"""Tests for Pydantic response models"""
import pytest
from pydantic import ValidationError
from linkedin_mcp_server.models import (
JobApplicationTracking,
JobBenefits,
JobCompanyEnrichment,
JobCompleteSkills,
JobCore,
JobDecisionMaking,
JobDescriptionInsights,
JobEmploymentDetails,
JobFullDescription,
JobMetadata,
JobResponse,
)
def test_job_core_required_fields():
"""Test JobCore with all required fields"""
core = JobCore(
job_id="123",
title="ML Engineer",
company="Anthropic",
location="San Francisco, CA",
posted_date="2 days ago",
posted_date_iso="2026-02-13T10:00:00Z",
)
assert core.job_id == "123"
assert core.title == "ML Engineer"
assert core.company == "Anthropic"
assert core.location == "San Francisco, CA"
assert core.posted_date == "2 days ago"
assert core.posted_date_iso == "2026-02-13T10:00:00Z"
def test_job_core_missing_fields():
"""Test JobCore raises error when required fields missing"""
with pytest.raises(ValidationError):
JobCore(job_id="123", title="ML Engineer")
def test_job_decision_making_defaults():
"""Test JobDecisionMaking with default values"""
decision = JobDecisionMaking()
assert decision.salary_range is None
assert decision.remote_eligible is False
assert decision.visa_sponsorship is False
assert decision.applicants is None
assert decision.easy_apply is False
def test_job_decision_making_custom_values():
"""Test JobDecisionMaking with custom values"""
decision = JobDecisionMaking(
salary_range="$150K - $200K",
remote_eligible=True,
visa_sponsorship=True,
applicants="50-100 applicants",
easy_apply=True,
)
assert decision.salary_range == "$150K - $200K"
assert decision.remote_eligible is True
assert decision.visa_sponsorship is True
assert decision.applicants == "50-100 applicants"
assert decision.easy_apply is True
def test_job_description_insights_defaults():
"""Test JobDescriptionInsights with default values"""
insights = JobDescriptionInsights()
assert insights.description_summary is None
assert insights.key_requirements == []
assert insights.key_responsibilities_preview is None
def test_job_description_insights_custom_values():
"""Test JobDescriptionInsights with custom values"""
insights = JobDescriptionInsights(
description_summary="Seeking ML Engineer...",
key_requirements=["Python", "TensorFlow", "5+ years experience"],
key_responsibilities_preview="Build ML pipelines",
)
assert insights.description_summary == "Seeking ML Engineer..."
assert len(insights.key_requirements) == 3
assert "Python" in insights.key_requirements
assert insights.key_responsibilities_preview == "Build ML pipelines"
def test_job_application_tracking():
"""Test JobApplicationTracking model"""
tracking = JobApplicationTracking(
application_status="applied",
applied_at="2026-02-10T10:00:00Z",
application_notes="Applied via LinkedIn",
)
assert tracking.application_status == "applied"
assert tracking.applied_at == "2026-02-10T10:00:00Z"
assert tracking.application_notes == "Applied via LinkedIn"
def test_job_company_enrichment():
"""Test JobCompanyEnrichment model"""
enrichment = JobCompanyEnrichment(
company_size="1000-5000 employees",
company_industry="Artificial Intelligence",
company_description="AI safety and research",
company_website="https://anthropic.com",
company_headquarters="San Francisco, CA",
company_founded=2021,
company_specialties=["AI Safety", "LLMs", "Alignment"],
)
assert enrichment.company_size == "1000-5000 employees"
assert enrichment.company_founded == 2021
assert len(enrichment.company_specialties) == 3
def test_job_metadata():
"""Test JobMetadata model"""
metadata = JobMetadata(
job_url="https://linkedin.com/jobs/view/123",
scraped_at="2026-02-15T10:00:00Z",
last_seen="2026-02-15T10:00:00Z",
seniority_level="Entry level",
employment_type="Full-time",
)
assert metadata.job_url == "https://linkedin.com/jobs/view/123"
assert metadata.seniority_level == "Entry level"
assert metadata.employment_type == "Full-time"
def test_job_full_description():
"""Test JobFullDescription model"""
desc = JobFullDescription(description="We are seeking an ML Engineer...")
assert desc.description == "We are seeking an ML Engineer..."
