CV Creator

Generate professionally designed, ATS-optimized PDF CVs from structured data.

Features

• ATS-Optimized: Single-column layout that applicant tracking systems can parse
• Professional Design: F-pattern eye-tracking layout with proper typographic hierarchy
• Customizable: Choose accent colors and page size (Letter/A4)
• Pure Python: No system dependencies, works everywhere

Installation

pip install cv-creator-ats

Quick Start

from cv_creator import CVData, ContactInfo, ExperienceEntry, generate_cv

# Create contact information
contact = ContactInfo(
    name="Jane Doe",
    email="jane.doe@email.com",
    phone="+1-555-0123",
    city="San Francisco, CA",
    linkedin="linkedin.com/in/janedoe",
    portfolio="janedoe.com"
)

# Create experience entries
experience = [
    ExperienceEntry(
        company="Tech Corp",
        title="Senior Software Engineer",
        start_date="Jan 2020",
        end_date="Present",
        bullets=[
            "Led team of 5 engineers building microservices architecture",
            "Reduced API latency by 40% through optimization",
            "Mentored 3 junior developers"
        ]
    )
]

# Build CV data
cv_data = CVData(
    contact=contact,
    summary="Experienced software engineer with 5+ years building scalable systems",
    experience=experience,
    skills=["Python", "JavaScript", "AWS", "Docker", "React"],
    accent_color="#1a2e5a",  # Navy blue
    page_size="letter"        # or "a4"
)

# Generate PDF
pdf_path = generate_cv(cv_data, output_dir="/tmp")
print(f"CV generated: {pdf_path}")

Usage with Claude Web

Claude can install this package and generate CVs directly:

# Claude will do this automatically:
pip install cv-creator-ats

from cv_creator import CVData, ContactInfo, generate_cv

# ... collect CV data from conversation ...

pdf_path = generate_cv(cv_data, output_dir="/mnt/user-data/outputs")
present_files(pdf_path)  # Shows PDF as artifact

Data Models

CVData

Main container for all CV information.

Fields:

• contact (ContactInfo, required)
• summary (str, optional)
• experience (list[ExperienceEntry], optional)
• skills (list[str], optional)
• education (list[EducationEntry], optional)
• certifications (list[CertificationEntry], optional)
• projects (list[ProjectEntry], optional)
• languages (list[LanguageEntry], optional)
• accent_color (str, default: "#1a2e5a") - Hex color code
• page_size (str, default: "letter") - "letter" or "a4"

ContactInfo

Fields:

• name (str, required)
• email (str, required)
• phone (str, required)
• city (str, required)
• linkedin (str, optional)
• portfolio (str, optional)

ExperienceEntry

Fields:

• company (str, required)
• title (str, required)
• start_date (str, required) - e.g., "Jan 2020"
• end_date (str, required) - e.g., "Present"
• bullets (list[str], max 5)

EducationEntry

Fields:

• institution (str, required)
• degree (str, required)
• field (str, required)
• end_date (str, required)
• gpa (str, optional)

Other Models

See models.py for complete model definitions:

• LanguageEntry
• CertificationEntry
• ProjectEntry

Design Principles

The CV follows research-backed design principles:

1. F-Pattern Layout: Important information in the top-left "hot zone"
2. Single Column: ATS-friendly, no tables or columns that confuse parsers
3. Typographic Hierarchy: Clear visual distinction between sections
4. Professional Fonts: Inter (if available) with Helvetica fallback
5. Optimal Margins: 0.75 inch margins for readability

Font Support

The package works with system fonts (Helvetica) by default. For the best appearance, you can optionally place Inter font files in the assets/ directory:

• Inter-Regular.ttf
• Inter-Bold.ttf

Download from: https://fonts.google.com/specimen/Inter

Requirements

• Python >= 3.10
• reportlab >= 4.0.0

License

MIT License - see LICENSE file for details

Author

Alejandro Cuartas

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.