"""Shared test fixtures."""
from __future__ import annotations
import pytest
from latex_resume_mcp.models.resume import (
ContactInfo,
Education,
Experience,
Project,
Publication,
ResumeData,
ResumeVariant,
SkillCategory,
)
@pytest.fixture
def sample_contact() -> ContactInfo:
return ContactInfo(
name="Danny Willow Liu",
phone="510-876-2949",
email="dannywillowliu@uchicago.edu",
linkedin="linkedin.com/in/dwliu2",
github="github.com/dannywillowliu-uchi",
)
@pytest.fixture
def sample_education() -> list[Education]:
return [
Education(
institution="The University of Chicago",
location="Chicago, IL",
degree="Bachelor of Science in Computer Science (A.I Specialization)",
date="Expected June 2028",
bullets=[
"Coursework: Systems Programming I & II, Machine Learning, Theory of Algorithms",
"Activities: Kappa Theta Pi, TASA, Maroon Capital (Quant Club)",
],
tags=["cs", "ai"],
),
]
@pytest.fixture
def sample_experience() -> list[Experience]:
return [
Experience(
company="E2 Consulting Engineers",
location="Emeryville, CA",
title="Software Engineer Intern",
date="June 2025 -- September 2025",
bullets=[
"Shipped Apache Superset + PostgreSQL dashboard for 600+ projects",
"Built agentic workflows with AWS Bedrock, Lambda, and RAG API",
],
tags=["swe", "cloud"],
),
Experience(
company="Yotta-Labs",
location="Seattle, WA",
title="ML Engineer Intern",
date="June 2025 -- Present",
bullets=[
"Building BloomBee, a decentralized LLM inference platform",
"Developed batched tensor distributed inference sessions",
],
tags=["ml", "distributed"],
),
]
@pytest.fixture
def sample_projects() -> list[Project]:
return [
Project(
name="Prediction Market Information Arbitrage",
technologies="Flask, Playwright, Kalshi/Polymarket APIs",
date="August 2025 -- Present",
bullets=[
"Exploited 2-second delay between live sports and market prices",
"Built cross-correlation analysis on orderbook data",
],
tags=["trading", "swe"],
),
]
@pytest.fixture
def sample_publications() -> list[Publication]:
return [
Publication(
title="Network Effect Prediction Framework for Crypto Technologies",
link="https://github.com/dannywillowliu-uchi/Metcalf_Law_Crypto_Valuation",
date="2025",
bullets=["Extended Metcalfe's Law + Markov-switching models"],
tags=["research", "crypto"],
),
]
@pytest.fixture
def sample_skills() -> list[SkillCategory]:
return [
SkillCategory(category="Languages", skills=["Python", "C", "SQL", "JavaScript"]),
SkillCategory(category="Frameworks", skills=["Flask", "PostgreSQL", "PyTorch"]),
SkillCategory(category="Developer Tools", skills=["Git", "Linux", "Docker"]),
]
@pytest.fixture
def sample_resume_data(
sample_contact: ContactInfo,
sample_education: list[Education],
sample_experience: list[Experience],
sample_projects: list[Project],
sample_publications: list[Publication],
sample_skills: list[SkillCategory],
) -> ResumeData:
return ResumeData(
contact=sample_contact,
education=sample_education,
experience=sample_experience,
projects=sample_projects,
publications=sample_publications,
skills=sample_skills,
)
@pytest.fixture
def sample_variant() -> ResumeVariant:
return ResumeVariant(
name="swe",
description="Software engineering variant",
experience_indices=[0, 1],
project_indices=[0],
publication_indices=[0],
education_indices=[0],
section_order=["education", "publications", "experience", "projects", "skills"],
)
