(f"[{idx + 1}/{len(df)}] {repo_name} GHA: {gha_count}")
+
+        result = pd.DataFrame(
+            [{"full_name": repo_name, "gha_run_count": gha_count, "travis_build_count": None}]
+        )
+        result.to_csv(
+            OUTPUT_FILE,
+            mode="a",
+            header=not OUTPUT_FILE.exists(),
+            index=False,
+        )
+        time.sleep(1)
+
+    print("Done!")
+
+
+if __name__ == "__main__":
+    main()

Scripts/get_issue_closers_for_SE4DE_repos.py

@@ -0,0 +1,229 @@
+"""
+get_issue_closers_for_SE4DE_repos.py
+--------------------------------------
+For each closed issue in DE_all_issue_details.csv, fetches the login
+of whoever fired the 'closed' event by paginating issue timeline events.
+
+Needed to distinguish self-closed vs. closed-by-another for the
+maintenance/process interaction types and autonomy classification.
+
+No batching possible via REST (one API call per issue event page),
+so issues are processed one at a time with the same streaming/resume
+pattern as get_pr_reviews_graphql_for_SE4DE_repos.py.
+
+Reads:  ../Data/DE_all_issue_details.csv
+Writes: ../Data/DE_all_issue_closers.csv
+"""
+
+import os
+import csv
+import sys
+import time
+import requests
+
+GITHUB_REST_URL = 'https://api.github.com'
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+token_index = 0          # current position in round-robin
+rate_limit_reset = {}    # token_index -> unix timestamp when it becomes available again
+
+
+def get_next_token():
+    """
+    Round-robin through tokens, skipping any that are currently rate-limited.
+    If all tokens are rate-limited, sleeps until the earliest one resets.
+    """
+    global token_index
+    _ensure_auth()
+    n = len(authorization_headers)
+
+    while True:
+        now = time.time()
+
+        # Try each token starting from current position, wrapping around
+        for offset in range(n):
+            idx = (token_index + offset) % n
+            reset_at = rate_limit_reset.get(idx, 0)
+            if now >= reset_at:
+                token_index = (idx + 1) % n   # next call starts after this one
+                return idx
+
+        # All tokens are rate-limited — sleep until the earliest reset
+        earliest_reset = min(rate_limit_reset.values())
+        wait = max(earliest_reset - now, 1)
+        print(f'       -- All tokens rate-limited. Sleeping {wait:.0f}s ...')
+        time.sleep(wait)
+
+
+def makeRequest(api_url, params):
+    num_tries = 0
+    max_tries = 5
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print('       -- Max retries reached. Exiting...')
+            return None
+
+        idx = get_next_token()
+        headers = authorization_headers[idx]
+
+        try:
+            response = requests.get(api_url, headers=headers, params=params, timeout=30)
+        except requests.exceptions.RequestException as e:
+            print(f'       -- Request error: {e}. Retrying in 60 seconds...')
+            time.sleep(60)
+            continue
+
+        if response.status_code == 200:
+            return response.json()
+        elif response.status_code == 403 and 'rate limit' in response.text.lower():
+            reset_at = int(response.headers.get('X-RateLimit-Reset', time.time() + 60))
+            rate_limit_reset[idx] = reset_at
+            print(f'       -- Token [{idx}] rate-limited. Resets at {reset_at}. Trying next token ...')
+            continue
+        elif response.status_code in {401, 404, 422}:
+            return None
+        else:
+            print(f'       -- Status code {response.status_code}. Retrying... {api_url}')
+            time.sleep(1)
+
+
+def get_issue_closer(full_name, issue_number):
+    """
+    Paginate issue events to find the login of whoever fired the last
+    'closed' event. Returns '' if not found.
+    Takes the *last* closed event to handle issues reopened and closed
+    multiple times.
+    """
+    url = f'{GITHUB_REST_URL}/repos/{full_name}/issues/{issue_number}/events'
+    closer = ''
+    page = 1
+
+    while True:
+        data = makeRequest(url, {'per_page': 100, 'page': page})
+        if not data:
+            break
+        for event in data:
+            if event.get('event') == 'closed':
+                actor = event.get('actor') or {}
+                closer = actor.get('login') or ''
+        if len(data) < 100:
+            break
+        page += 1
+
+    return closer
+
+
+def count_data_rows(csv_path):
+    """Count logical CSV records, not physical newlines."""
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+    with open(csv_path, 'r', encoding='utf-8', newline='') as f:
+        return sum(1 for _ in csv.reader(f)) - 1
+
+
+def iter_issues(input_csv, processed):
+    """
+    Yield (full_name, issue_number, opener_login, state) for unprocessed rows.
+    Streams the file — never loads it fully into memory.
+    """
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+    with open(input_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                issue_number = int(row['issue_number'])
+            except (ValueError, KeyError):
+                continue
+            if (full_name, issue_number) in processed:
+                continue
+            opener = row.get('user_login', '').strip()
+            state  = row.get('state', '').strip()
+            yield full_name, issue_number, opener, state
+
+
+def process_issue(full_name, issue_number, opener, state, writer):
+    """
+    Fetch closer for one closed issue and write the result row.
+    Open issues are written immediately with empty closer fields.
+    """
+    if state != 'closed':
+        writer.writerow({
+            'full_name':    full_name,
+            'issue_number': issue_number,
+            'opener_login': opener,
+            'closer_login': '',
+            'self_closed':  '',
+        })
+        return
+
+    closer = get_issue_closer(full_name, issue_number)
+    self_closed = (opener == closer) if closer else ''
+
+    writer.writerow({
+        'full_name':    full_name,
+        'issue_number': issue_number,
+        'opener_login': opener,
+        'closer_login': closer,
+        'self_closed':  self_closed,
+    })
+    print(f'       -- opener={opener}, closer={closer}, self_closed={self_closed}')
+
+
+if __name__ == '__main__':
+    input_csv  = '../Data/DE_all_issue_details.csv'
+    output_csv = '../Data/DE_all_issue_closers.csv'
+
+    # Load already-processed (full_name, issue_number) pairs for resume support.
+    # Uses a manual line-by-line reader so a corrupted last line (from a crash)
+    # does not wipe out all the valid rows that came before it.
+    processed = set()
+    try:
+        csv.field_size_limit(min(sys.maxsize, 10**7))
+        with open(output_csv, 'r', encoding='utf-8', newline='') as f:
+            reader = csv.DictReader(f)
+            for row in reader:
+                try:
+                    processed.add((row['full_name'].strip(), int(row['issue_number'])))
+                except (ValueError, KeyError, csv.Error):
+                    pass  # skip any malformed row, including a corrupted last line
+    except (FileNotFoundError, csv.Error):
+        pass
+
+    print('Counting rows in input file (logical CSV records)...')
+    total_in_file = count_data_rows(input_csv)
+    print(f'Found {total_in_file:,} issues in input file.')
+
+    print('Counting issues still to fetch...')
+    to_fetch = sum(1 for _ in iter_issues(input_csv, processed))
+    print(f'{to_fetch:,} issues to process ({len(processed):,} already done).')
+
+    output_exists = os.path.exists(output_csv)
+    fieldnames = ['full_name', 'issue_number', 'opener_login', 'closer_login', 'self_closed']
+
+    with open(output_csv, 'a', newline='', encoding='utf-8') as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        if not output_exists:
+            writer.writeheader()
+
+        for idx, (full_name, issue_number, opener, state) in \
+                enumerate(iter_issues(input_csv, processed), 1):
+
+            print(f'  ({idx}/{to_fetch}) {full_name} Issue#{issue_number} [{state}] ...')
+            process_issue(full_name, issue_number, opener, state, writer)
+            outfile.flush()
+
+            if state == 'closed':
+                time.sleep(0.3)
+
+    print(f'Done. Output: {output_csv}')

Scripts/get_pr_reviews_graphql_for_SE4DE_repos.py

@@ -0,0 +1,271 @@
+"""
+get_pr_reviews_graphql_for_SE4DE_repos.py
+-------------------------------------------
+Fallback for PRs not covered by GH Archive (e.g. private period gaps).
+Fetches merger_login and review info via GraphQL, batching up to 10 PRs
+per query using aliases — reducing ~1.8M REST calls to ~60k GraphQL calls.
+
+GraphQL rate limit: 5000 points/hr per token (each query costs ~10-50 points
+depending on response size). With multiple tokens this is feasible.
+
+Reads:  ../Data/DE_all_pr_details.csv
+Writes: ../Data/DE_all_pr_reviews_graphql.csv
+"""
+
+import os
+import csv
+import sys
+import time
+import requests
+
+GITHUB_GRAPHQL_URL = 'https://api.github.com/graphql'
+BATCH_SIZE = 10     # PRs per GraphQL query; keep low to stay under complexity limit
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+token_index = 0
+last_request_time = {}
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+
+def make_graphql_request(query, variables=None):
+    """GraphQL POST with same token-rotation logic as existing scripts."""
+    global token_index
+    _ensure_auth()
+    num_tries = 0
+    max_tries = 5
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print('       -- Max retries reached.')
+            return None
+
+        current_time = time.time()
+        available_token = None
+        for i in range(len(tokens)):
+            if i not in last_request_time or (current_time - last_request_time[i] >= 1):
+                available_token = i
+                break
+
+        if available_token is None:
+            min_wait = min(last_request_time.values()) + 1 - current_time
+            time.sleep(max(min_wait, 1))
+            continue
+
+        token_index = available_token
+        last_request_time[token_index] = time.time()
+
+        headers = {
+            'Authorization': f'Bearer {tokens[token_index]}',
+            'Content-Type': 'application/json',
+        }
+
+        try:
+            payload = {'query': query}
+            if variables:
+                payload['variables'] = variables
+            response = requests.post(
+                GITHUB_GRAPHQL_URL, headers=headers,
+                json=payload, timeout=30
+            )
+        except requests.exceptions.RequestException as e:
+            print(f'       -- Request error: {e}. Retrying in 60 seconds...')
+            time.sleep(60)
+            continue
+
+        if response.status_code == 200:
+            data = response.json()
+            if 'errors' in data:
+                # Log but return data — partial results are still useful
+                print(f'       -- GraphQL errors: {data["errors"]}')
+            return data
+        elif response.status_code == 403 and 'rate limit' in response.text.lower():
+            last_request_time[token_index] = time.time()
+            continue
+        else:
+            print(f'       -- Status {response.status_code}. Retrying...')
+            time.sleep(1)
+
+
+def build_batch_query(batch):
+    """
+    Build a GraphQL query that fetches up to BATCH_SIZE PRs using aliases.
+    batch: list of (alias, owner, repo_name, pr_number)
+    """
+    fragments = []
+    for alias, owner, repo_name, pr_number in batch:
+        fragments.append(f"""
+  {alias}: repository(owner: "{owner}", name: "{repo_name}") {{
+    pullRequest(number: {pr_number}) {{
+      mergedBy {{ login }}
+      reviews(first: 100) {{
+        nodes {{
+          author {{ login }}
+          state
+        }}
+      }}
+    }}
+  }}""")
+    return '{ ' + '\n'.join(fragments) + '\n}'
+
+
+def parse_batch_response(data, batch):
+    """Extract results from a batched GraphQL response."""
+    results = {}
+    if not data or 'data' not in data:
+        return results
+
+    graphql_data = data['data'] or {}
+    for alias, owner, repo_name, pr_number in batch:
+        key = (f'{owner}/{repo_name}', pr_number)
+        repo_data = graphql_data.get(alias) or {}
+        pr_data   = repo_data.get('pullRequest') or {}
+
+        merged_by_data = pr_data.get('mergedBy') or {}
+        merger_login   = merged_by_data.get('login') or ''
+
+        reviewer_set      = set()
+        approved_by       = []
+        changes_req       = []
+        num_review_events = 0
+
+        for node in (pr_data.get('reviews') or {}).get('nodes') or []:
+            reviewer = (node.get('author') or {}).get('login') or ''
+            state    = node.get('state', '').upper()
+            if reviewer:
+                reviewer_set.add(reviewer)
+            if state == 'APPROVED':
+                approved_by.append(reviewer)
+            elif state == 'CHANGES_REQUESTED':
+                changes_req.append(reviewer)
+            num_review_events += 1
+
+        results[key] = {
+            'merger_login':          merger_login,
+            'num_reviewers':         len(reviewer_set),
+            'reviewers':             '|'.join(sorted(reviewer_set)),
+            'approved_by':           '|'.join(approved_by),
+            'changes_requested_by':  '|'.join(changes_req),
+            'num_review_events':     num_review_events,
+        }
+    return results
+
+
+def count_data_rows(csv_path):
+    """Count logical CSV records, not physical newlines."""
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+    with open(csv_path, 'r', encoding='utf-8', newline='') as f:
+        return sum(1 for _ in csv.reader(f)) - 1
+
+
+def iter_prs(input_csv, processed):
+    """Yield (full_name, owner, repo_name, pr_number) without loading the file."""
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+    with open(input_csv, newline='', encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            full_name = row['full_name'].strip()
+            try:
+                pr_number = int(row['pr_number'])
+            except ValueError:
+                continue
+            if '/' not in full_name:
+                continue
+            if (full_name, pr_number) in processed:
+                continue
+            owner, repo_name = full_name.split('/', 1)
+            yield full_name, owner, repo_name, pr_number
+
+
+def process_batch(chunk, writer, current_batch_num, total_batches):
+    print(f'  Batch ({current_batch_num}/{total_batches}) — {len(chunk)} PRs ...')
+
+    batch_with_aliases = [
+        (f'pr_{i}', owner, rn, prn)
+        for i, (fn, owner, rn, prn) in enumerate(chunk)
+    ]
+
+    query = build_batch_query(batch_with_aliases)
+    data = make_graphql_request(query)
+
+    alias_to_fullname = {f'pr_{i}': fn for i, (fn, _, _, _) in enumerate(chunk)}
+    results = parse_batch_response(data, batch_with_aliases)
+
+    for alias, owner, repo_name, pr_number in batch_with_aliases:
+        full_name = alias_to_fullname[alias]
+        key = (full_name, pr_number)
+        result = results.get(key, {})
+        writer.writerow({
+            'full_name':            full_name,
+            'pr_number':            pr_number,
+            'merger_login':         result.get('merger_login', ''),
+            'num_reviewers':        result.get('num_reviewers', 0),
+            'reviewers':            result.get('reviewers', ''),
+            'approved_by':          result.get('approved_by', ''),
+            'changes_requested_by': result.get('changes_requested_by', ''),
+            'num_review_events':    result.get('num_review_events', 0),
+        })
+
+
+if __name__ == '__main__':
+    input_csv = '../Data/DE_all_pr_details.csv'
+    output_csv = '../Data/DE_all_pr_reviews_graphql.csv'
+
+    # Load already-processed
+    processed = set()
+    try:
+        with open(output_csv, newline='', encoding='utf-8') as f:
+            for row in csv.DictReader(f):
+                try:
+                    processed.add((row['full_name'].strip(), int(row['pr_number'])))
+                except ValueError:
+                    pass
+    except FileNotFoundError:
+        pass
+
+    print('Counting rows in input file (logical CSV records)...')
+    total_in_file = count_data_rows(input_csv)
+    print(f'Found {total_in_file:,} PRs in input file.')
+
+    print('Counting PRs still to fetch...')
+    to_fetch = sum(1 for _ in iter_prs(input_csv, processed))
+    total_batches = (to_fetch + BATCH_SIZE - 1) // BATCH_SIZE if to_fetch else 0
+    print(f'{to_fetch:,} PRs to fetch via GraphQL (batch size={BATCH_SIZE})')
+
+    output_exists = os.path.exists(output_csv)
+    fieldnames = [
+        'full_name', 'pr_number', 'merger_login',
+        'num_reviewers', 'reviewers', 'approved_by',
+        'changes_requested_by', 'num_review_events',
+    ]
+
+    with open(output_csv, 'a', newline='', encoding='utf-8') as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        if not output_exists:
+            writer.writeheader()
+
+        chunk = []
+        current_batch_num = 0
+        for pr_tuple in iter_prs(input_csv, processed):
+            chunk.append(pr_tuple)
+            if len(chunk) < BATCH_SIZE:
+                continue
+            current_batch_num += 1
+            process_batch(chunk, writer, current_batch_num, total_batches)
+            outfile.flush()
+            chunk = []
+            time.sleep(0.5)
+
+        if chunk:
+            current_batch_num += 1
+            process_batch(chunk, writer, current_batch_num, total_batches)
+            outfile.flush()
+
+    print(f'Done. Output: {output_csv}')

