da-luce · da-luce · Sep 21, 2025 · Sep 17, 2025 · Sep 17, 2025 · Sep 19, 2025
diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml
@@ -3,48 +3,31 @@ name: Deploy Resume
 on:
     push:
         branches: [main]
+    pull_request:
+      branches: [main]
     workflow_dispatch:
-
-env:
-    # These are GitHub Camo image proxy URLs.
-    # To obtain them: paste the raw S3 image link into a GitHub Markdown file (README, issue, etc.),
-    # let GitHub render it, then right-click → "Copy image address".
-    RESUME_IMAGE_URL: "https://camo.githubusercontent.com/19e0bf2e0d1d9b58f0bd2a4bf66b214f817d5ae7e72ff4e3684b8b15522be23f/68747470733a2f2f64616c746f6e2d63762d6172746966616374732e73332e75732d656173742d312e616d617a6f6e6177732e636f6d2f696d616765732f63762e706e67"
-    COVER_LETTER_IMAGE_URL: "https://camo.githubusercontent.com/31c147493e3d013bd48fcbeda87b802e2a8012a64faf6dc324f640ba7eec4f24/68747470733a2f2f64616c746f6e2d63762d6172746966616374732e73332e75732d656173742d312e616d617a6f6e6177732e636f6d2f696d616765732f636f7665725f6c65747465722e706e67"
-
 jobs:
     build-and-deploy:
         runs-on: ubuntu-latest
+        container:
+          image: daluce/cv:latest
+          env:
+            AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
+            AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+            AWS_REGION: ${{ secrets.AWS_REGION }}
 
         steps:
             - name: Checkout source
               uses: actions/checkout@v4
               with:
                   fetch-depth: 0
 
-            - name: Install dependencies
-              run: |
-                  sudo apt-get update
-                  sudo apt-get install -y make texlive-latex-base texlive-latex-extra imagemagick
-
             - name: Build resume
               run: make all
 
-            - name: Upload resume to S3
-              uses: aws-actions/configure-aws-credentials@v4
-              with:
-                  aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
-                  aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-                  aws-region: ${{ secrets.AWS_REGION }}
-
-            - name: Copy PDF + images to S3
-              run: |
-                  aws s3 cp dist/pdfs/ s3://${{ secrets.AWS_S3_BUCKET }}/pdfs/ --recursive
-                  aws s3 cp dist/images/ s3://${{ secrets.AWS_S3_BUCKET }}/images/ --recursive
-
-            # Purge GitHub's Camo CDN cache so updated resume/cover letter images show up immediately
-            # Docs: https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/about-anonymized-urls#removing-an-image-from-camos-cache
-            - name: Clear GitHub Camo cache
-              run: |
-                  curl -X PURGE "${RESUME_IMAGE_URL}"
-                  curl -X PURGE "${COVER_LETTER_IMAGE_URL}"
+            - name: Test
+              run: make test
+            - name: Upload PDFs and images to S3
+            # Only upload on pushes to main branch, not PRs
+              if: github.event_name == 'push'
+              run: make release
diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
@@ -0,0 +1,27 @@
+name: Build and Push Docker Image
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'Dockerfile'
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Log in to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKER_HUB_USERNAME }}
+          password: ${{ secrets.DOCKER_HUB_PASSWORD }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v4
+        with:
+          push: true
+          tags: daluce/cv:latest
+          platforms: linux/amd64
diff --git a/Dockerfile b/Dockerfile
@@ -0,0 +1,15 @@
+FROM python:3.11-slim
+
+RUN apt-get update && apt-get install -y \
+    imagemagick \
+    texlive-latex-base \
+    texlive-latex-extra \
+    git \
+    awscli \
+    make \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install cvlint
+RUN git clone https://github.com/da-luce/cvlint.git
+WORKDIR /cvlint
+RUN pip install .
diff --git a/Makefile b/Makefile
@@ -1,4 +1,4 @@
-.PHONY: all clean build private cover-letter images help install test
+.PHONY: all clean build private cover-letter images help install test release
 
