test: add tests

2026-04-17 15:56:04 -04:00
parent 088e07dee8
commit 74d140e5f8
10 changed files with 1659 additions and 0 deletions
@@ -0,0 +1,230 @@
+"""Tests for paperlib data models."""
+
+import json
+import tempfile
+from datetime import datetime
+from pathlib import Path
+
+import pytest
+
+from paperlib.models import (
+    ConversionStatus,
+    PaperMetadata,
+    PaperSummary,
+    SourceType,
+    SummaryStatus,
+)
+
+
+class TestPaperMetadata:
+    """Test PaperMetadata data model."""
+
+    def test_create_metadata(self):
+        """Test creating a PaperMetadata instance."""
+        metadata = PaperMetadata(
+            paper_id="test-paper-1",
+            source_type=SourceType.LOCAL,
+            title="Test Paper",
+            authors=["Alice Smith", "Bob Jones"],
+            categories=["cs.AI", "stat.ML"],
+            tags=["machine-learning", "ai"],
+            notes="Test notes",
+        )
+
+        assert metadata.paper_id == "test-paper-1"
+        assert metadata.source_type == SourceType.LOCAL
+        assert metadata.title == "Test Paper"
+        assert metadata.authors == ["Alice Smith", "Bob Jones"]
+        assert metadata.categories == ["cs.AI", "stat.ML"]
+        assert metadata.tags == ["machine-learning", "ai"]
+        assert metadata.notes == "Test notes"
+        assert metadata.conversion_status == ConversionStatus.PENDING
+        assert metadata.summary_status == SummaryStatus.NOT_REQUESTED
+
+    def test_to_dict(self):
+        """Test converting metadata to dictionary."""
+        metadata = PaperMetadata(
+            paper_id="test-paper-1",
+            source_type=SourceType.ARXIV,
+            source_id="2212.06340",
+            title="Test Paper",
+            published_date=datetime(2022, 12, 13, 2, 46, 55),
+        )
+
+        data = metadata.to_dict()
+
+        assert data["paper_id"] == "test-paper-1"
+        assert data["source_type"] == "arxiv"
+        assert data["source_id"] == "2212.06340"
+        assert data["title"] == "Test Paper"
+        assert data["published_date"] == "2022-12-13T02:46:55"
+
+    def test_from_dict(self):
+        """Test creating metadata from dictionary."""
+        data = {
+            "paper_id": "test-paper-1",
+            "source_type": "local",
+            "title": "Test Paper",
+            "authors": ["Alice Smith"],
+            "published_date": "2022-12-13T02:46:55",
+            "categories": ["cs.AI"],
+            "pdf_path": "papers/test.pdf",
+            "imported_at": "2022-12-13T02:46:55",
+            "conversion_status": "success",
+            "summary_status": "pending",
+            "tags": ["test"],
+            "notes": "Test notes",
+        }
+
+        metadata = PaperMetadata.from_dict(data)
+
+        assert metadata.paper_id == "test-paper-1"
+        assert metadata.source_type == SourceType.LOCAL
+        assert metadata.title == "Test Paper"
+        assert metadata.authors == ["Alice Smith"]
+        assert metadata.published_date == datetime(2022, 12, 13, 2, 46, 55)
+        assert metadata.conversion_status == ConversionStatus.SUCCESS
+        assert metadata.summary_status == SummaryStatus.PENDING
+
+    def test_save_and_load_file(self):
+        """Test saving and loading metadata from file."""
+        metadata = PaperMetadata(
+            paper_id="test-paper-1",
+            source_type=SourceType.LOCAL,
+            title="Test Paper",
+            authors=["Alice Smith"],
+        )
+
+        with tempfile.NamedTemporaryFile(suffix=".json", delete=False) as tmp:
+            tmp_path = Path(tmp.name)
+
+        try:
+            # Save to file
+            metadata.save_to_file(tmp_path)
+
+            # Verify file exists and contains JSON
+            assert tmp_path.exists()
+            with tmp_path.open() as f:
+                data = json.load(f)
+            assert data["paper_id"] == "test-paper-1"
+
+            # Load from file
+            loaded_metadata = PaperMetadata.load_from_file(tmp_path)
+            assert loaded_metadata.paper_id == "test-paper-1"
+            assert loaded_metadata.title == "Test Paper"
+            assert loaded_metadata.source_type == SourceType.LOCAL
+
+        finally:
+            if tmp_path.exists():
+                tmp_path.unlink()
+
+
+class TestPaperSummary:
+    """Test PaperSummary data model."""