Scripts/get_pr_reviews_rest_for_SE4DE_repos.py

@@ -0,0 +1,236 @@
+"""
+get_pr_reviews_for_SE4DE_repos.py
+----------------------------------
+For each PR in DE_all_pr_details.csv, collects:
+  - merger_login  : who merged the PR (not just whether it was merged)
+  - reviewers     : pipe-separated logins of reviewers
+  - approved_by   : pipe-separated logins of approvers
+  - changes_requested_by : pipe-separated logins
+  - num_review_comments  : total review thread comments
+  - num_inline_comments  : total inline code comments
+
+Reads:  ../Data/DE_all_pr_details.csv
+Writes: ../Data/DE_all_pr_reviews.csv
+"""
+
+import os
+import csv
+import sys
+import time
+import requests
+from datetime import datetime
+
+# === Token and Request Setup ===
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+token_index = 0
+last_request_time = {}
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+
+def makeRequest(api_url, params):
+    global token_index
+    _ensure_auth()
+    num_tries = 0
+    max_tries = 5
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print('       -- Max retries reached. Exiting...')
+            return None
+
+        current_time = time.time()
+        available_token = None
+        for i in range(len(authorization_headers)):
+            if i not in last_request_time or (current_time - last_request_time[i] >= 1):
+                available_token = i
+                break
+
+        if available_token is None:
+            min_wait = min(last_request_time.values()) + 1 - current_time
+            time.sleep(max(min_wait, 1))
+            continue
+
+        token_index = available_token
+        headers = authorization_headers[token_index]
+        last_request_time[token_index] = time.time()
+
+        try:
+            response = requests.get(api_url, headers=headers, params=params, timeout=30)
+        except requests.exceptions.RequestException as e:
+            print(f'       -- Request error: {e}. Retrying in 60 seconds...')
+            time.sleep(60)
+            continue
+
+        if response.status_code == 200:
+            return response.json()
+        elif response.status_code == 403 and 'rate limit' in response.text.lower():
+            last_request_time[token_index] = time.time()
+            continue
+        elif response.status_code in {422, 401, 404}:
+            return None
+        else:
+            print(f'       -- Status code {response.status_code}. Retrying... {api_url}')
+            time.sleep(1)
+
+
+def get_merger_login(full_name, pr_number):
+    """Fetch the login of whoever merged the PR from the PR endpoint."""
+    url = f'https://api.github.com/repos/{full_name}/pulls/{pr_number}'
+    data = makeRequest(url, {})
+    if not data:
+        return ''
+    merged_by = data.get('merged_by') or {}
+    return merged_by.get('login') or ''
+
+
+def get_pr_reviews(full_name, pr_number):
+    """
+    Paginate through all reviews for a PR.
+    Returns aggregated: reviewers, approved_by, changes_requested_by,
+    num_review_comments.
+    """
+    url = f'https://api.github.com/repos/{full_name}/pulls/{pr_number}/reviews'
+    reviewer_logins = set()
+    approved_by = []
+    changes_requested_by = []
+    num_review_comments = 0
+    page = 1
+
+    while True:
+        params = {'per_page': 100, 'page': page}
+        data = makeRequest(url, params)
+        if not data:
+            break
+        for review in data:
+            login = (review.get('user') or {}).get('login') or ''
+            state = review.get('state', '')
+            if login:
+                reviewer_logins.add(login)
+            if state == 'APPROVED':
+                approved_by.append(login)
+            elif state == 'CHANGES_REQUESTED':
+                changes_requested_by.append(login)
+            if review.get('body'):
+                num_review_comments += 1
+        if len(data) < 100:
+            break
+        page += 1
+
+    return reviewer_logins, approved_by, changes_requested_by, num_review_comments
+
+
+def get_pr_inline_comments(full_name, pr_number):
+    """Count inline (line-level) review comments for a PR."""
+    url = f'https://api.github.com/repos/{full_name}/pulls/{pr_number}/comments'
+    total = 0
+    page = 1
+    while True:
+        params = {'per_page': 100, 'page': page}
+        data = makeRequest(url, params)
+        if not data:
+            break
+        total += len(data)
+        if len(data) < 100:
+            break
+        page += 1
+    return total
+
+
+def count_data_rows(csv_path):
+    """Count logical CSV records (PR rows), not physical newlines.
+
+    body/labels fields often contain embedded newlines, so line counts
+    overstate row count by an order of magnitude on this file.
+    """
+    csv.field_size_limit(min(sys.maxsize, 10**7))
+    with open(csv_path, 'r', encoding='utf-8', newline='') as f:
+        return sum(1 for _ in csv.reader(f)) - 1
+
+
+if __name__ == '__main__':
+    input_csv  = '../Data/DE_all_pr_details.csv'
+    output_csv = '../Data/DE_all_pr_reviews.csv'
+
+    # Load already-processed (full_name, pr_number) pairs
+    processed = set()
+    try:
+        with open(output_csv, 'r', encoding='utf-8', newline='') as checkfile:
+            for row in csv.DictReader(checkfile):
+                processed.add((row['full_name'].strip(), row['pr_number'].strip()))
+    except FileNotFoundError:
+        pass
+
+    output_exists = os.path.exists(output_csv)
+
+    fieldnames = [
+        'full_name', 'pr_number',
+        'merger_login',       # who merged (empty if not merged or unknown)
+        'num_reviewers',
+        'reviewers',          # pipe-separated logins
+        'approved_by',        # pipe-separated logins
+        'changes_requested_by',
+        'num_review_comments',
+        'num_inline_comments',
+    ]
+
+    print('Counting input rows (streaming, no full load)...')
+    total = count_data_rows(input_csv)
+    print(f'Found {total:,} PRs in input file.')
+
+    with open(input_csv, 'r', encoding='utf-8', newline='') as infile, \
+         open(output_csv, 'a', newline='', encoding='utf-8') as outfile:
+
+        reader = csv.DictReader(infile)
+        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
+        if not output_exists:
+            writer.writeheader()
+
+        for idx, row in enumerate(reader, 1):
+            full_name = row['full_name'].strip()
+            pr_number = str(row['pr_number']).strip()
+
+            if (full_name, pr_number) in processed:
+                print(f'Skipping already processed: {full_name} PR#{pr_number}')
+                continue
+
+            print(f'({idx}/{total}) {full_name} PR#{pr_number} ...')
+
+            merger_login = ''
+            # Only fetch merger login if the PR was actually merged
+            if row.get('merged_at') and row['merged_at'].strip():
+                merger_login = get_merger_login(full_name, pr_number)
+                time.sleep(0.5)
+
+            reviewers, approved_by, changes_requested_by, num_review_comments = \
+                get_pr_reviews(full_name, pr_number)
+            time.sleep(0.5)
+
+            num_inline = get_pr_inline_comments(full_name, pr_number)
+            time.sleep(0.5)
+
+            writer.writerow({
+                'full_name':             full_name,
+                'pr_number':             pr_number,
+                'merger_login':          merger_login,
+                'num_reviewers':         len(reviewers),
+                'reviewers':             '|'.join(sorted(reviewers)),
+                'approved_by':           '|'.join(filter(None, approved_by)),
+                'changes_requested_by':  '|'.join(filter(None, changes_requested_by)),
+                'num_review_comments':   num_review_comments,
+                'num_inline_comments':   num_inline,
+            })
+            outfile.flush()
+            processed.add((full_name, pr_number))
+
+            print(f'   ===> merger={merger_login}, reviewers={len(reviewers)}, '
+                  f'approved={len(approved_by)}, inline_comments={num_inline}')