 # Default target
 all: build images
@@ -7,75 +7,82 @@ all: build images
 BUILD_DIR := build
 DIST_DIR := dist
 SRC_DIR := src
+PDF_DIR := $(DIST_DIR)/pdfs
+IMG_DIR := $(DIST_DIR)/images
+CV_NAME := dalton_luce_cv
+COVER_LETTER_NAME := cover_letter
+S3_BUCKET := dalton-cv-artifacts
+AWS_REGION := us-east-1
+
+# These are GitHub Camo image proxy URLs.
+# To obtain them: paste the raw S3 image link into a GitHub Markdown file (README, issue, etc.),
+# let GitHub render it, then right-click → "Copy image address".
+CV_GITHUB_CACHE_URL:= https://camo.githubusercontent.com/19e0bf2e0d1d9b58f0bd2a4bf66b214f817d5ae7e72ff4e3684b8b15522be23f/68747470733a2f2f64616c746f6e2d63762d6172746966616374732e73332e75732d656173742d312e616d617a6f6e6177732e636f6d2f696d616765732f63762e706e67
+COVER_GITHUB_CACHE_URL:= https://camo.githubusercontent.com/31c147493e3d013bd48fcbeda87b802e2a8012a64faf6dc324f640ba7eec4f24/68747470733a2f2f64616c746f6e2d63762d6172746966616374732e73332e75732d656173742d312e616d617a6f6e6177732e636f6d2f696d616765732f636f7665725f6c65747465722e706e67
 
 # Help target
 help:
 	@echo "Available targets:"
-	@echo "  all          - Build CV and cover letter, generate images"
-	@echo "  build        - Build CV (public version)"
-	@echo "  private      - Build CV (private version)"
-	@echo "  cover-letter - Build cover letter only"
-	@echo "  images       - Generate PNG images from PDFs"
-	@echo "  clean        - Remove build directory"
-	@echo "  install      - Install Python dependencies"
-	@echo "  test         - Run tests"
+	@echo "  all            - Build CV and cover letter, then generate images"
+	@echo "  build          - Build public version of the CV"
+	@echo "  private        - Build private version of the CV"
+	@echo "  cover-letter   - Build the cover letter PDF"
+	@echo "  images         - Generate PNG images from PDFs using ImageMagick"
+	@echo "  clean          - Remove all build and distribution artifacts"
+	@echo "  install        - Install Python dependencies (not defined here)"
+	@echo "  test           - Run cvlint on the generated CV PDF"
+	@echo "  release        - Upload PDFs and images to S3, purge GitHub Camo cache"
 
 # Create necessary directories
-$(DIST_DIR)/pdfs $(DIST_DIR)/images:
+$(PDF_DIR) $(IMG_DIR):
 	mkdir -p $@
 
 # Build public CV
-build: $(DIST_DIR)/pdfs cover-letter
-	mkdir -p $(BUILD_DIR)
-	pdflatex -output-directory=$(BUILD_DIR) -jobname=dalton_luce_cv $(SRC_DIR)/cv.tex
-	cp $(BUILD_DIR)/dalton_luce_cv.pdf $(DIST_DIR)/pdfs/
+build: $(PDF_DIR) cover-letter
+	mkdir -p $(PDF_DIR)
+	pdflatex -output-directory=$(BUILD_DIR) -jobname=$(CV_NAME) $(SRC_DIR)/$(CV_NAME).tex
+	cp $(BUILD_DIR)/$(CV_NAME).pdf $(PDF_DIR)
 