+
+    def test_create_summary(self):
+        """Test creating a PaperSummary instance."""
+        summary = PaperSummary(
+            one_sentence_summary="This paper introduces a new method.",
+            problem_statement="Current methods are inefficient.",
+            method_overview="We propose a novel approach.",
+            main_results="Our method achieves 95% accuracy.",
+            claimed_contributions=["Novel architecture", "Improved performance"],
+            problem_tags=["classification", "optimization"],
+            technique_tags=["neural-networks", "reinforcement-learning"],
+        )
+
+        assert summary.schema_version == "1.0"
+        assert summary.one_sentence_summary == "This paper introduces a new method."
+        assert summary.problem_statement == "Current methods are inefficient."
+        assert summary.claimed_contributions == [
+            "Novel architecture",
+            "Improved performance",
+        ]
+        assert summary.problem_tags == ["classification", "optimization"]
+
+    def test_to_dict(self):
+        """Test converting summary to dictionary."""
+        summary = PaperSummary(
+            one_sentence_summary="Test summary",
+            relevance_to_user=0.85,
+        )
+
+        data = summary.to_dict()
+
+        assert data["schema_version"] == "1.0"
+        assert data["one_sentence_summary"] == "Test summary"
+        assert data["relevance_to_user"] == 0.85
+
+    def test_from_dict(self):
+        """Test creating summary from dictionary."""
+        data = {
+            "schema_version": "1.0",
+            "one_sentence_summary": "Test summary",
+            "problem_statement": "Test problem",
+            "claimed_contributions": ["Test contribution"],
+            "problem_tags": ["test"],
+            "technique_tags": ["neural-networks"],
+            "entities": ["Entity1", "Entity2"],
+        }
+
+        summary = PaperSummary.from_dict(data)
+
+        assert summary.schema_version == "1.0"
+        assert summary.one_sentence_summary == "Test summary"
+        assert summary.problem_statement == "Test problem"
+        assert summary.claimed_contributions == ["Test contribution"]
+        assert summary.entities == ["Entity1", "Entity2"]
+
+    def test_save_and_load_file(self):
+        """Test saving and loading summary from file."""
+        summary = PaperSummary(
+            one_sentence_summary="Test summary",
+            problem_tags=["tag1", "tag2"],
+        )
+
+        with tempfile.NamedTemporaryFile(suffix=".json", delete=False) as tmp:
+            tmp_path = Path(tmp.name)
+
+        try:
+            # Save to file
+            summary.save_to_file(tmp_path)
+
+            # Verify file exists and contains JSON
+            assert tmp_path.exists()
+            with tmp_path.open() as f:
+                data = json.load(f)
+            assert data["one_sentence_summary"] == "Test summary"
+
+            # Load from file
+            loaded_summary = PaperSummary.load_from_file(tmp_path)
+            assert loaded_summary.one_sentence_summary == "Test summary"
+            assert loaded_summary.problem_tags == ["tag1", "tag2"]
+
+        finally:
+            if tmp_path.exists():
+                tmp_path.unlink()
+
+
+class TestEnums:
+    """Test enum types."""
+
+    def test_source_type_values(self):
+        """Test SourceType enum values."""
+        assert SourceType.LOCAL == "local"
+        assert SourceType.ARXIV == "arxiv"
+
+    def test_conversion_status_values(self):
+        """Test ConversionStatus enum values."""
+        assert ConversionStatus.PENDING == "pending"
+        assert ConversionStatus.PROCESSING == "processing"
+        assert ConversionStatus.SUCCESS == "success"
+        assert ConversionStatus.FAILED == "failed"
+
+    def test_summary_status_values(self):
+        """Test SummaryStatus enum values."""
+        assert SummaryStatus.PENDING == "pending"
+        assert SummaryStatus.PROCESSING == "processing"
+        assert SummaryStatus.SUCCESS == "success"
+        assert SummaryStatus.FAILED == "failed"
+        assert SummaryStatus.NOT_REQUESTED == "not_requested"