Scripts/get_repo_commits_pr_issues_contributors_for_SE4DE_repos.py

@@ -0,0 +1,421 @@
+import os
+import csv
+import time
+import requests
+from datetime import datetime, timedelta
+
+# === Token and Request Setup ===
+
+from github_tokens import init_rest_client_auth
+
+tokens: list[str] = []
+authorization_headers: list[dict[str, str]] = []
+token_index = 0
+last_request_time = {}
+
+
+def _ensure_auth() -> None:
+    global tokens, authorization_headers
+    if not tokens:
+        tokens, authorization_headers = init_rest_client_auth()
+
+
+def makeRequest(api_url, params):
+    global token_index
+    _ensure_auth()
+    num_tries = 0
+    max_tries = 5
+
+    while True:
+        num_tries += 1
+        if num_tries > max_tries:
+            print('       -- Max retries reached. Exiting...')
+            break
+
+        available_token = None
+        current_time = time.time()
+        for i in range(len(authorization_headers)):
+            if i not in last_request_time or (current_time - last_request_time[i] >= 1):
+                available_token = i
+                break
+
+        if available_token is None:
+            min_wait = min(last_request_time.values()) + 1 - current_time
+            time.sleep(max(min_wait, 1))
+            continue
+
+        token_index = available_token
+        headers = authorization_headers[token_index]
+        last_request_time[token_index] = time.time()
+
+        try:
+            response = requests.get(api_url, headers=headers, params=params, timeout=30)
+        except requests.exceptions.RequestException as e:
+            print(f'       -- Request error: {e}. Retrying in 60 seconds...')
+            time.sleep(60)
+            continue
+
+        if response.status_code == 200:
+            return response.json()
+        elif response.status_code == 403 and 'rate limit' in response.text.lower():
+            last_request_time[token_index] = time.time()
+            continue
+        elif response.status_code in {422, 401}:
+            return None
+        else:
+            print(f'       -- Status code {response.status_code}. Retrying... {api_url}')
+            time.sleep(1)
+
+def convert_to_datetime(date_str):
+    return datetime.strptime(date_str, '%Y-%m-%dT%H:%M:%SZ')
+
+def get_commit_details(repo_full_name, start_date, end_date):
+    url = f'https://api.github.com/repos/{repo_full_name}/commits'
+    total_count = 0
+    commit_details = []
+    current_start = start_date
+    step = timedelta(days=8192)  # Start with a large step
+
+    while current_start < end_date:
+        current_end = min(current_start + step, end_date)
+        print(f"     Checking Commits {current_start.date()} to {current_end.date()}")
+        page = 1
+        count_in_window = 0
+        window_commits = []
+        page_limit_hit = False
+
+        while True:
+            params = {
+                'since': current_start.isoformat() + 'Z',
+                'until': current_end.isoformat() + 'Z',
+                'per_page': 100,
+                'page': page
+            }
+            time.sleep(1)
+            data = makeRequest(url, params)
+            if not data:
+                print(f"       -- No commits on page {page}")
+                break
+            print(f"       -- Commits page {page}: {len(data)}")
+            count_in_window += len(data)
+
+            # Collect commit details
+            for commit in data:
+                window_commits.append({
+                    'commit_sha': commit.get('sha'),
+                    'parent_sha': commit.get('parents', [{}])[0].get('sha') if commit.get('parents') else '',
+                    'commit_message': commit.get('commit', {}).get('message'),
+                    'author_login': commit.get('author', {}).get('login') if commit.get('author') else '',
+                    'author_name': commit.get('commit', {}).get('author', {}).get('name'),
+                    'author_email': commit.get('commit', {}).get('author', {}).get('email'),
+                    'author_date': commit.get('commit', {}).get('author', {}).get('date'),
+                    'committer_login': commit.get('committer', {}).get('login') if commit.get('committer') else '',
+                    'committer_name': commit.get('commit', {}).get('committer', {}).get('name'),
+                    'committer_email': commit.get('commit', {}).get('committer', {}).get('email'),
+                    'committer_date': commit.get('commit', {}).get('committer', {}).get('date'),
+                    'comment_count': commit.get('commit', {}).get('comment_count')
+                })
+            if len(data) < 100:
+                break
+            page += 1
+            if page > 10:
+                if step == timedelta(days=1):
+                    print("       -- Step reached 1 day and still too many commits. Aborting.")
+                    return '<many>', []
+                print("       -- Hit page limit, reducing step size and retrying")
+                step = step / 2
+                page_limit_hit = True
+                break
+        
+        if not page_limit_hit:
+            commit_details.extend(window_commits)
+            total_count += count_in_window
+            current_start = current_end
+            # Gradually increase step size after a successful small window, only if the previous count was less than 500
+            if step < timedelta(days=4096) and count_in_window < 500:
+                step = step * 2
+                # Cap the step so it doesn't get bigger than your initial max
+                if step > timedelta(days=4096):
+                    step = timedelta(days=4096)
+        
+    return total_count, commit_details
+
+def get_pr_count(repo_full_name, before_date, type):
+    query = f'repo:{repo_full_name} is:{type} created:<{before_date.date()}'
+    url = 'https://api.github.com/search/issues'
+    params = {'q': query, 'per_page': 1}
+    print(f"      Checking {type.upper()}s until {before_date.date()}")
+    data = makeRequest(url, params)
+    prs_issues_count = data['total_count'] if data and 'total_count' in data else 0
+    print(f"       -- {type.upper()}s: {prs_issues_count}")
+    return prs_issues_count
+
+def get_pr_issue_details(repo_full_name, start_date, end_date, type):
+    url = 'https://api.github.com/search/issues'
+    pr_issue_details = []
+
+    # Check total PR count for the whole period
+    query = f'repo:{repo_full_name} is:{type} created:{start_date.date()}..{end_date.date()}'
+    params = {'q': query, 'per_page': 1}
+    data = makeRequest(url, params)
+    total_count = data['total_count'] if data and 'total_count' in data else 0
+
+    # If total_count unders 1000, fetch all in one window
+    if total_count <= 1000:
+        step = end_date - start_date
+    else:
+        step = timedelta(days=4096)
+
+    current_start = start_date
+    total_count_accum = 0
+
+    while current_start < end_date:
+        current_end = min(current_start + step, end_date)
+        print(f"     Checking {type.upper()}s {current_start.date()} to {current_end.date()}")
+        # If splitting, check window count
+        if total_count > 1000:
+            query = f'repo:{repo_full_name} is:{type} created:{current_start.date()}..{current_end.date()}'
+            params = {'q': query, 'per_page': 1}
+            data = makeRequest(url, params)
+            window_count = data['total_count'] if data and 'total_count' in data else 0
+            if window_count > 1000:
+                if step == timedelta(days=1):
+                    print(f"       -- Step reached 1 day and still too many {type.upper()}s. Aborting.")
+                    return '<many>', []
+                print(f"       -- Too many {type.upper()}s, reducing step size and retrying")
+                step = step / 2
+                continue
+        else:
+            window_count = total_count
+
+        # Fetch PRs and Issues for this window
+        page = 1
+        seen_item_numbers = set()
+        while True:
+            params = {'q': query, 'per_page': 100, 'page': page}
+            time.sleep(1)
+            data = makeRequest(url, params)
+            if not data or 'items' not in data:
+                break
+            items = data['items']
+            print(f"       -- {type.upper()}s page {page}: {len(items)}")
+
+            for item in items:
+                if item.get('number') in seen_item_numbers:
+                    continue
+                seen_item_numbers.add(item.get('number'))
+                pr_issue_details.append({
+                    f'{type}_number': item.get('number'),
+                    'title': item.get('title'),
+                    'user_login': item.get('user', {}).get('login'),
+                    'created_at': item.get('created_at'),
+                    'updated_at': item.get('updated_at'),
+                    'closed_at': item.get('closed_at'),
+                    'merged_at': item.get('pull_request', {}).get('merged_at') if item.get('pull_request') else '',
+                    'state': item.get('state'),
+                    'locked': item.get('locked'),
+                    'body': item.get('body'),
+                    'merge_commit_sha': item.get('pull_request', {}).get('merge_commit_sha') if item.get('pull_request') else '',
+                    'draft': item.get('draft'),
+                    'milestone': item.get('milestone', {}).get('title') if item.get('milestone') else '',
+                    'labels': ','.join([label.get('name', '') for label in item.get('labels', [])]),
+                    'assignees': ','.join([assignee.get('login', '') for assignee in item.get('assignees', [])])
+                })
+            if len(items) < 100:
+                break
+            page += 1
+
+        total_count_accum += window_count
+        current_start = current_end
+
+    return total_count_accum, pr_issue_details
+
+def get_contributors_count(repo_full_name):
+    total_count = 0
+    page = 1
+    headers = {'Accept': 'application/vnd.github.v3+json', 'Authorization': f'Bearer {tokens[0]}'}
+    print(f"     Checking Contributors ...")
+
+    while True:
+        url = f'https://api.github.com/repos/{repo_full_name}/contributors'
+        params = {'per_page': 100, 'page': page, 'anon': 'false'}
+        response = requests.get(url, headers=headers, params=params)
+        data = response.json()
+        if response.status_code != 200 or not data:
+            print(f"Error or empty response on page {page}: {response.status_code}")
+            break
+        print(f"       -- Contributors page {page}: {len(data)}")
+        total_count += len(data)
+        if len(data) < 100:
+            break
+        page += 1
+
+    return total_count
+
+def get_repo_data(repo_full_name, start_date, before_date):
+    commits, commit_details = get_commit_details(repo_full_name, start_date, before_date)
+    time.sleep(1)
+    prs, pr_details = get_pr_issue_details(repo_full_name, start_date, before_date, 'pr')
+    time.sleep(1)
+    issues, issue_details = get_pr_issue_details(repo_full_name, start_date, before_date, 'issue')
+    time.sleep(1)
+    contributors = get_contributors_count(repo_full_name)
+    time.sleep(2)
+    return commits, commit_details, prs, pr_details, issues, issue_details, contributors
+
+def resolve_repo_redirect(owner, repo):
+    url = f'https://api.github.com/repos/{owner}/{repo}'
+    for token_id, headers in enumerate(authorization_headers):
+        try:
+            response = requests.get(url, headers=headers, allow_redirects=True, timeout=10)
+            if response.status_code == 200:
+                data = response.json()
+                full_name = data.get('full_name')
+                if full_name:
+                    return full_name  # New or unchanged repo name
+            elif response.status_code == 404:
+                print(f"       -- Repo not found: {owner}/{repo}")
+                return None
+        except Exception as e:
+            print(f"       -- Error resolving {owner}/{repo}: {e}")
+    return None
+
+if __name__ == '__main__':
+    print(f"Collecting data for Data Engineering repositories ...")
+    input_csv = f'../Data/all_DE_repositories.csv'
+    output_csv = f'../Data/DE_repo_metrics.csv'
+    commit_details_csv = f'../Data/DE_all_commits_details.csv'
+    pr_details_csv = f'../Data/DE_all_pr_details.csv'
+    issue_details_csv = f'../Data/DE_all_issue_details.csv'
+    
+    start_date = datetime(2008, 1, 1)
+    end_date = datetime(2026, 4, 30)
+
+    # Read already processed repos
+    processed_repos = set()
+    try:
+        with open(output_csv, 'r', encoding='utf-8', newline='') as checkfile:
+            for row in csv.DictReader(checkfile):
+                processed_repos.add(row['full_name'].strip())
+    except FileNotFoundError:
+        pass
+
+    output_exists = os.path.exists(output_csv)
+    commit_details_exists = os.path.exists(commit_details_csv)
+    pr_details_exists = os.path.exists(pr_details_csv)
+    issue_details_exists = os.path.exists(issue_details_csv)
+    
+    with open(input_csv, 'r', encoding='utf-8') as infile, \
+        open(output_csv, 'a', newline='', encoding='utf-8') as outfile, \
+        open(commit_details_csv, 'a', newline='', encoding='utf-8') as commitfile, \
+        open(pr_details_csv, 'a', newline='', encoding='utf-8') as pr_file, \
+        open(issue_details_csv, 'a', newline='', encoding='utf-8') as issue_file:
+
+        reader = list(csv.DictReader(infile))
+        total_repos = len(reader)
+
+        writer = csv.DictWriter(outfile, fieldnames=['full_name', 'repo_resolved_name', 'commits', 'pull_requests', 'issues', 'contributors'])
+        if not output_exists:
+            writer.writeheader()
+
+        # Prepare commit details writers
+        commit_fieldnames = [
+            'full_name', 'commit_sha', 'parent_sha', 'commit_message',
+            'author_login', 'author_name', 'author_email', 'author_date',
+            'committer_login', 'committer_name', 'committer_email', 'committer_date',
+            'comment_count'
+        ]
+        commit_writer = csv.DictWriter(commitfile, fieldnames=commit_fieldnames)
+        if not commit_details_exists:
+            commit_writer.writeheader()
+
+        # Prepare PR details writer
+        pr_fieldnames = [
+            'full_name', 'pr_number', 'title', 'user_login', 'created_at', 'updated_at', 'closed_at',
+            'merged_at', 'state', 'locked', 'body', 'merge_commit_sha', 'draft', 'milestone', 'labels', 'assignees'
+        ]
+        pr_writer = csv.DictWriter(pr_file, fieldnames=pr_fieldnames)
+        if not pr_details_exists:
+            pr_writer.writeheader()
+
+        # Prepare Issue details writer
+        issue_fieldnames = [
+            'full_name', 'issue_number', 'title', 'user_login', 'created_at', 'updated_at', 'closed_at',
+            'merged_at', 'state', 'locked', 'body', 'merge_commit_sha', 'draft', 'milestone', 'labels', 'assignees'
+        ]
+        issue_writer = csv.DictWriter(issue_file, fieldnames=issue_fieldnames)
+        if not issue_details_exists:
+            issue_writer.writeheader()
+
+        for idx, row in enumerate(reader, 1):
+            original_repo = row['full_name'].strip()
+            if '/' not in original_repo:
+                continue
+
+            # Skip if already processed
+            if original_repo in processed_repos:
+                print(f"Skipping already processed DE repo: {original_repo}")
+                continue
+
+            owner, full_name = original_repo.split('/')
+            resolved_repo = resolve_repo_redirect(owner, full_name)
+
+            if not resolved_repo:
+                print(f"Skipping unresolved DE repo: {original_repo}")
+                writer.writerow({
+                    'full_name': original_repo,
+                    'repo_resolved_name': '',
+                    'commits': 0,
+                    'pull_requests': 0,
+                    'issues': 0,
+                    'contributors': 0
+                })
+                outfile.flush()
+                processed_repos.add(original_repo)
+                continue
+
+            print(f"({idx}/{total_repos}) DE Processing {original_repo} ...")
+
+            try:
+                commits, commit_details, prs, pr_details, issues, issue_details, contributors = get_repo_data(resolved_repo, start_date, end_date)
+            except Exception as e:
+                print(f"       -- Error with {original_repo}: {e}")
+                commits, commit_details, prs, pr_details, issues, issue_details, contributors = 'error', 'error', 'error', 'error', 'error', 'error', 'error'
+
+            writer.writerow({
+                'full_name': original_repo,
+                'repo_resolved_name': resolved_repo,
+                'commits': commits,
+                'pull_requests': prs,
+                'issues': issues,
+                'contributors': contributors
+            })
+            outfile.flush()
+            processed_repos.add(original_repo)
+
+            # Write commit details
+            if commit_details and isinstance(commit_details, list):
+                for detail in commit_details:
+                    detail_with_repo = {'full_name': original_repo}
+                    detail_with_repo.update(detail)
+                    commit_writer.writerow(detail_with_repo)
+                commitfile.flush()
+            
+            # Write PR details
+            if pr_details and isinstance(pr_details, list):
+                for pr in pr_details:
+                    pr_with_repo = {'full_name': original_repo}
+                    pr_with_repo.update(pr)
+                    pr_writer.writerow(pr_with_repo)
+                pr_file.flush()
+
+            # Write issue details
+            if issue_details and isinstance(issue_details, list):
+                for issue in issue_details:
+                    issue_with_repo = {'full_name': original_repo}
+                    issue_with_repo.update(issue)
+                    issue_writer.writerow(issue_with_repo)
+                issue_file.flush()
+
+            print(f"   ===> {original_repo}: commits={commits}, PRs={prs}, Issues={issues}, contributors={contributors}")
+            time.sleep(1)

Scripts/github_api.py

@@ -0,0 +1,78 @@
+"""Shared GitHub REST session with rate-limit and transient-network retries."""
+from __future__ import annotations
+
+import logging
+import time
+
+import requests
+
+log = logging.getLogger(__name__)
+
+GITHUB_API = "https://api.github.com"
+_RATE_FLOOR = 200
+_MAX_NETWORK_RETRIES = 8
+_RETRY_BASE_SEC = 2.0
+_TRANSIENT_HTTP = {502, 503, 504, 520, 521, 522, 429}
+_TRANSIENT_EXC = (
+    requests.exceptions.ConnectionError,
+    requests.exceptions.Timeout,
+    requests.exceptions.ChunkedEncodingError,
+)
+
+
+class GitHubSession:
+    """requests.Session wrapper: rate limits, 202 polling, network retries."""
+
+    def __init__(self, token: str) -> None:
+        self._s = requests.Session()
+        headers = {
+            "Accept": "application/vnd.github+json",
+            "X-GitHub-Api-Version": "2022-11-28",
+        }
+        if token:
+            headers["Authorization"] = f"Bearer {token}"
+        self._s.headers.update(headers)
+
+    def get(self, url: str, **kwargs) -> requests.Response:
+        kwargs.setdefault("timeout", (15, 90))
+        attempt = 0
+        while True:
+            attempt += 1
+            try:
+                resp = self._s.get(url, **kwargs)
+            except _TRANSIENT_EXC as exc:
+                if attempt >= _MAX_NETWORK_RETRIES:
+                    raise
+                sleep_sec = min(120.0, _RETRY_BASE_SEC * (2 ** (attempt - 1)))
+                log.warning(
+                    "Network error on GET (attempt %d/%d), sleeping %.0fs: %s",
+                    attempt, _MAX_NETWORK_RETRIES, sleep_sec, exc,
+                )
+                time.sleep(sleep_sec)
+                continue
+
+            remaining = int(resp.headers.get("X-RateLimit-Remaining", 9999))
+            reset_at = int(resp.headers.get("X-RateLimit-Reset", 0))
+
+            if resp.status_code == 403 and remaining == 0:
+                sleep_sec = max(reset_at - int(time.time()), 0) + 5
+                log.warning("Rate limit hit; sleeping %ds", sleep_sec)
+                time.sleep(sleep_sec)
+                continue
+            if resp.status_code == 202:
+                time.sleep(3)
+                continue
+            if resp.status_code in _TRANSIENT_HTTP and attempt < _MAX_NETWORK_RETRIES:
+                retry_after = int(resp.headers.get("Retry-After", 0))
+                sleep_sec = retry_after or min(120.0, _RETRY_BASE_SEC * (2 ** (attempt - 1)))
+                log.warning(
+                    "HTTP %d on GET (attempt %d/%d), sleeping %.0fs",
+                    resp.status_code, attempt, _MAX_NETWORK_RETRIES, sleep_sec,
+                )
+                time.sleep(sleep_sec)
+                continue
+            if remaining < _RATE_FLOOR:
+                sleep_sec = max(reset_at - int(time.time()), 0) + 2
+                log.info("Rate budget low (%d remaining); sleeping %ds", remaining, sleep_sec)
+                time.sleep(sleep_sec)
+            return resp