 # Build private CV
-private: $(DIST_DIR)/pdfs
+private: $(PDF_DIR)
 	mkdir -p $(BUILD_DIR)
-	pdflatex -output-directory=$(BUILD_DIR) -jobname=dalton_luce_cv '\def\private{} \input{$(SRC_DIR)/cv.tex}'
-	cp $(BUILD_DIR)/dalton_luce_cv.pdf $(DIST_DIR)/pdfs/
+	pdflatex -output-directory=$(BUILD_DIR) -jobname=$(CV_NAME) "\def\\private{} \input{$(SRC_DIR)/$(CV_NAME).tex}"
+	cp $(BUILD_DIR)/$(CV_NAME).pdf $(PDF_DIR)
 
 # Build cover letter
-cover-letter: $(DIST_DIR)/pdfs
+cover-letter: $(PDF_DIR)
 	mkdir -p $(BUILD_DIR)
-	pdflatex -output-directory=$(BUILD_DIR) -jobname=cover_letter $(SRC_DIR)/cover_letter.tex
-	cp $(BUILD_DIR)/cover_letter.pdf $(DIST_DIR)/pdfs/
+	pdflatex -output-directory=$(BUILD_DIR) -jobname=cover_letter $(SRC_DIR)/$(COVER_LETTER_NAME).tex
+	cp $(BUILD_DIR)/$(COVER_LETTER_NAME).pdf $(PDF_DIR)
 
 # Generate images from PDFs
-# FIXME: currently using deprecated "convert" since ubuntu GitHub runners only have access to IMv6
-images: $(DIST_DIR)/images
+images: $(IMG_DIR)
 	@if command -v convert >/dev/null 2>&1; then \
-		convert -density 300 $(DIST_DIR)/pdfs/dalton_luce_cv.pdf -quality 100 -flatten -sharpen 0x1.0 $(DIST_DIR)/images/cv.png; \
-		convert -density 300 $(DIST_DIR)/pdfs/cover_letter.pdf -quality 100 -flatten -sharpen 0x1.0 $(DIST_DIR)/images/cover_letter.png; \
+		magick -density 300 $(DIST_DIR)/pdfs/dalton_luce_cv.pdf -quality 100 -flatten -sharpen 0x1.0 $(IMG_DIR)/$(CV_NAME).png; \
+		magick -density 300 $(DIST_DIR)/pdfs/cover_letter.pdf -quality 100 -flatten -sharpen 0x1.0 $(IMG_DIR)/$(COVER_LETTER_NAME).png; \
 	else \
 		echo "Imageconvert not found. Please install Imageconvert to generate images."; \
 	fi
 
 # Clean build directory
 clean:
-	rm -rf $(BUILD_DIR)
-
-
-# Install Python dependencies in a venv
-install:
-	@if [ ! -d .venv ]; then \
-		echo "Creating virtual environment..."; \
-		python3 -m venv .venv; \
-	fi
-	@echo "Installing dependencies..."
-	@. .venv/bin/activate; \
-	if [ -f pyproject.toml ]; then \
-		pip install --upgrade pip; \
-		pip install -e .; \
-	else \
-		echo "No dependency file found"; \
-	fi
-	@echo ""
-	@echo "✅ Next steps:"
-	@echo "   source .venv/bin/activate"
-	@echo "   (or run commands with .venv/bin/python, e.g. .venv/bin/python -m pytest)"
+	rm -rf $(BUILD_DIR) $(DIST_DIR)
 
