jspeed-meyers

Overall Grade: B+ (Straightforward)

---

Score Breakdown

Category	Score	Weight	Details
CI Complexity	B	30%	Moderate - 3 workflows, ~16 total steps, matrix strategies
Dependency Health	A	40%	Excellent - All dependencies very recent (2025)
Project Structure	B-	20%	Single language (Go) but complex build requirements

jspeed-meyers

Repository Fork Difficulty Grader

A Claude Code tool for assessing the difficulty of forking archived open source projects.

Overview

This tool analyzes a GitHub repository and assigns a grade (A through F) based on how difficult it would be to fork the project, get CI/GitHub Actions running and passing, and update dependencies with CVEs.

Usage

jspeed-meyers

#!/usr/bin/env python3
# Run this script with: source venv/bin/activate && python3 analyze_github_repos.py
"""
Script to analyze GitHub repositories referenced in Wolfi OS melange YAML files
and check which ones are archived.

generated by claude code. Only lightly reviewed and used by John Speed Meyers.
"""

import os

jspeed-meyers

#!/usr/bin/env python3
"""
GitHub Archived Repository Search & Export. Created via Claude Code.

This script searches for GitHub repositories that have:
- More than 10,000 stars
- Are archived

It exports the results to a CSV file with the repository URL and archive date
(using the last push date as a proxy for when it was archived).

jspeed-meyers

➜  ~ syft nvcr.io/nvidia/pytorch:24.02-py3
 ✔ Pulled image                    
 ✔ Loaded image                                                                                     nvcr.io/nvidia/pytorch:24.02-py3
 ✔ Parsed image                                              sha256:43fcc1b74fd54c3598c3c3d569c7ec4f6e93dc78adad06e38783c95e1bfd5c94
 ✔ Cataloged contents                                               57fd547447043b585ed68a43a7f1dfd3d01ea25c821df0b032b9da79ab82a385
   ├── ✔ Packages                        [892 packages]  
   ├── ✔ File digests                    [14,449 files]  
   ├── ✔ File metadata                   [14,449 locations]  
   └── ✔ Executables                     [2,759 executables]  
[0432]  WARN cataloger failed cataloger=javascript-package-cataloger error=failed to parse package.json file: json: cannot unmarshal s

jspeed-meyers

 syft --platform linux/amd64 cgr.dev/chainguard/pytorch-cuda12
 ✔ Pulled image                    
 ✔ Loaded image                                                                             cgr.dev/chainguard/pytorch-cuda12:latest
 ✔ Parsed image                                              sha256:fde1b4b832c4dd0008ba8a49ac886ada4b3bbf3248b438f893e42664d29c9e07
 ✔ Cataloged contents                                               efb7865bb45355ec5582bd8e02f1b14792c03cfdade52b6b1214e8eaf88ac99c
   ├── ✔ Packages                        [69 packages]  
   ├── ✔ File digests                    [19,193 files]  
   ├── ✔ File metadata                   [19,193 locations]  
   └── ✔ Executables                     [432 executables]  
NAME                      VERSION           TYPE                    

jspeed-meyers

import json

import pandas as pd
import requests

YOUR_SHEET_ID = "1ifFaQyNfgC-V0AnubYm9P3btkNwN9rXJNAHiauflHV4"
CSV_URL = f"https://docs.google.com/spreadsheet/ccc?key={YOUR_SHEET_ID}&output=csv"

res = requests.get(url=CSV_URL)
with open("image-names.csv", "wb") as data:

jspeed-meyers

import json
import pandas as pd

pd.options.display.float_format = '{:.4f}'.format

with open("funder_finder_results.jsonl") as f:
    df = pd.DataFrame(json.loads(line) for line in f)
    #print(df.info())
    #print(df.type.value_counts())
    #print(pd.crosstab(df.type, df.funding_type))

jspeed-meyers

import json
import pandas as pd

with open("funder_finder_results.jsonl") as f:
    df = pd.DataFrame(json.loads(line) for line in f)

jspeed-meyers

# find number of top 1000 python packages that have one or more CVEs

import json

# find all packages with a CVE

# Open the JSON file
with open("pyup_io_safety_db_python_cve.json") as file:
    # Load the JSON data
    data = json.load(file)