Scripts/github_tokens.py

@@ -0,0 +1,126 @@
+"""GitHub PAT configuration for DEPosit collection scripts.
+
+Never commit personal access tokens. Provide credentials via:
+
+  1. Environment variables (recommended for CI)
+  2. A local ``.env`` file (copy from ``.env.example``; not committed)
+  3. ``--token`` / ``--tokens`` CLI flags where supported
+
+Variables:
+  GITHUB_TOKEN_SE4DE  — project-specific name (preferred)
+  GITHUB_TOKEN        — standard name
+  GITHUB_TOKENS       — comma-separated PATs for rate-limit rotation
+"""
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+PACKAGE_ROOT = Path(__file__).resolve().parents[1]
+
+
+def load_dotenv(path: Path | None = None) -> None:
+    """Load KEY=VALUE pairs from .env into os.environ (does not override existing)."""
+    path = path or PACKAGE_ROOT / ".env"
+    if not path.is_file():
+        return
+    for raw in path.read_text(encoding="utf-8").splitlines():
+        line = raw.strip()
+        if not line or line.startswith("#") or "=" not in line:
+            continue
+        key, _, value = line.partition("=")
+        key = key.strip()
+        value = value.strip().strip("'").strip('"')
+        if key and key not in os.environ:
+            os.environ[key] = value
+
+
+def load_tokens() -> list[str]:
+    """Return all configured PATs (may be empty)."""
+    load_dotenv()
+    found: list[str] = []
+    for env in ("GITHUB_TOKEN_SE4DE", "GITHUB_TOKEN"):
+        value = os.environ.get(env, "").strip()
+        if value and value not in found:
+            found.append(value)
+    for part in os.environ.get("GITHUB_TOKENS", "").split(","):
+        part = part.strip()
+        if part and part not in found:
+            found.append(part)
+    return found
+
+
+def build_authorization_headers(tokens: list[str]) -> list[dict[str, str]]:
+    return [
+        {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}
+        for token in tokens
+    ]
+
+
+def resolve_token(cli_token: str | None = None, cli_tokens: str | None = None) -> str | None:
+    """Single PAT: CLI overrides environment."""
+    if cli_token and cli_token.strip():
+        return cli_token.strip()
+    if cli_tokens:
+        parts = [p.strip() for p in cli_tokens.split(",") if p.strip()]
+        if parts:
+            return parts[0]
+    tokens = load_tokens()
+    return tokens[0] if tokens else None
+
+
+def require_github_tokens(
+    cli_token: str | None = None,
+    cli_tokens: str | None = None,
+) -> list[str]:
+    """Return PAT list or exit with instructions."""
+    if cli_token and cli_token.strip():
+        return [cli_token.strip()]
+    if cli_tokens:
+        parts = [p.strip() for p in cli_tokens.split(",") if p.strip()]
+        if parts:
+            return parts
+    tokens = load_tokens()
+    if not tokens:
+        _exit_missing_token()
+    return tokens
+
+
+def primary_token(cli_token: str | None = None, cli_tokens: str | None = None) -> str:
+    token = resolve_token(cli_token, cli_tokens)
+    if not token:
+        _exit_missing_token()
+    return token
+
+
+def init_rest_client_auth(
+    cli_token: str | None = None,
+    cli_tokens: str | None = None,
+) -> tuple[list[str], list[dict[str, str]]]:
+    """Used by REST collection scripts with token rotation."""
+    tokens = require_github_tokens(cli_token, cli_tokens)
+    return tokens, build_authorization_headers(tokens)
+
+
+def add_github_token_args(parser: argparse.ArgumentParser) -> None:
+    group = parser.add_argument_group("GitHub authentication")
+    group.add_argument(
+        "--token",
+        metavar="PAT",
+        help="GitHub personal access token (overrides environment)",
+    )
+    group.add_argument(
+        "--tokens",
+        metavar="PAT1,PAT2",
+        help="Comma-separated PATs for rate-limit rotation (overrides environment)",
+    )
+
+
+def _exit_missing_token() -> None:
+    print("GitHub token required for API collection.", file=sys.stderr)
+    print("  Option A: copy .env.example to .env and set GITHUB_TOKEN_SE4DE", file=sys.stderr)
+    print("  Option B: $env:GITHUB_TOKEN_SE4DE = '<your-pat>'  (PowerShell)", file=sys.stderr)
+    print("  Option C: pass --token <your-pat> on scripts that support it", file=sys.stderr)
+    sys.exit(1)

Scripts/pipeline_parsers/__init__.py

@@ -0,0 +1,138 @@
+"""
+pipeline_parsers
+~~~~~~~~~~~~~~~~
+Per-artifact-type feature extractors for DEPosit pipeline artifact collection.
+
+Path patterns follow official or recommended layouts (dbt, Airflow, Prefect,
+Dagster, Kedro, Mage, etc.). Ambiguous paths require CONTENT_SIGNALS confirmation.
+
+Each parser exposes a single function:
+    extract(content: str, file_path: str) -> dict
+
+The returned dict maps column names to values ready for INSERT into the
+corresponding SQLite table.  Parsers never raise; on unrecoverable errors
+they return a dict with parse_error set and numeric fields set to None.
+"""
+
+ARTIFACT_PATTERNS = {
+    # Evaluated in order; first match wins.
+    #
+    # Airflow: DAG bundles live under dags_folder (default subfolder "dags").
+    # Do not scan plugins/ — shared code, not DAG definitions (Airflow docs).
+    "airflow_dag": [
+        r"(?:^|/)dags/.*\.py$",
+        r"(?:^|/)dag/.*\.py$",
+        r"(?:^|/)airflow/dags?/.*\.py$",
+    ],
+    # dbt: top-level resource dirs from dbt_project.yml (dbt Developer Hub).
+    "dbt_model": [
+        r"(?:^|/)models/.*\.sql$",
+        r"(?:^|/)macros/.*\.sql$",
+        r"(?:^|/)snapshots/.*\.sql$",
+        r"(?:^|/)analyses/.*\.sql$",
+        r"(?:^|/)analysis/.*\.sql$",
+    ],
+    # dbt: schema YAML, project manifest, package lockfile.
+    "dbt_schema": [
+        r"(?:^|/)models/.*\.yml$",
+        r"(?:^|/)models/.*\.yaml$",
+        r"(?:^|/)macros/.*\.ya?ml$",
+        r"(?:^|/)snapshots/.*\.ya?ml$",
+        r"(?i)(?:^|/)dbt_project\.ya?ml$",
+        r"(?i)(?:^|/)packages\.ya?ml$",
+    ],
+    # Prefect: flow modules and project/deployment YAML (Prefect 2/3 docs).
+    "prefect_flow": [
+        r"(?:^|/)flows?/.*\.py$",
+        r"(?:^|/)prefect/.*\.py$",
+        r"(?i)(?:^|/)prefect\.ya?ml$",
+        r"(?i)(?:^|/)[^/]+-deployment\.ya?ml$",
+    ],
+    # Dagster: defs/assets/jobs layout + src/<pkg>/definitions.py (Dagster docs).
+    "dagster": [
+        r"(?:^|/)(?:assets|jobs|ops|graphs|schedules|sensors|repository)/.*\.py$",
+        r"(?:^|/)dagster/.*\.py$",
+        r"(?:^|/)definitions\.py$",
+        r"(?:^|/)src/[^/]+/definitions\.py$",
+        r"(?:^|/)src/[^/]+/defs/.+\.py$",
+        r"(?:^|/)src/[^/]+/assets/.+\.py$",
+    ],
+    # Luigi: task modules (luigi.Task).
+    "luigi": [
+        r"(?:^|/)(?:tasks?|luigi)/.*\.py$",
+    ],
+    # Kedro: src/<pkg>/pipelines and conf/base catalog (Kedro docs).
+    "kedro": [
+        r"(?:^|/)src/[^/]+/pipelines?/.+\.py$",
+        r"(?:^|/)pipelines?/[^/]+\.py$",
+        r"(?i)(?:^|/)conf/base/catalog\.ya?ml$",
+        r"(?i)(?:^|/)conf/base/parameters\.ya?ml$",
+        r"(?:^|/)nodes?\.py$",
+    ],
+    # Apache Beam: dedicated beam/ or pipelines/ package (content-gated).
+    "beam": [
+        r"(?:^|/)beam/.*\.py$",
+        r"(?:^|/)pipelines?/[^/]+\.py$",
+    ],
+    # dlt: sources/ and pipelines/ modules (dlthub layout).
+    "dlt": [
+        r"(?:^|/)sources?/[^/]+\.py$",
+        r"(?:^|/)pipelines?/[^/]+\.py$",
+    ],
+    # Mage: block folders per Mage project structure docs.
+    "mage_block": [
+        r"(?:^|/)(?:data_loaders?|transformers?|data_exporters?|sensors?)/.*\.py$",
+        r"(?:^|/)(?:data_loaders?|transformers?|data_exporters?|sensors?)/.*\.sql$",
+        r"(?:^|/)dbt/(?:models|macros|snapshots)/.*\.sql$",
+    ],
+}
+
+# Content-level signals confirm ambiguous path matches (bytes substrings).
+CONTENT_SIGNALS = {
+    "airflow_dag": [
+        b"from airflow",
+        b"import airflow",
+        b"DAG(",
+        b"@dag",
+    ],
+    "dbt_model": [],  # path alone is sufficient for dbt SQL resources
+    "dbt_schema": [
+        b"models:",
+        b"version:",
+        b"dbt_project",
+        b"packages:",
+        b"require-dbt-version",
+    ],
+    "prefect_flow": [
+        b"from prefect",
+        b"import prefect",
+        b"@flow",
+        b"@task",
+        b"deployments:",
+        b"prefect:",
+    ],
+    "dagster": [
+        b"from dagster",
+        b"import dagster",
+        b"@asset",
+        b"@op",
+        b"@job",
+        b"Definitions",
+    ],
+    "luigi": [b"import luigi", b"from luigi", b"luigi.Task"],
+    "kedro": [
+        b"from kedro",
+        b"import kedro",
+        b"kedro.pipeline",
+        b"catalog:",
+    ],
+    "beam": [b"import apache_beam", b"from apache_beam"],
+    "dlt": [b"import dlt", b"from dlt", b"@dlt.resource", b"@dlt.source"],
+    "mage_block": [
+        b"@data_loader",
+        b"@transformer",
+        b"@data_exporter",
+        b"@sensor",
+        b"mage_ai",
+    ],
+}