 # Run tests
 test:
-	python -m pytest test/test.py
+	@if ! command -v cvlint >/dev/null 2>&1; then \
+		echo "Error: cvlint is not installed or not in PATH."; \
+		echo "Please install cvlint by following instructions at https://github.com/da-luce/cvlint"; \
+		exit 1; \
+	fi
+	cvlint check $(PDF_DIR)/$(CV_NAME).pdf
+
+release:
+	aws s3 cp $(PDF_DIR)/ s3://$(S3_BUCKET)/pdfs/ --recursive --region $(AWS_REGION)
+	aws s3 cp $(IMG_DIR)/ s3://$(S3_BUCKET)/images/ --recursive --region $(AWS_REGION)
+	# Purge GitHub Camo image cache, so updated images show up in README immediately
+	curl -X PURGE "$(CV_GITHUB_CACHE_URL)"
+	curl -X PURGE "$(COVER_GITHUB_CACHE_URL)"
+
+enter:
+	docker run --rm -it --pull always -v "$$(pwd)":/cv -w /cv daluce/cv:latest /bin/bash
diff --git a/README.md b/README.md
@@ -1,19 +1,21 @@
 # 📄 CV [![Deploy Resume](https://github.com/da-luce/cv/actions/workflows/deploy.yml/badge.svg)](https://github.com/da-luce/cv/actions/workflows/deploy.yml)
 
+<br>
 <br>
 
 <p align="center">
   <a href="https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/pdfs/dalton_luce_cv.pdf">
     <img src="https://img.shields.io/badge/📄%20View_PDF-blue?style=for-the-badge&logo=&logoColor=white" alt="View PDF">
   </a>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
-  <a href="https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/images/cv.png">
+  <a href="https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/images/dalton_luce_cv.png">
     <img src="https://img.shields.io/badge/🌄%20View_PNG-blue?style=for-the-badge&logo=&logoColor=white" alt="View PNG">
   </a>
 </p>
 
+<br>
 <br>
 
-My [Curriculum Vitae](https://en.wikipedia.org/wiki/Curriculum_vitae) (CV) and cover letter template, written in $\LaTeX$ ([learn more](https://www.latex-project.org/)). All artifacts (PDFs and preview images) are automatically built using [GitHub Actions](https://github.com/features/actions) and uploaded to an [AWS S3](https://aws.amazon.com/s3/) bucket. A [Terraform](https://developer.hashicorp.com/terraform) configuration and [instructions](#deploying-artifacts-to-aws) are included below if you want to set it up yourself.
+My [Curriculum Vitae](https://en.wikipedia.org/wiki/Curriculum_vitae) and cover letter template, written in $\LaTeX$. All artifacts (PDFs and preview images) are automatically built using GitHub Actions and uploaded to an AWS S3 bucket. A Terraform configuration and [instructions](#deploying-artifacts-to-aws) are included below if you want a similar settup for your own resume.
 
 Is it overengineered? _For most, probably yes._ <br>
 Is it perfect for automation enthusiasts? _Absolutely._ <br>
@@ -23,45 +25,28 @@ Maybe I can convince you to become one too—_[here's why](#why-this-setup)._
 
 ### Curriculum Vitae &nbsp; [![PDF](https://img.shields.io/badge/PDF-blue?style=flat)](https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/pdfs/dalton_luce_cv.pdf)
 
-![CV Image](https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/images/cv.png)
+![CV Image](https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/images/dalton_luce_cv.png)
 
 ### Cover Letter &nbsp; [![PDF](https://img.shields.io/badge/PDF-blue?style=flat)](https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/pdfs/cover_letter.pdf)
 
 ![Cover Letter Image](https://dalton-cv-artifacts.s3.us-east-1.amazonaws.com/images/cover_letter.png)
 
 ## Building
 
-> [!NOTE]
-> Requires `pdflatex` and `imagemagick` (for image generation). On macOS, you can install them with:
->
-> ```shell
-> brew install basictex imagemagick
-> ```
->
-> Then reload your terminal to ensure the binaries are in your PATH.
-
-1. Install Python dependencies for testing:
+1. Enter the development container (this requires Docker)
 
     ```shell
-    make install
+    make enter
     ```
 
-    ```shell
-    source .venv/bin/activate
-    ````
-
-2. Build all outputs
+2. Build and test all outputs
 
     ```shell
-    # Build everything (CV + cover letter + images)
-    make all
+    make all && make test
     ```
 
     To view other available targets, run `make help`.
 