def test_job_complete_skills():
"""Test JobCompleteSkills model"""
skills = JobCompleteSkills(
skills_required=["Python", "TensorFlow"],
skills_preferred=["PyTorch", "AWS"],
)
assert len(skills.skills_required) == 2
assert len(skills.skills_preferred) == 2
assert "Python" in skills.skills_required
def test_job_benefits():
"""Test JobBenefits model"""
benefits = JobBenefits(benefits=["Health insurance", "401(k)", "Remote work"])
assert len(benefits.benefits) == 3
assert "Remote work" in benefits.benefits
def test_job_employment_details():
"""Test JobEmploymentDetails model"""
details = JobEmploymentDetails(
workplace_type="Remote",
experience_level="Mid-Senior level",
industry="Technology",
)
assert details.workplace_type == "Remote"
assert details.experience_level == "Mid-Senior level"
assert details.industry == "Technology"
def test_job_response_minimal():
"""Test JobResponse with only required sections (core + decision_making)"""
core = JobCore(
job_id="123",
title="ML Engineer",
company="Anthropic",
location="San Francisco, CA",
posted_date="2 days ago",
posted_date_iso="2026-02-13T10:00:00Z",
)
decision = JobDecisionMaking(remote_eligible=True)
response = JobResponse(core=core, decision_making=decision)
assert response.core.job_id == "123"
assert response.decision_making.remote_eligible is True
assert response.description_insights is None
assert response.application_tracking is None
assert response.company_enrichment is None
assert response.metadata is None
assert response.full_description is None
assert response.complete_skills is None
assert response.benefits is None
assert response.employment_details is None
def test_job_response_full():
"""Test JobResponse with all sections"""
core = JobCore(
job_id="123",
title="ML Engineer",
company="Anthropic",
location="San Francisco, CA",
posted_date="2 days ago",
posted_date_iso="2026-02-13T10:00:00Z",
)
decision = JobDecisionMaking(
salary_range="$150K - $200K",
remote_eligible=True,
visa_sponsorship=True,
applicants="50-100 applicants",
easy_apply=True,
)
insights = JobDescriptionInsights(
description_summary="Seeking ML Engineer...",
key_requirements=["Python", "TensorFlow"],
key_responsibilities_preview="Build ML pipelines",
)
tracking = JobApplicationTracking(application_status="applied")
enrichment = JobCompanyEnrichment(company_size="1000-5000 employees")
metadata = JobMetadata(seniority_level="Entry level")
full_desc = JobFullDescription(description="Full description...")
skills = JobCompleteSkills(skills_required=["Python"])
benefits = JobBenefits(benefits=["Health insurance"])
emp_details = JobEmploymentDetails(workplace_type="Remote")
response = JobResponse(
core=core,
decision_making=decision,
description_insights=insights,
application_tracking=tracking,
company_enrichment=enrichment,
metadata=metadata,
full_description=full_desc,
complete_skills=skills,
benefits=benefits,
employment_details=emp_details,
)
assert response.core.job_id == "123"
assert response.decision_making.remote_eligible is True
assert response.description_insights.description_summary == "Seeking ML Engineer..."
assert response.application_tracking.application_status == "applied"
assert response.company_enrichment.company_size == "1000-5000 employees"
assert response.metadata.seniority_level == "Entry level"
assert response.full_description.description == "Full description..."
assert response.complete_skills.skills_required == ["Python"]
assert response.benefits.benefits == ["Health insurance"]
assert response.employment_details.workplace_type == "Remote"
def test_job_response_serialization_exclude_none():
"""Test JobResponse serialization with exclude_none=True"""
core = JobCore(
job_id="123",
title="ML Engineer",
company="Anthropic",
location="San Francisco, CA",
posted_date="2 days ago",
posted_date_iso="2026-02-13T10:00:00Z",
)
decision = JobDecisionMaking(remote_eligible=True)
insights = JobDescriptionInsights(description_summary="Seeking ML Engineer...")
response = JobResponse(
core=core, decision_making=decision, description_insights=insights
)
# Serialize with exclude_none=True
data = response.model_dump(exclude_none=True)
# Verify core and decision_making are present
assert "core" in data
assert "decision_making" in data
assert "description_insights" in data
# Verify None optional sections are excluded
assert "application_tracking" not in data
assert "company_enrichment" not in data
assert "metadata" not in data
assert "full_description" not in data
assert "complete_skills" not in data
assert "benefits" not in data
assert "employment_details" not in data
def test_job_response_serialization_include_all():
"""Test JobResponse serialization without exclude_none"""
core = JobCore(
job_id="123",
title="ML Engineer",
company="Anthropic",
location="San Francisco, CA",
posted_date="2 days ago",
posted_date_iso="2026-02-13T10:00:00Z",
)
decision = JobDecisionMaking(remote_eligible=True)
response = JobResponse(core=core, decision_making=decision)
# Serialize without exclude_none
data = response.model_dump()
# Verify all fields are present (including None values)
assert "core" in data
assert "decision_making" in data
assert "description_insights" in data
assert data["description_insights"] is None
assert "application_tracking" in data
assert data["application_tracking"] is None