Scripts/pipeline_parsers/airflow_parser.py

@@ -0,0 +1,338 @@
+"""
+airflow_parser.py
+~~~~~~~~~~~~~~~~~
+Extracts structural and quality features from Airflow DAG files.
+
+Strategy: AST-walk the file.  We collect every Call node whose function
+resolves to a known DAG constructor or task operator, plus every binary
+operation (>>, <<) and explicit set_downstream / set_upstream call.
+
+We intentionally avoid executing the file: dynamic DAG generation patterns
+(DagFactory, loop-based DAGs) are flagged via heuristics rather than
+skipped entirely.
+"""
+
+import ast
+import json
+import re
+from typing import Any
+
+# Operators we track individually because they carry specific semantic meaning
+# for SE research (coupling, reliability, observability).
+_SENSOR_OPERATORS = {
+    "ExternalTaskSensor", "ExternalTaskMarker",
+    "HttpSensor", "S3KeySensor", "SqlSensor",
+    "BaseSensorOperator",
+}
+_BRANCH_OPERATORS = {
+    "BranchPythonOperator", "BranchSQLOperator",
+    "BranchDayOfWeekOperator", "BranchDateTimeOperator",
+    "BaseBranchOperator",
+}
+_PYTHON_OPERATORS = {"PythonOperator", "PythonVirtualenvOperator", "ExternalPythonOperator"}
+_BASH_OPERATORS   = {"BashOperator"}
+
+_SCHEDULE_PRESETS = {
+    "@once", "@hourly", "@daily", "@weekly", "@monthly", "@yearly", "None",
+}
+
+_CRON_RE = re.compile(
+    r"^(\*|[0-9,\-\*/]+)\s+"   # minute
+    r"(\*|[0-9,\-\*/]+)\s+"   # hour
+    r"(\*|[0-9,\-\*/]+)\s+"   # day-of-month
+    r"(\*|[0-9,\-\*/]+)\s+"   # month
+    r"(\*|[0-9,\-\*/]+)$"     # day-of-week
+)
+
+
+def _schedule_type(raw: str | None) -> str:
+    if raw is None or raw in ("None", ""):
+        return "none"
+    if raw in _SCHEDULE_PRESETS:
+        return "preset"
+    if _CRON_RE.match(raw.strip()):
+        return "cron"
+    if "timedelta" in raw or "datetime.timedelta" in raw:
+        return "timedelta"
+    if "schedule" in raw.lower() or "timetable" in raw.lower():
+        return "dynamic"
+    return "other"
+
+
+class _DAGVisitor(ast.NodeVisitor):
+    """Walks a DAG file AST and accumulates all features we care about."""
+
+    def __init__(self) -> None:
+        self.dags:               list[dict] = []
+        self._current_dag:       dict | None = None
+        self._operator_names:    set[str] = set()
+        self._edge_count:        int = 0
+        self._uses_xcom:         bool = False
+        self._uses_pools:        bool = False
+        self._uses_connections:  bool = False
+
+    # ── DAG detection ─────────────────────────────────────────────────────
+
+    def visit_With(self, node: ast.With) -> None:
+        """Handles:  with DAG(...) as dag:"""
+        for item in node.items:
+            if isinstance(item.context_expr, ast.Call):
+                name = self._call_name(item.context_expr)
+                if name in ("DAG", "airflow.DAG"):
+                    dag = self._parse_dag_call(item.context_expr)
+                    self._current_dag = dag
+                    self.generic_visit(node)
+                    self._finalise_dag()
+                    return
+        self.generic_visit(node)
+
+    def visit_Assign(self, node: ast.Assign) -> None:
+        """Handles:  dag = DAG(...)"""
+        if isinstance(node.value, ast.Call):
+            name = self._call_name(node.value)
+            if name in ("DAG", "airflow.DAG"):
+                dag = self._parse_dag_call(node.value)
+                self._current_dag = dag
+                self.generic_visit(node)
+                self._finalise_dag()
+                return
+        self.generic_visit(node)
+
+    # ── @dag decorator ────────────────────────────────────────────────────
+
+    def visit_FunctionDef(self, node: ast.FunctionDef) -> None:
+        for dec in node.decorator_list:
+            call = dec if isinstance(dec, ast.Call) else None
+            bare = dec if isinstance(dec, ast.Name) else None
+            name = (self._call_name(call) if call else
+                    (bare.id if bare else None))
+            if name == "dag":
+                dag = self._parse_dag_call(call) if call else {}
+                dag.setdefault("dag_id", node.name)
+                self._current_dag = dag
+                self.generic_visit(node)
+                self._finalise_dag()
+                return
+        self.generic_visit(node)
+
+    visit_AsyncFunctionDef = visit_FunctionDef
+
+    def _finalise_dag(self) -> None:
+        if self._current_dag is None:
+            return
+        d = self._current_dag
+        d["task_count"]         = d.get("task_count", 0)
+        d["edge_count"]         = self._edge_count
+        d["operator_types"]     = json.dumps(sorted(self._operator_names))
+        d["unique_operator_count"] = len(self._operator_names)
+        d["has_python_operator"]    = int(bool(self._operator_names & _PYTHON_OPERATORS))
+        d["has_bash_operator"]      = int(bool(self._operator_names & _BASH_OPERATORS))
+        d["has_external_task_sensor"] = int(bool(self._operator_names & _SENSOR_OPERATORS))
+        d["has_branch_operator"]    = int(bool(self._operator_names & _BRANCH_OPERATORS))
+        d["uses_xcom"]           = int(self._uses_xcom)
+        d["uses_pools"]          = int(self._uses_pools)
+        d["uses_connections"]    = int(self._uses_connections)
+        # Derive anti-patterns
+        catchup        = d.get("catchup")
+        max_active     = d.get("max_active_runs")
+        retries        = d.get("default_retries")
+        on_fail        = d.get("has_on_failure_callback", 0)
+        sched_type     = d.get("schedule_type", "none")
+        d["antipattern_catchup_no_maxruns"] = int(
+            catchup is True and max_active is None
+        )
+        d["antipattern_no_retries"]   = int(retries is None or retries == 0)
+        d["antipattern_no_failure_cb"] = int(not on_fail)
+        d["antipattern_no_schedule"]  = int(sched_type == "none")
+        d["antipattern_bare_xcom"]    = int(self._uses_xcom)  # heuristic; refine if needed
+        self.dags.append(d)
+        self._current_dag       = None
+        self._operator_names    = set()
+        self._edge_count        = 0
+        self._uses_xcom         = False
+        self._uses_pools        = False
+        self._uses_connections  = False
+
+    # ── Task operator detection ───────────────────────────────────────────
+
+    def visit_Call(self, node: ast.Call) -> None:
+        name = self._call_name(node)
+        # Count task operators
+        if name and ("Operator" in name or "Sensor" in name or "Hook" in name):
+            short = name.split(".")[-1]
+            self._operator_names.add(short)
+            if self._current_dag is not None:
+                self._current_dag["task_count"] = (
+                    self._current_dag.get("task_count", 0) + 1
+                )
+        # xcom usage
+        if name in ("xcom_push", "xcom_pull") or (
+            isinstance(node.func, ast.Attribute)
+            and node.func.attr in ("xcom_push", "xcom_pull")
+        ):
+            self._uses_xcom = True
+        # pool usage
+        for kw in node.keywords:
+            if kw.arg == "pool":
+                self._uses_pools = True
+            if kw.arg in ("conn_id", "gcp_conn_id", "aws_conn_id",
+                          "azure_conn_id", "http_conn_id"):
+                self._uses_connections = True
+        self.generic_visit(node)
+
+    # ── Dependency edges ──────────────────────────────────────────────────
+
+    def visit_BinOp(self, node: ast.BinOp) -> None:
+        if isinstance(node.op, (ast.RShift, ast.LShift)):
+            self._edge_count += 1
+        self.generic_visit(node)
+
+    def visit_Expr(self, node: ast.Expr) -> None:
+        if isinstance(node.value, ast.Call):
+            name = self._call_name(node.value)
+            if name in ("set_downstream", "set_upstream") or (
+                isinstance(node.value.func, ast.Attribute)
+                and node.value.func.attr in ("set_downstream", "set_upstream")
+            ):
+                self._edge_count += 1
+        self.generic_visit(node)
+
+    # ── DAG constructor argument parsing ─────────────────────────────────
+
+    def _parse_dag_call(self, node: ast.Call) -> dict:
+        d: dict[str, Any] = {}
+        # Positional: DAG(dag_id, schedule_interval=...)
+        if node.args:
+            d["dag_id"] = self._const_str(node.args[0])
+        for kw in node.keywords:
+            arg = kw.arg
+            val = kw.value
+            if arg == "dag_id":
+                d["dag_id"] = self._const_str(val)
+            elif arg in ("schedule_interval", "schedule"):
+                raw = self._const_str(val)
+                d["schedule_interval"] = raw
+                d["schedule_type"] = _schedule_type(raw)
+            elif arg == "catchup":
+                d["catchup"] = self._const_bool(val)
+            elif arg == "max_active_runs":
+                d["max_active_runs"] = self._const_int(val)
+            elif arg == "default_args":
+                self._parse_default_args(val, d)
+            elif arg == "tags":
+                d["dag_tags"] = self._const_list_str(val)
+            elif arg == "sla_miss_callback":
+                d["has_sla"] = 1
+            elif arg == "on_failure_callback":
+                d["has_on_failure_callback"] = 1
+            elif arg == "on_success_callback":
+                d["has_on_success_callback"] = 1
+        return d
+
+    def _parse_default_args(self, node: ast.expr, d: dict) -> None:
+        """Extract retries / sla / callbacks from default_args dict literal."""
+        if not isinstance(node, ast.Dict):
+            return
+        for key, val in zip(node.keys, node.values):
+            k = self._const_str(key)
+            if k == "retries":
+                d["default_retries"] = self._const_int(val)
+            elif k == "retry_delay":
+                # timedelta(minutes=...) etc. — just flag presence
+                d["default_retry_delay_seconds"] = -1  # present but not trivially parsed
+            elif k == "sla":
+                d["has_sla"] = 1
+            elif k == "on_failure_callback":
+                d["has_on_failure_callback"] = 1
+            elif k == "on_success_callback":
+                d["has_on_success_callback"] = 1
+
+    # ── AST helper utilities ──────────────────────────────────────────────
+
+    @staticmethod
+    def _call_name(node: ast.Call | None) -> str | None:
+        if node is None:
+            return None
+        f = node.func
+        if isinstance(f, ast.Name):
+            return f.id
+        if isinstance(f, ast.Attribute):
+            parts = []
+            cur: ast.expr = f
+            while isinstance(cur, ast.Attribute):
+                parts.append(cur.attr)
+                cur = cur.value
+            if isinstance(cur, ast.Name):
+                parts.append(cur.id)
+            return ".".join(reversed(parts))
+        return None
+
+    @staticmethod
+    def _const_str(node: ast.expr | None) -> str | None:
+        if node is None:
+            return None
+        if isinstance(node, ast.Constant) and isinstance(node.value, str):
+            return node.value
+        if isinstance(node, ast.Constant) and node.value is None:
+            return "None"
+        if isinstance(node, ast.Name) and node.id == "None":
+            return "None"
+        return repr(node)   # non-literal: store textual representation
+
+    @staticmethod
+    def _const_int(node: ast.expr | None) -> int | None:
+        if isinstance(node, ast.Constant) and isinstance(node.value, int):
+            return node.value
+        return None
+
+    @staticmethod
+    def _const_bool(node: ast.expr | None) -> bool | None:
+        if isinstance(node, ast.Constant) and isinstance(node.value, bool):
+            return node.value
+        if isinstance(node, ast.Name):
+            if node.id == "True":
+                return True
+            if node.id == "False":
+                return False
+        return None
+
+    @staticmethod
+    def _const_list_str(node: ast.expr | None) -> str:
+        if not isinstance(node, (ast.List, ast.Tuple)):
+            return "[]"
+        items = []
+        for elt in node.elts:
+            if isinstance(elt, ast.Constant) and isinstance(elt.value, str):
+                items.append(elt.value)
+        return json.dumps(items)
+
+
+def extract(content: str, file_path: str) -> list[dict]:
+    """
+    Parse one Airflow DAG file and return a list of feature dicts,
+    one per DAG definition found in the file.
+
+    Returns [{"parse_error": ..., "file_lines": ...}] on parse failure.
+    """
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return [{"parse_error": str(exc), "file_lines": file_lines}]
+
+    visitor = _DAGVisitor()
+    try:
+        visitor.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return [{"parse_error": f"visitor: {exc}", "file_lines": file_lines}]
+
+    if not visitor.dags:
+        # No DAG found — could be a helper module in the dags/ folder.
+        return [{"parse_error": "no_dag_found", "file_lines": file_lines}]
+
+    for d in visitor.dags:
+        d["file_lines"] = file_lines
+        d.setdefault("parse_error", None)
+
+    return visitor.dags

Scripts/pipeline_parsers/dagster_parser.py

@@ -0,0 +1,178 @@
+"""
+dagster_parser.py
+~~~~~~~~~~~~~~~~~
+Extracts features from Dagster definition files.
+
+Dagster's API has evolved significantly: pre-1.0 used Solids/Pipelines,
+post-1.0 uses Assets/Ops/Jobs/Graphs.  We detect both sets of decorators
+and mark which paradigm is in use.
+"""
+
+import ast
+
+# Decorator/function name sets per concept
+_ASSET_DECORATORS  = {"asset", "multi_asset", "graph_asset", "observable_source_asset"}
+_OP_DECORATORS     = {"op", "solid"}          # solid = pre-1.0 name
+_JOB_DECORATORS    = {"job", "pipeline"}      # pipeline = pre-1.0
+_GRAPH_DECORATORS  = {"graph"}
+_RESOURCE_DECS     = {"resource", "configured"}
+_SCHEDULE_DECS     = {"schedule", "ScheduleDefinition"}
+_SENSOR_DECS       = {"sensor", "asset_sensor", "multi_asset_sensor",
+                      "run_status_sensor", "run_failure_sensor"}
+_PARTITION_CLASSES = {"DailyPartitionsDefinition", "WeeklyPartitionsDefinition",
+                      "MonthlyPartitionsDefinition", "HourlyPartitionsDefinition",
+                      "StaticPartitionsDefinition", "DynamicPartitionsDefinition",
+                      "MultiPartitionsDefinition", "TimeWindowPartitionsDefinition"}
+_IO_MANAGER_DECS   = {"io_manager", "IOManager"}
+_CONFIG_CLASSES    = {"Config", "RunConfig"}
+_METADATA_FUNCS    = {"MetadataValue", "with_metadata"}
+_FRESHNESS_CLASSES = {"FreshnessPolicy"}
+
+
+def _decorator_names(node: ast.FunctionDef | ast.AsyncFunctionDef | ast.ClassDef
+                     ) -> list[str]:
+    names = []
+    for dec in node.decorator_list:
+        if isinstance(dec, ast.Name):
+            names.append(dec.id)
+        elif isinstance(dec, ast.Attribute):
+            names.append(dec.attr)
+        elif isinstance(dec, ast.Call):
+            f = dec.func
+            if isinstance(f, ast.Name):
+                names.append(f.id)
+            elif isinstance(f, ast.Attribute):
+                names.append(f.attr)
+    return names
+
+
+class _DagsterVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.asset_count        = 0
+        self.op_count           = 0
+        self.job_count          = 0
+        self.graph_count        = 0
+        self.resource_count     = 0
+        self.has_partitions     = False
+        self.has_sensors        = False
+        self.has_schedules      = False
+        self.uses_io_manager    = False
+        self.uses_config_schema = False
+        self.uses_metadata      = False
+        self.has_freshness_policy = False
+        # Anti-pattern: op/solid that returns data without IO manager reference
+        self._op_names:     set[str] = set()
+        self._io_mgr_refs:  int = 0
+
+    def visit_FunctionDef(self, node: ast.FunctionDef) -> None:
+        dnames = set(_decorator_names(node))
+        if dnames & _ASSET_DECORATORS:
+            self.asset_count += 1
+        if dnames & _OP_DECORATORS:
+            self.op_count += 1
+            self._op_names.add(node.name)
+        if dnames & _JOB_DECORATORS:
+            self.job_count += 1
+        if dnames & _GRAPH_DECORATORS:
+            self.graph_count += 1
+        if dnames & _RESOURCE_DECS:
+            self.resource_count += 1
+        if dnames & _IO_MANAGER_DECS:
+            self.uses_io_manager = True
+            self._io_mgr_refs += 1
+        if dnames & _SCHEDULE_DECS:
+            self.has_schedules = True
+        if dnames & _SENSOR_DECS:
+            self.has_sensors = True
+        self.generic_visit(node)
+
+    visit_AsyncFunctionDef = visit_FunctionDef
+
+    def visit_ClassDef(self, node: ast.ClassDef) -> None:
+        dnames = set(_decorator_names(node))
+        if node.name in _PARTITION_CLASSES or any(
+            isinstance(b, ast.Name) and b.id in _PARTITION_CLASSES
+            for b in node.bases
+        ):
+            self.has_partitions = True
+        if dnames & _IO_MANAGER_DECS or node.name in _IO_MANAGER_DECS:
+            self.uses_io_manager = True
+        if node.name in _CONFIG_CLASSES or any(
+            isinstance(b, ast.Name) and b.id in _CONFIG_CLASSES for b in node.bases
+        ):
+            self.uses_config_schema = True
+        if node.name in _FRESHNESS_CLASSES:
+            self.has_freshness_policy = True
+        self.generic_visit(node)
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = ""
+        if isinstance(f, ast.Name):
+            name = f.id
+        elif isinstance(f, ast.Attribute):
+            name = f.attr
+        if name in _PARTITION_CLASSES:
+            self.has_partitions = True
+        if name in _METADATA_FUNCS:
+            self.uses_metadata = True
+        if name in _FRESHNESS_CLASSES:
+            self.has_freshness_policy = True
+        if name in {"ScheduleDefinition", "build_schedule_from_partitioned_job"}:
+            self.has_schedules = True
+        if name in {"SensorDefinition"} or "sensor" in name.lower():
+            self.has_sensors = True
+        # io_manager reference in function call arguments
+        for kw in node.keywords:
+            if kw.arg in ("io_manager", "io_manager_key", "io_manager_def"):
+                self.uses_io_manager = True
+                self._io_mgr_refs += 1
+        self.generic_visit(node)
+
+    @property
+    def antipattern_op_without_io_manager(self) -> int:
+        # Op/solid definitions exist but no IOManager is configured anywhere
+        return int(self.op_count > 0 and self._io_mgr_refs == 0)
+
+    @property
+    def antipattern_no_metadata(self) -> int:
+        return int(self.asset_count > 0 and not self.uses_metadata)
+
+
+def extract(content: str, file_path: str) -> dict:
+    """
+    Parse one Dagster definition file.
+    Returns a feature dict for dagster_features.
+    """
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines}
+
+    v = _DagsterVisitor()
+    try:
+        v.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines}
+
+    return {
+        "asset_count":          v.asset_count,
+        "op_count":             v.op_count,
+        "job_count":            v.job_count,
+        "graph_count":          v.graph_count,
+        "resource_count":       v.resource_count,
+        "has_partitions":       int(v.has_partitions),
+        "has_sensors":          int(v.has_sensors),
+        "has_schedules":        int(v.has_schedules),
+        "uses_io_manager":      int(v.uses_io_manager),
+        "uses_config_schema":   int(v.uses_config_schema),
+        "uses_metadata":        int(v.uses_metadata),
+        "has_freshness_policy": int(v.has_freshness_policy),
+        "antipattern_op_without_io_manager": v.antipattern_op_without_io_manager,
+        "antipattern_no_metadata":           v.antipattern_no_metadata,
+        "file_lines":           file_lines,
+        "parse_error":          None,
+    }

