Brian Bondy's Website

This is the source code for brianbondy.com, a personal website built with Go.

Development

Prerequisites

• Go 1.19+
• Python 3.7+ (for image processing scripts)
• cwebp tool (for WebP image conversion)

Installation

1. Clone the repository
2. Install the cwebp tool:

   # macOS
   brew install webp
   
   # Ubuntu/Debian
   sudo apt-get install webp
   
   # CentOS/RHEL
   sudo yum install libwebp-tools

Running Locally

go run .

The site will be available at http://localhost:8080

Testing

make test

Formatting

make format

Cheatsheets

To fetch the latest cheatsheets markdown from https://github.com/bbondy/cheatsheets and generate the local manifest:

make cheatsheets

This writes data/cheatsheetsManifest.json and data/markdown/cheatsheets/*.md.

Deployment

make deploy

Blog Post Workflow

Adding a New Blog Post

1. Create a new markdown file in data/markdown/blog/ with the next available ID
2. Add the blog post metadata to data/blogPostManifest.json
3. Add images to static/img/blogpost_[ID]/ directory
4. Process the images for WebP optimization:

   make blog-images [ID]

   Or process all blog post images:

   make blog-images

5. Test locally: go run .
6. Run tests: make test
7. Deploy: make deploy

Image Processing

The website automatically optimizes images for better performance by:

• Converting images to WebP format
• Adding lazy loading
• Adding async decoding
• Providing responsive image support

Manual Image Processing

Convert all images to WebP:

make webp

Force convert all images (even if WebP already exists):

make webp-force

Process images for a specific blog post:

python3 scripts/process_new_blog_images.py [blog_post_id]

Image Processing Scripts

• scripts/convert_images_to_webp.py - Main WebP conversion script
• scripts/process_new_blog_images.py - Blog post specific image processing
• scripts/download_strava_images.py - Download images from Strava activities
• scripts/generate_books.py - Generate book data from Goodreads export

Project Structure

• data/ - Blog posts, projects, and other content
• static/ - CSS, images, and other static assets
• templates/ - HTML templates
• scripts/ - Utility scripts for content management
• handlers.go - HTTP request handlers
• routes.go - URL routing
• utils.go - Utility functions including image optimization

Prerequisites

• Go 1.18+
• Python 3 (for scripts)
• golangci-lint (brew install golangci-lint)
• Google Cloud SDK (for deployment)

Adding a Blog Post

1. Create a new markdown file in data/markdown/blog/.
2. Add an entry to data/blogPostManifest.json with the new post's metadata.
3. (Optional) Add images to static/img/blogpost_<id>/.

Format & Lint

To check for linting issues without fixing them:

make lint

To automatically format and fix linting issues:

make format

Testing

To run all tests:

make test

Deployment

Authenticate with Google Cloud (if you haven't already):

make auth

Then deploy:

make deploy

Updating book list

Download an export from https://www.goodreads.com/review/import and save it to data/goodreads_library_export.csv.

Run python3 scripts/generate_books.py

Where to publish blog posts

• Facebook page and related groups (Adjust visibility to Public)
• Twitter
• LinkedIn
• Strava (if about running)

License

See LICENSE.

Running Data Automation

Auto-Fetching Run Times from Strava

The script scripts/fetch_memorable_runs.py helps automate the process of adding elapsed time (hours and minutes) to each running activity in data/memorableRuns.json.

Features:

• Extracts time from the description if present (and cleans up duplicates)
• If time is missing, fetches the elapsed time from the public Strava activity web page (no API credentials required)
• Updates the manifest with a "time" field for each activity
• Cleans up the description to avoid duplicate time display

Requirements:

• Python 3
• requests and beautifulsoup4 libraries (install with pip install requests beautifulsoup4)

Usage:

python3 scripts/fetch_memorable_runs.py

After running, your data/memorableRuns.json will be updated with time fields for each activity. Activities without a Strava activity URL or with non-standard pages will be flagged for manual review.

Update Strava Run Manifest (Contribution Graph)

The contribution graph on the running page is generated from data/stravaRunManifest.json.

Requirements:

• Strava API access (either STRAVA_ACCESS_TOKEN, or STRAVA_CLIENT_ID + STRAVA_CLIENT_SECRET + STRAVA_REFRESH_TOKEN)

Usage:

make strava-run-manifest

If the token is missing or expired, set one of the following before running:

STRAVA_ACCESS_TOKEN=... make strava-run-manifest

Or use refresh-token credentials (no browser login):

STRAVA_CLIENT_ID=... STRAVA_CLIENT_SECRET=... STRAVA_REFRESH_TOKEN=... make strava-run-manifest

Or use OAuth client credentials (opens a browser for login when refresh token is not provided):

STRAVA_CLIENT_ID=... STRAVA_CLIENT_SECRET=... make strava-run-manifest

Auto-Fetching GitHub Project Stats

The script scripts/fetch_github_stats.py automates fetching commit and pull request counts for your projects from GitHub and updates data/projectManifest.json.

Features:

• Scrapes GitHub search pages for commit and PR counts by author (bbondy)
• Supports keyword-based filtering for subprojects (see searchKeywords in the manifest)
• Handles abbreviated numbers (e.g., "2.3k" → 2300)
• Retries on rate limiting with exponential backoff
• Waits 2 seconds between all requests to avoid rate limits
• Only includes real fetched data (removes stats if not available)

Requirements:

• Python 3
• requests library (install with pip install requests)

Usage:

python3 scripts/fetch_github_stats.py

After running, your data/projectManifest.json will be updated with the latest commit and PR counts for each project. If a project's data can't be fetched (e.g., due to rate limiting), it will be omitted from the stats until a successful fetch.