-> [!NOTE]
-> The Makefile builds PDFs and images locally. PDFs and images are uploaded to an [S3](https://aws.amazon.com/s3/) bucket via a [GitHub Action](./.github/workflows/deploy.yml) for easy access.  Storage cost is extremely low: for a 2 MB resume and cover letter, it would be just over a cent for three **years**.
-
 ## Deploying Artifacts to AWS
 
 Follow these steps to set up your AWS account and configure GitHub Actions for automatic CV deployment.
@@ -99,24 +84,17 @@ Follow these steps to set up your AWS account and configure GitHub Actions for a
 
 5. See it in action
 
-   Once the secrets are added, the provided [workflow](./.github/workflows/deploy.yml) will automatically build your CV PDFs and preview images, then upload them to the configured S3 bucket whenever you push changes to the repository.
-
-> **Note:** S3 storage is extremely cheap—effectively pennies for years of CV and cover letter artifacts.
+  Once the secrets are added, the provided [workflow](./.github/workflows/deploy.yml) will automatically build your CV PDFs and preview images, then upload them to the configured S3 bucket whenever you push changes to the repository.
+  You can also run `make release` to upload artifacts to S3.
 
 ## Why This Setup?
 
-| Component     | Why?                                                                                                                                                                                                    |
-| ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Git**       | Tracks every change in fine detail—much more granular than cloud-hosted solutions like Google Drive. Supports collaboration, safe experimentation, and integrates seamlessly with automation workflows. |
-| **LaTeX**     | Produces professional, highly customizable PDFs. Standard in math and engineering fields, and easy to track with Git.                                                                                   |
-| **AWS S3**    | Cheap, reliable hosting. Stores the latest PDFs and images outside the repo (avoiding repo bloat) and provides a stable URL accessible by anyone on the internet.                                       |
-| **Terraform** | Makes AWS setup reproducible and version-controlled. Anyone (including future you) can recreate the environment easily.                                                                                 |
-
-## To be Implemented
-
-* [ ] Improve testing and add to `deploy.yml` action
-* [x] Add Terraform template for AWS setup
-* [x] Add details on AWS usage in README
-* [x] GitHub action to only generate new PDFs/Images on `main` to reduce repo size
-* [x] A more standard build process that works on any OS (✅ Makefile added)
-* [x] Migrate from requirements.txt to pyproject.toml for Python dependencies
+| Component                                                  | Why?                                                                                                                                                                                                    |
+| ---------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [**Git**](https://git-scm.com/)                            | Tracks every change in fine detail—much more granular than cloud-hosted solutions like Google Drive. Supports collaboration, safe experimentation, and integrates seamlessly with automation workflows. |
+| [**LaTeX**](https://www.latex-project.org/)                | Produces professional, highly customizable PDFs. Standard in math and engineering fields, and easy to track with Git.                                                                                   |
+| [**AWS S3**](https://aws.amazon.com/s3/)                   | Cheap (pennies for 2 MB of assets) and reliable hosting. Stores the latest PDFs and images outside the repo (avoiding repo bloat) and provides a stable URL accessible by anyone on the internet.       |
+| [**Terraform**](https://developer.hashicorp.com/terraform) | Makes AWS setup reproducible and version-controlled. Anyone (including future you) can recreate the environment easily.                                                                                 |
+| [**GitHub Actions**](https://github.com/features/actions)  | Automates the build, test, and deployment workflow on every push. Ensures your CV and cover letter are always up-to-date without manual intervention, seamlessly integrating with Git and AWS S3.       |
+| [**cvlint**](https://github.com/da-luce/cvlint)            | Automatically checks your CV for formatting and content issues.                                                                                                                                         |
+| [**Docker**](https://www.docker.com/)                      | Encapsulates all dependencies and tools needed to build your CV into one portable image, guaranteeing the build runs exactly the same anywhere.                                                         |
diff --git a/pyproject.toml b/pyproject.toml