Scripts/pipeline_parsers/dbt_parser.py

@@ -0,0 +1,187 @@
+"""
+dbt_parser.py
+~~~~~~~~~~~~~
+Feature extraction for dbt SQL models and dbt_project.yml / schema.yml files.
+
+SQL parsing uses regex rather than a full SQL parser because dbt models
+are templated Jinja2+SQL, which most parsers reject.  We extract structural
+signals (CTEs, JOINs, window functions, ref/source calls) with targeted
+patterns rather than attempting full syntax analysis.
+"""
+
+import json
+import re
+from pathlib import PurePosixPath
+
+# ── dbt Jinja macro patterns ──────────────────────────────────────────────────
+_REF_RE    = re.compile(r"\{\{\s*ref\s*\(\s*['\"](\w+)['\"]\s*\)\s*\}\}", re.I)
+_SOURCE_RE = re.compile(r"\{\{\s*source\s*\(", re.I)
+_CONFIG_RE = re.compile(r"\{\{\s*config\s*\(([^}]+)\)\s*\}\}", re.I | re.S)
+_MAT_RE    = re.compile(r"materialized\s*=\s*['\"](\w+)['\"]", re.I)
+_UKEY_RE   = re.compile(r"unique_key\s*=", re.I)
+
+# ── SQL structural patterns ───────────────────────────────────────────────────
+_CTE_RE    = re.compile(r"\bWITH\b", re.I)
+_JOIN_RE   = re.compile(r"\b(?:INNER|LEFT|RIGHT|FULL|CROSS)?\s*JOIN\b", re.I)
+_WHERE_RE  = re.compile(r"\bWHERE\b", re.I)
+_WINDOW_RE = re.compile(r"\bOVER\s*\(", re.I)
+_LIMIT_RE  = re.compile(r"\bLIMIT\s+(\d+)\b", re.I)
+_STAR_RE   = re.compile(r"\bSELECT\s+\*", re.I)
+_INCR_RE   = re.compile(r"is_incremental\s*\(\s*\)", re.I)
+# Hardcoded raw table reference (FROM word without ref/source) — rough heuristic
+_RAW_FROM_RE = re.compile(r"\bFROM\s+([a-zA-Z_]\w*(?:\.\w+){1,2})\b", re.I)
+
+# ── Model layer inference from path ──────────────────────────────────────────
+_LAYER_MAP = {
+    "staging":      "staging",
+    "stg":          "staging",
+    "intermediate": "intermediate",
+    "int":          "intermediate",
+    "marts":        "marts",
+    "mart":         "marts",
+    "core":         "marts",
+    "final":        "marts",
+    "reporting":    "marts",
+}
+
+
+def _infer_layer(file_path: str) -> str:
+    parts = PurePosixPath(file_path).parts
+    for part in parts:
+        if part.lower() in _LAYER_MAP:
+            return _LAYER_MAP[part.lower()]
+    return "other"
+
+
+def _extract_materialization(content: str) -> str | None:
+    m = _CONFIG_RE.search(content)
+    if m:
+        inner = m.group(1)
+        mat = _MAT_RE.search(inner)
+        if mat:
+            return mat.group(1).lower()
+    return None
+
+
+def extract_model(content: str, file_path: str) -> dict:
+    """
+    Parse one dbt SQL model file.
+    Returns a feature dict ready for INSERT into dbt_model_features.
+    """
+    lines = content.splitlines()
+    file_lines = len(lines)
+    model_name = PurePosixPath(file_path).stem
+
+    try:
+        ref_count   = len(_REF_RE.findall(content))
+        source_count = len(_SOURCE_RE.findall(content))
+        mat         = _extract_materialization(content)
+        uses_incr   = int(bool(_INCR_RE.search(content)))
+        has_ukey    = int(bool(_UKEY_RE.search(content)))
+        cte_count   = len(_CTE_RE.findall(content))
+        has_join    = int(bool(_JOIN_RE.search(content)))
+        has_where   = int(bool(_WHERE_RE.search(content)))
+        has_window  = int(bool(_WINDOW_RE.search(content)))
+        hardcoded_limit = int(bool(_LIMIT_RE.search(content)))
+        select_star = int(bool(_STAR_RE.search(content)))
+
+        # No ref/source + FROM literal table name = hardcoded raw table
+        raw_froms = _RAW_FROM_RE.findall(content)
+        antipattern_no_src_ref = int(
+            ref_count == 0 and source_count == 0 and len(raw_froms) > 0
+        )
+
+        return {
+            "model_name":           model_name,
+            "model_layer":          _infer_layer(file_path),
+            "materialization":      mat,
+            "ref_count":            ref_count,
+            "source_count":         source_count,
+            "cte_count":            cte_count,
+            "has_where_clause":     has_where,
+            "has_join":             has_join,
+            "has_window_function":  has_window,
+            "uses_incremental":     uses_incr,
+            "has_unique_key":       has_ukey,
+            "hardcoded_limit":      hardcoded_limit,
+            "select_star":          select_star,
+            "file_lines":           file_lines,
+            "antipattern_incremental_no_unique_key": int(uses_incr and not has_ukey),
+            "antipattern_select_star":               select_star,
+            "antipattern_no_source_no_ref":          antipattern_no_src_ref,
+            "parse_error":          None,
+        }
+    except Exception as exc:  # noqa: BLE001
+        return {"model_name": model_name, "parse_error": str(exc),
+                "file_lines": file_lines}
+
+
+# ── dbt_project.yml / schema.yml ─────────────────────────────────────────────
+try:
+    import yaml as _yaml
+    _YAML_OK = True
+except ImportError:
+    _YAML_OK = False
+
+_DBT_VERSION_RE = re.compile(r"require-dbt-version\s*:\s*['\"]?([^\s'\"]+)")
+_MODEL_PATHS_RE = re.compile(r"model-paths\s*:\s*\[([^\]]+)\]")
+
+
+def extract_project(content: str, file_path: str) -> dict:
+    """
+    Parse dbt_project.yml and return a summary dict for dbt_project_summary.
+    """
+    result: dict = {"parse_error": None}
+    fname = PurePosixPath(file_path).name.lower()
+
+    if fname not in ("dbt_project.yml", "dbt_project.yaml"):
+        result["parse_error"] = "not_dbt_project_file"
+        return result
+
+    if _YAML_OK:
+        try:
+            data = _yaml.safe_load(content) or {}
+            result["dbt_version_required"] = str(
+                data.get("require-dbt-version", "")
+            ) or None
+            paths = data.get("model-paths") or data.get("source-paths") or []
+            result["model_paths"] = json.dumps(paths)
+            result["has_tests_dir"] = int("test-paths" in data or "tests" in data)
+            result["has_snapshots"]  = int("snapshot-paths" in data)
+            result["has_seeds"]      = int("seed-paths" in data)
+            result["has_analyses"]   = int("analysis-paths" in data)
+        except Exception as exc:  # noqa: BLE001
+            result["parse_error"] = str(exc)
+    else:
+        # Regex fallback
+        m = _DBT_VERSION_RE.search(content)
+        result["dbt_version_required"] = m.group(1) if m else None
+        result["has_tests_dir"]  = int("test-paths" in content)
+        result["has_snapshots"]  = int("snapshot-paths" in content)
+        result["has_seeds"]      = int("seed-paths" in content)
+        result["has_analyses"]   = int("analysis-paths" in content)
+
+    return result
+
+
+def extract_schema(content: str, file_path: str) -> dict:
+    """
+    Parse a models/**/schema.yml and return per-model test coverage signals.
+    Returns a lightweight dict:  {model_name: has_tests, ...}
+    Caller merges this into dbt_model_features rows.
+    """
+    coverage: dict[str, int] = {}
+    if not _YAML_OK:
+        return coverage
+    try:
+        data = _yaml.safe_load(content) or {}
+        for model in data.get("models", []):
+            name = model.get("name", "")
+            tests = model.get("tests", []) or []
+            col_tests = any(
+                col.get("tests") for col in model.get("columns", [])
+            )
+            coverage[name] = int(bool(tests) or col_tests)
+    except Exception:  # noqa: BLE001
+        pass
+    return coverage

Scripts/pipeline_parsers/other_parsers.py

@@ -0,0 +1,441 @@
+"""
+other_parsers.py
+~~~~~~~~~~~~~~~~
+Feature extractors for Luigi, Kedro, Apache Beam, and dlt.
+
+Each exposes an extract(content, file_path) -> dict function
+matching the contract of the other parser modules.
+"""
+
+import ast
+import json
+import re
+
+# ══════════════════════════════════════════════════════════════════════════════
+# Luigi
+# ══════════════════════════════════════════════════════════════════════════════
+
+_TARGET_TYPES = {
+    "LocalTarget":    "local",
+    "S3Target":       "s3",
+    "GCSTarget":      "gcs",
+    "GCSFlagTarget":  "gcs",
+    "HdfsTarget":     "hdfs",
+    "HdfsFlag":       "hdfs",
+    "AtomicLocalFile": "local",
+    "MockTarget":     "mock",
+    "PostgresTarget": "postgres",
+    "BigQueryTarget": "bigquery",
+}
+
+_LUIGI_EXTERNAL = {"ExternalTask", "ExternalProgram"}
+
+_HARDCODED_PATH_RE = re.compile(
+    r'LocalTarget\s*\(\s*["\']([^"\']+/[^"\']+)["\']',  # literal path with slash
+    re.S,
+)
+
+
+class _LuigiVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.task_count          = 0
+        self.target_types: set[str] = set()
+        self.uses_external_task  = False
+        self.has_dynamic_requires = False
+        self.task_names: list[str] = []
+        self._task_has_run:   set[str] = set()
+        self._task_has_output: set[str] = set()
+        self._requires_nodes: dict[str, ast.FunctionDef] = {}
+
+    def visit_ClassDef(self, node: ast.ClassDef) -> None:
+        is_task = any(
+            (isinstance(b, ast.Name) and (b.id == "Task" or b.id.endswith("Task")))
+            or (isinstance(b, ast.Attribute) and b.attr == "Task")
+            for b in node.bases
+        )
+        is_external = any(
+            isinstance(b, ast.Name) and b.id in _LUIGI_EXTERNAL
+            for b in node.bases
+        )
+        if is_task or is_external:
+            self.task_count += 1
+            self.task_names.append(node.name)
+            if is_external:
+                self.uses_external_task = True
+            # Inspect methods
+            for item in ast.walk(node):
+                if isinstance(item, ast.FunctionDef):
+                    if item.name == "run":
+                        self._task_has_run.add(node.name)
+                    if item.name == "output":
+                        self._task_has_output.add(node.name)
+                    if item.name == "requires":
+                        self._requires_nodes[node.name] = item
+        self.generic_visit(node)
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = ""
+        if isinstance(f, ast.Name):
+            name = f.id
+        elif isinstance(f, ast.Attribute):
+            name = f.attr
+        if name in _TARGET_TYPES:
+            self.target_types.add(_TARGET_TYPES[name])
+        self.generic_visit(node)
+
+    def _check_dynamic_requires(self) -> None:
+        for fname, req_node in self._requires_nodes.items():
+            for n in ast.walk(req_node):
+                # Dynamic requires: list comprehension, yield, or conditional return
+                if isinstance(n, (ast.ListComp, ast.GeneratorExp,
+                                  ast.YieldFrom, ast.Yield)):
+                    self.has_dynamic_requires = True
+                    return
+                if isinstance(n, ast.If):
+                    self.has_dynamic_requires = True
+                    return
+
+    @property
+    def antipattern_missing_output(self) -> int:
+        tasks_with_run_no_output = (
+            self._task_has_run - self._task_has_output - self.uses_external_task_names
+        )
+        return int(bool(tasks_with_run_no_output))
+
+    @property
+    def uses_external_task_names(self) -> set:
+        return set()  # Sentinel; external tasks don't need output()
+
+
+def extract_luigi(content: str, file_path: str) -> dict:
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines}
+
+    v = _LuigiVisitor()
+    try:
+        v.visit(tree)
+        v._check_dynamic_requires()
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines}
+
+    hardcoded = bool(_HARDCODED_PATH_RE.search(content))
+
+    return {
+        "task_count":              v.task_count,
+        "uses_local_target":       int("local" in v.target_types),
+        "uses_s3_target":          int("s3" in v.target_types),
+        "uses_gcs_target":         int("gcs" in v.target_types),
+        "uses_hdfs_target":        int("hdfs" in v.target_types),
+        "uses_external_task":      int(v.uses_external_task),
+        "has_dynamic_requires":    int(v.has_dynamic_requires),
+        "has_run_method":          int(bool(v._task_has_run)),
+        "has_output_method":       int(bool(v._task_has_output)),
+        "antipattern_missing_output":   int(
+            bool(v._task_has_run - v._task_has_output)
+        ),
+        "antipattern_hardcoded_path":   int(hardcoded),
+        "file_lines":              file_lines,
+        "parse_error":             None,
+    }
+
+
+# ══════════════════════════════════════════════════════════════════════════════
+# Kedro
+# ══════════════════════════════════════════════════════════════════════════════
+
+try:
+    import yaml as _yaml
+    _YAML_OK = True
+except ImportError:
+    _YAML_OK = False
+
+
+class _KedroVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.node_count      = 0
+        self.pipeline_count  = 0
+        self.dataset_types: set[str] = set()
+        self.uses_versioning = False
+        self.uses_partitioned = False
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = ""
+        if isinstance(f, ast.Name):
+            name = f.id
+        elif isinstance(f, ast.Attribute):
+            name = f.attr
+        if name == "node":
+            self.node_count += 1
+        if name in ("pipeline", "Pipeline"):
+            self.pipeline_count += 1
+        if "Dataset" in name or "DataSet" in name:
+            self.dataset_types.add(name)
+        if name == "PartitionedDataset" or name == "PartitionedDataSet":
+            self.uses_partitioned = True
+        for kw in node.keywords:
+            if kw.arg == "versioned":
+                if isinstance(kw.value, ast.Constant) and kw.value.value:
+                    self.uses_versioning = True
+        self.generic_visit(node)
+
+
+def extract_kedro(content: str, file_path: str) -> dict:
+    """Parse a Kedro pipeline Python file."""
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines}
+
+    v = _KedroVisitor()
+    try:
+        v.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines}
+
+    return {
+        "node_count":           v.node_count,
+        "pipeline_count":       v.pipeline_count,
+        "dataset_types":        json.dumps(sorted(v.dataset_types)),
+        "uses_versioning":      int(v.uses_versioning),
+        "uses_partitioned_ds":  int(v.uses_partitioned),
+        "file_lines":           file_lines,
+        "parse_error":          None,
+    }
+
+
+def extract_kedro_catalog(content: str, file_path: str) -> dict:
+    """Parse catalog.yml and extract dataset type inventory."""
+    result = {"has_catalog_file": 1, "dataset_types": "[]", "parse_error": None}
+    if not _YAML_OK:
+        result["parse_error"] = "pyyaml_not_installed"
+        return result
+    try:
+        data = _yaml.safe_load(content) or {}
+        types: list[str] = []
+        for ds_name, ds_conf in data.items():
+            if isinstance(ds_conf, dict) and "type" in ds_conf:
+                types.append(ds_conf["type"])
+        result["dataset_types"] = json.dumps(sorted(set(types)))
+        result["uses_versioning"] = int(
+            any(
+                ds_conf.get("versioned") is True
+                for ds_conf in data.values()
+                if isinstance(ds_conf, dict)
+            )
+        )
+        result["uses_partitioned_ds"] = int(
+            any("Partitioned" in t for t in types)
+        )
+    except Exception as exc:  # noqa: BLE001
+        result["parse_error"] = str(exc)
+    return result
+
+
+# ══════════════════════════════════════════════════════════════════════════════
+# Apache Beam
+# ══════════════════════════════════════════════════════════════════════════════
+
+_RUNNER_RE = re.compile(
+    r"(DirectRunner|DataflowRunner|SparkRunner|FlinkRunner|"
+    r"PortableRunner|InteractiveRunner)",
+    re.I,
+)
+
+
+class _BeamVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.ptransform_count   = 0
+        self.pardo_count        = 0
+        self.combinefn_count    = 0
+        self.uses_windowing     = False
+        self.uses_side_inputs   = False
+        self.uses_state_timers  = False
+        self.runner_type: str | None = None
+
+    def visit_ClassDef(self, node: ast.ClassDef) -> None:
+        for base in node.bases:
+            base_name = ""
+            if isinstance(base, ast.Name):
+                base_name = base.id
+            elif isinstance(base, ast.Attribute):
+                base_name = base.attr
+            if base_name == "PTransform" or base_name.endswith("PTransform"):
+                self.ptransform_count += 1
+            if base_name in ("DoFn", "ParDo"):
+                self.pardo_count += 1
+            if base_name == "CombineFn":
+                self.combinefn_count += 1
+            if "StatefulDoFn" in base_name or "Timer" in base_name:
+                self.uses_state_timers = True
+        self.generic_visit(node)
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = ""
+        if isinstance(f, ast.Name):
+            name = f.id
+        elif isinstance(f, ast.Attribute):
+            name = f.attr
+        if name in ("WindowInto", "window", "FixedWindows", "SlidingWindows",
+                    "Sessions", "GlobalWindows"):
+            self.uses_windowing = True
+        if name == "AsSingleton" or name == "AsIter" or name == "AsList":
+            self.uses_side_inputs = True
+        if name in ("ParDo", "FlatMap", "Map"):
+            self.pardo_count += 1
+        self.generic_visit(node)
+
+
+def extract_beam(content: str, file_path: str) -> dict:
+    """Parse an Apache Beam pipeline file."""
+    lines = content.splitlines()
+    file_lines = len(lines)
+
+    runner_match = _RUNNER_RE.search(content)
+    runner = runner_match.group(1) if runner_match else None
+
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines,
+                "runner_type": runner}
+
+    v = _BeamVisitor()
+    v.runner_type = runner
+    try:
+        v.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines,
+                "runner_type": runner}
+
+    return {
+        "ptransform_count":    v.ptransform_count,
+        "pardo_count":         v.pardo_count,
+        "combinefn_count":     v.combinefn_count,
+        "runner_type":         runner,
+        "uses_windowing":      int(v.uses_windowing),
+        "uses_side_inputs":    int(v.uses_side_inputs),
+        "uses_state_and_timers": int(v.uses_state_timers),
+        "file_lines":          file_lines,
+        "parse_error":         None,
+    }
+
+
+# ══════════════════════════════════════════════════════════════════════════════
+# dlt (data load tool)
+# ══════════════════════════════════════════════════════════════════════════════
+
+_DESTINATION_RE = re.compile(
+    r'dlt\.destination\s*\(\s*["\'](\w+)["\']'
+    r'|pipeline\s*\([^)]*destination\s*=\s*(\w+)',
+    re.I,
+)
+_KNOWN_DESTINATIONS = {
+    "bigquery", "snowflake", "redshift", "postgres", "duckdb",
+    "filesystem", "s3", "gcs", "azure", "databricks", "motherduck",
+    "synapse", "clickhouse",
+}
+
+
+class _DltVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.source_count       = 0
+        self.resource_count     = 0
+        self.transformer_count  = 0
+        self.uses_incremental   = False
+        self.uses_schema_contracts = False
+        self.destinations: set[str] = set()
+
+    def _dlt_decorator(self, node: ast.FunctionDef | ast.AsyncFunctionDef) -> None:
+        for dec in node.decorator_list:
+            if isinstance(dec, ast.Attribute):
+                if dec.attr == "source":
+                    self.source_count += 1
+                elif dec.attr == "resource":
+                    self.resource_count += 1
+                elif dec.attr == "transformer":
+                    self.transformer_count += 1
+            elif isinstance(dec, ast.Call):
+                f = dec.func
+                attr = f.attr if isinstance(f, ast.Attribute) else ""
+                if attr == "source":
+                    self.source_count += 1
+                elif attr == "resource":
+                    self.resource_count += 1
+                elif attr == "transformer":
+                    self.transformer_count += 1
+                # Check for incremental in resource decorator
+                for kw in dec.keywords:
+                    if kw.arg == "primary_key" or kw.arg == "merge_key":
+                        self.uses_incremental = True
+
+    def visit_FunctionDef(self, node: ast.FunctionDef) -> None:
+        self._dlt_decorator(node)
+        self.generic_visit(node)
+
+    visit_AsyncFunctionDef = visit_FunctionDef
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = f.attr if isinstance(f, ast.Attribute) else (
+            f.id if isinstance(f, ast.Name) else ""
+        )
+        if name == "pipeline":
+            for kw in node.keywords:
+                if kw.arg == "destination":
+                    dest = (
+                        kw.value.id if isinstance(kw.value, ast.Name) else
+                        kw.value.value if isinstance(kw.value, ast.Constant) else ""
+                    )
+                    if dest:
+                        self.destinations.add(dest.lower())
+        if name == "incremental" or name == "Incremental":
+            self.uses_incremental = True
+        if name in ("SchemaContract", "schema_contract"):
+            self.uses_schema_contracts = True
+        self.generic_visit(node)
+
+
+def extract_dlt(content: str, file_path: str) -> dict:
+    """Parse a dlt pipeline file."""
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines}
+
+    v = _DltVisitor()
+    try:
+        v.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines}
+
+    # Supplement with regex for destination strings in module-level calls
+    for m in _DESTINATION_RE.finditer(content):
+        dest = (m.group(1) or m.group(2) or "").lower()
+        if dest:
+            v.destinations.add(dest)
+
+    return {
+        "source_count":         v.source_count,
+        "resource_count":       v.resource_count,
+        "destination_types":    json.dumps(sorted(v.destinations)),
+        "uses_incremental":     int(v.uses_incremental),
+        "uses_schema_contracts": int(v.uses_schema_contracts),
+        "uses_transformers":    int(v.transformer_count > 0),
+        "file_lines":           file_lines,
+        "parse_error":          None,
+    }

Scripts/pipeline_parsers/prefect_parser.py

@@ -0,0 +1,197 @@
+"""
+prefect_parser.py
+~~~~~~~~~~~~~~~~~
+Extracts features from Prefect flow files (both 1.x and 2.x/3.x APIs).
+
+Prefect 1.x uses class-based flows (@task on free functions, Flow context manager).
+Prefect 2.x/3.x uses @flow and @task decorators directly.
+We detect both patterns via AST.
+"""
+
+import ast
+import json
+from typing import Any
+
+
+def _decorator_names(node: ast.FunctionDef | ast.AsyncFunctionDef) -> list[str]:
+    names = []
+    for dec in node.decorator_list:
+        if isinstance(dec, ast.Name):
+            names.append(dec.id)
+        elif isinstance(dec, ast.Attribute):
+            names.append(dec.attr)
+        elif isinstance(dec, ast.Call):
+            f = dec.func
+            if isinstance(f, ast.Name):
+                names.append(f.id)
+            elif isinstance(f, ast.Attribute):
+                names.append(f.attr)
+    return names
+
+
+def _kw_value(node: ast.Call, name: str) -> ast.expr | None:
+    for kw in node.keywords:
+        if kw.arg == name:
+            return kw.value
+    return None
+
+
+def _const_int(node: ast.expr | None) -> int | None:
+    if isinstance(node, ast.Constant) and isinstance(node.value, int):
+        return node.value
+    return None
+
+
+def _const_bool(node: ast.expr | None) -> bool | None:
+    if isinstance(node, ast.Constant) and isinstance(node.value, bool):
+        return node.value
+    if isinstance(node, ast.Name):
+        return {"True": True, "False": False}.get(node.id)
+    return None
+
+
+class _PrefectVisitor(ast.NodeVisitor):
+
+    def __init__(self) -> None:
+        self.flow_count           = 0
+        self.task_count           = 0
+        self.max_retries          = 0
+        self.has_retries          = False
+        self.has_schedule         = False
+        self.has_timeout          = False
+        self.uses_result_caching  = False
+        self.uses_state_handler   = False
+        self.uses_mapped_tasks    = False
+        self.has_deployment_block = False
+        self.prefect_version      = "unknown"
+        self._imports: set[str]   = set()
+
+    def visit_Import(self, node: ast.Import) -> None:
+        for alias in node.names:
+            self._imports.add(alias.name)
+        self.generic_visit(node)
+
+    def visit_ImportFrom(self, node: ast.ImportFrom) -> None:
+        if node.module:
+            self._imports.add(node.module)
+            # Version detection
+            if node.module.startswith("prefect."):
+                if "deployments" in node.module or "flows" in node.module:
+                    self.prefect_version = "2.x"
+            if node.module == "prefect" and any(
+                a.name in ("flow", "task") for a in node.names
+            ):
+                self.prefect_version = "2.x"
+        self.generic_visit(node)
+
+    def _inspect_flow_decorator(self, dec: ast.expr) -> None:
+        if not isinstance(dec, ast.Call):
+            return
+        if _kw_value(dec, "schedule") is not None:
+            self.has_schedule = True
+        timeout = _kw_value(dec, "timeout_seconds")
+        if timeout is not None:
+            self.has_timeout = True
+
+    def _inspect_task_decorator(self, dec: ast.expr) -> None:
+        if not isinstance(dec, ast.Call):
+            return
+        retries = _kw_value(dec, "retries") or _kw_value(dec, "max_retries")
+        if retries is not None:
+            self.has_retries = True
+            v = _const_int(retries)
+            if v is not None and v > self.max_retries:
+                self.max_retries = v
+        if _kw_value(dec, "cache_key_fn") is not None:
+            self.uses_result_caching = True
+        if _kw_value(dec, "result_storage") is not None:
+            self.uses_result_caching = True
+
+    def visit_FunctionDef(self, node: ast.FunctionDef) -> None:
+        dnames = _decorator_names(node)
+        if "flow" in dnames:
+            self.flow_count += 1
+            for dec in node.decorator_list:
+                self._inspect_flow_decorator(dec)
+        if "task" in dnames:
+            self.task_count += 1
+            for dec in node.decorator_list:
+                self._inspect_task_decorator(dec)
+        self.generic_visit(node)
+
+    visit_AsyncFunctionDef = visit_FunctionDef
+
+    def visit_With(self, node: ast.With) -> None:
+        """Prefect 1.x: with Flow(...) as flow:"""
+        for item in node.items:
+            if isinstance(item.context_expr, ast.Call):
+                f = item.context_expr.func
+                name = f.id if isinstance(f, ast.Name) else (
+                    f.attr if isinstance(f, ast.Attribute) else ""
+                )
+                if name == "Flow":
+                    self.flow_count += 1
+                    self.prefect_version = "1.x"
+                    sched = _kw_value(item.context_expr, "schedule")
+                    if sched is not None:
+                        self.has_schedule = True
+        self.generic_visit(node)
+
+    def visit_Call(self, node: ast.Call) -> None:
+        f = node.func
+        name = ""
+        if isinstance(f, ast.Attribute):
+            name = f.attr
+        # .map() for Prefect 1.x mapped tasks
+        if name == "map":
+            self.uses_mapped_tasks = True
+        # unmapped() for Prefect 2.x mapped tasks
+        if isinstance(f, ast.Name) and f.id == "unmapped":
+            self.uses_mapped_tasks = True
+        # Deployment block
+        if isinstance(f, ast.Name) and f.id in ("Deployment", "deploy"):
+            self.has_deployment_block = True
+        if isinstance(f, ast.Attribute) and f.attr in ("Deployment", "deploy"):
+            self.has_deployment_block = True
+        # State handlers (Prefect 1.x)
+        for kw in node.keywords:
+            if kw.arg == "state_handlers":
+                self.uses_state_handler = True
+        self.generic_visit(node)
+
+
+def extract(content: str, file_path: str) -> dict:
+    """
+    Parse one Prefect flow file.
+    Returns a feature dict for prefect_flow_features.
+    """
+    lines = content.splitlines()
+    file_lines = len(lines)
+    try:
+        tree = ast.parse(content, filename=file_path)
+    except SyntaxError as exc:
+        return {"parse_error": str(exc), "file_lines": file_lines}
+
+    v = _PrefectVisitor()
+    try:
+        v.visit(tree)
+    except Exception as exc:  # noqa: BLE001
+        return {"parse_error": f"visitor: {exc}", "file_lines": file_lines}
+
+    return {
+        "prefect_version":          v.prefect_version,
+        "flow_count":               v.flow_count,
+        "task_count":               v.task_count,
+        "has_retries":              int(v.has_retries),
+        "max_retries":              v.max_retries or None,
+        "has_schedule":             int(v.has_schedule),
+        "has_timeout":              int(v.has_timeout),
+        "uses_result_caching":      int(v.uses_result_caching),
+        "uses_state_handler":       int(v.uses_state_handler),
+        "uses_mapped_tasks":        int(v.uses_mapped_tasks),
+        "has_deployment_block":     int(v.has_deployment_block),
+        "antipattern_no_retries":   int(not v.has_retries),
+        "antipattern_no_timeout":   int(not v.has_timeout),
+        "file_lines":               file_lines,
+        "parse_error":              None,
+    }

Scripts/pipeline_schema.sql

@@ -0,0 +1,231 @@
+-- DEPosit: Pipeline artifact tables
+-- Applied automatically by collect_pipeline_artifacts.py on first run.
+-- Manual init: sqlite3 Data/DE_pipeline_artifacts.db < Scripts/pipeline_schema.sql
+
+-- ── Collection progress (including repos with 0 matched artifacts) ─────────
+CREATE TABLE IF NOT EXISTS repo_scan_status (
+    repo_full_name       TEXT PRIMARY KEY,
+    artifact_file_count  INTEGER NOT NULL,
+    tree_status          TEXT,               -- ok | 404 | empty | truncated | http_*
+    scanned_at           TEXT NOT NULL
+);
+
+-- ── Discovery ──────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS pipeline_files (
+    id                  INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name      TEXT    NOT NULL,
+    file_path           TEXT    NOT NULL,
+    artifact_type       TEXT    NOT NULL,   -- airflow_dag | dbt_model | dbt_schema |
+                                            -- prefect_flow | dagster | luigi |
+                                            -- kedro | beam | dlt | mage_block
+    file_sha            TEXT,               -- git blob SHA
+    file_size_bytes     INTEGER,
+    collected_at        TEXT    NOT NULL,
+    parse_error         TEXT,               -- NULL when parsing succeeded
+    UNIQUE(repo_full_name, file_path)
+);
+
+-- ── Airflow ─────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS airflow_dag_features (
+    id                          INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name              TEXT    NOT NULL,
+    file_path                   TEXT    NOT NULL,
+    dag_id                      TEXT,
+    schedule_interval           TEXT,       -- cron expr, timedelta repr, preset, or NULL
+    schedule_type               TEXT,       -- cron | timedelta | preset | none | dynamic
+    catchup                     INTEGER,    -- 0/1/NULL (NULL = not set, inherits default)
+    max_active_runs             INTEGER,
+    default_retries             INTEGER,
+    default_retry_delay_seconds INTEGER,
+    task_count                  INTEGER,
+    edge_count                  INTEGER,    -- explicit dependency edges
+    unique_operator_count       INTEGER,
+    operator_types              TEXT,       -- JSON array of operator class names
+    has_python_operator         INTEGER,    -- 0/1
+    has_bash_operator           INTEGER,
+    has_external_task_sensor    INTEGER,    -- cross-DAG coupling
+    has_branch_operator         INTEGER,
+    has_trigger_rule            INTEGER,    -- non-default trigger rules
+    uses_xcom                   INTEGER,    -- xcom_push/xcom_pull detected
+    uses_pools                  INTEGER,
+    uses_connections            INTEGER,    -- conn_id parameter present
+    has_sla                     INTEGER,    -- sla= or sla_miss_callback
+    has_on_failure_callback     INTEGER,
+    has_on_success_callback     INTEGER,
+    dag_tags                    TEXT,       -- JSON array
+    -- Anti-pattern flags (directly usable as SE research features)
+    antipattern_catchup_no_maxruns  INTEGER, -- catchup=True with no max_active_runs
+    antipattern_no_retries          INTEGER, -- no retry config anywhere in DAG
+    antipattern_no_failure_cb       INTEGER, -- no failure callback
+    antipattern_no_schedule         INTEGER, -- schedule_interval=None (orphaned DAG)
+    antipattern_bare_xcom           INTEGER, -- xcom used for large data transfer
+    file_lines                  INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── dbt ─────────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS dbt_model_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    model_name              TEXT    NOT NULL,
+    model_layer             TEXT,           -- staging | intermediate | marts | other
+    materialization         TEXT,           -- view | table | incremental | ephemeral | NULL
+    ref_count               INTEGER,        -- upstream dbt model dependencies
+    source_count            INTEGER,        -- raw source references
+    cte_count               INTEGER,        -- WITH clause count
+    has_where_clause        INTEGER,
+    has_join                INTEGER,
+    has_window_function     INTEGER,
+    uses_incremental        INTEGER,
+    has_unique_key          INTEGER,        -- required for safe incremental models
+    hardcoded_limit         INTEGER,        -- LIMIT with literal integer (smell)
+    select_star             INTEGER,        -- SELECT * (smell)
+    has_tests               INTEGER,        -- set from schema.yml via extract_schema
+    file_lines              INTEGER,
+    -- Anti-pattern flags
+    antipattern_incremental_no_unique_key   INTEGER,
+    antipattern_select_star                 INTEGER,
+    antipattern_no_source_no_ref            INTEGER, -- raw table name in FROM (hardcoded)
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+CREATE TABLE IF NOT EXISTS dbt_project_summary (
+    repo_full_name          TEXT    PRIMARY KEY,
+    dbt_version_required    TEXT,
+    model_paths             TEXT,           -- JSON array from dbt_project.yml
+    has_tests_dir           INTEGER,
+    has_snapshots           INTEGER,
+    has_seeds               INTEGER,
+    has_analyses            INTEGER,
+    profile_outputs         TEXT,           -- JSON: target names from profiles.yml if present
+    total_model_files       INTEGER,
+    total_schema_files      INTEGER,
+    FOREIGN KEY(repo_full_name) REFERENCES pipeline_files(repo_full_name)
+);
+
+-- ── Prefect ──────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS prefect_flow_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    prefect_version         TEXT,           -- 1.x | 2.x inferred from imports
+    flow_count              INTEGER,
+    task_count              INTEGER,
+    has_retries             INTEGER,
+    max_retries             INTEGER,
+    has_schedule            INTEGER,
+    has_timeout             INTEGER,
+    uses_result_caching     INTEGER,
+    uses_state_handler      INTEGER,
+    uses_mapped_tasks       INTEGER,        -- .map() or unmapped() pattern
+    has_deployment_block    INTEGER,        -- Prefect 2.x deployment definition
+    -- Anti-patterns
+    antipattern_no_retries          INTEGER,
+    antipattern_no_timeout          INTEGER,
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── Dagster ──────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS dagster_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    asset_count             INTEGER,
+    op_count                INTEGER,
+    job_count               INTEGER,
+    graph_count             INTEGER,
+    resource_count          INTEGER,
+    has_partitions          INTEGER,
+    has_sensors             INTEGER,
+    has_schedules           INTEGER,
+    uses_io_manager         INTEGER,
+    uses_config_schema      INTEGER,
+    uses_metadata           INTEGER,
+    has_freshness_policy    INTEGER,
+    -- Anti-patterns
+    antipattern_op_without_io_manager   INTEGER, -- op returning data without IOManager
+    antipattern_no_metadata             INTEGER,
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── Luigi ────────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS luigi_task_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    task_count              INTEGER,
+    max_requires_depth      INTEGER,        -- longest dependency chain in file
+    uses_local_target       INTEGER,
+    uses_s3_target          INTEGER,
+    uses_gcs_target         INTEGER,
+    uses_hdfs_target        INTEGER,
+    uses_external_task      INTEGER,        -- ExternalTask dependency
+    has_dynamic_requires    INTEGER,        -- requires() returns variable list
+    has_run_method          INTEGER,
+    has_output_method       INTEGER,
+    -- Anti-patterns
+    antipattern_missing_output          INTEGER, -- run() without output()
+    antipattern_hardcoded_path          INTEGER, -- string literal in LocalTarget
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── Kedro ────────────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS kedro_pipeline_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    node_count              INTEGER,
+    pipeline_count          INTEGER,
+    dataset_types           TEXT,           -- JSON array of dataset type strings
+    has_parameters_file     INTEGER,
+    has_catalog_file        INTEGER,
+    uses_versioning         INTEGER,        -- versioned datasets
+    uses_partitioned_ds     INTEGER,
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── Apache Beam ──────────────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS beam_pipeline_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    ptransform_count        INTEGER,        -- custom PTransform subclasses
+    pardo_count             INTEGER,
+    combinefn_count         INTEGER,
+    runner_type             TEXT,           -- DirectRunner | DataflowRunner | SparkRunner
+    uses_windowing          INTEGER,
+    uses_side_inputs        INTEGER,
+    uses_state_and_timers   INTEGER,
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── dlt (data load tool) ────────────────────────────────────────────────────
+CREATE TABLE IF NOT EXISTS dlt_features (
+    id                      INTEGER PRIMARY KEY AUTOINCREMENT,
+    repo_full_name          TEXT    NOT NULL,
+    file_path               TEXT    NOT NULL,
+    source_count            INTEGER,        -- @dlt.source decorated functions
+    resource_count          INTEGER,        -- @dlt.resource decorated functions
+    destination_types       TEXT,           -- JSON array: bigquery, snowflake, etc.
+    uses_incremental        INTEGER,
+    uses_schema_contracts   INTEGER,
+    uses_transformers       INTEGER,        -- @dlt.transformer
+    file_lines              INTEGER,
+    FOREIGN KEY(repo_full_name, file_path) REFERENCES pipeline_files(repo_full_name, file_path)
+);
+
+-- ── Indexes ──────────────────────────────────────────────────────────────────
+CREATE INDEX IF NOT EXISTS idx_pf_repo   ON pipeline_files(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_pf_type   ON pipeline_files(artifact_type);
+CREATE INDEX IF NOT EXISTS idx_adf_repo  ON airflow_dag_features(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_dbt_repo  ON dbt_model_features(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_prf_repo  ON prefect_flow_features(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_dag_repo  ON dagster_features(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_lui_repo  ON luigi_task_features(repo_full_name);
+CREATE INDEX IF NOT EXISTS idx_ked_repo  ON kedro_pipeline_features(repo_full_name);

Scripts/redact_leaked_tokens_in_data.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+"""One-off utility: redact GitHub PAT-like strings in Data/*.csv (in place)."""
+from __future__ import annotations
+
+import re
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+DATA = ROOT / "Data"
+REDACTED = "[REDACTED_GITHUB_TOKEN]"
+
+# Fine-grained and classic PAT shapes; require sufficient length to avoid ghp_import-style false positives.
+_PATTERNS = [
+    re.compile(r"github_pat_[A-Za-z0-9_]{20,}"),
+    re.compile(r"ghp_[A-Za-z0-9]{36,}"),
+    re.compile(r"gho_[A-Za-z0-9]{36,}"),
+    re.compile(r"ghu_[A-Za-z0-9]{36,}"),
+    re.compile(r"ghs_[A-Za-z0-9]{36,}"),
+    re.compile(r"ghr_[A-Za-z0-9]{36,}"),
+]
+
+
+def redact_text(text: str) -> tuple[str, int]:
+    count = 0
+    for pattern in _PATTERNS:
+        text, n = pattern.subn(REDACTED, text)
+        count += n
+    return text, count
+
+
+def process_file(path: Path) -> int:
+    tmp = path.with_suffix(path.suffix + ".redacting")
+    total = 0
+    with open(path, encoding="utf-8", errors="replace") as src, open(
+        tmp, "w", encoding="utf-8", newline=""
+    ) as dst:
+        for line in src:
+            new_line, n = redact_text(line)
+            total += n
+            dst.write(new_line)
+    tmp.replace(path)
+    return total
+
+
+def main() -> None:
+    if not DATA.is_dir():
+        print(f"Missing {DATA}", file=sys.stderr)
+        sys.exit(1)
+    csv_files = sorted(DATA.rglob("*.csv"))
+    grand = 0
+    for path in csv_files:
+        n = process_file(path)
+        if n:
+            print(f"  {path.relative_to(ROOT)}: {n} redaction(s)")
+        grand += n
+    print(f"Done. {grand} token-like string(s) redacted across {len(csv_files)} file(s).")
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,2 @@
+requests>=2.28.0
+pandas>=1.5.0