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Author SHA1 Message Date
agent-company 44a162056d Add API tests for export endpoints (CSV and PDF)
Covers GET /export/{company_name} and /export/{company_name}/pdf with
13 test cases: successful export, 404 on missing data, auth enforcement,
filename sanitization, XML-special character handling in PDF, and
multi-row output validation.

Closes leeworks-agents/SPARC#1655

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-20 19:11:42 +00:00
2 changed files with 300 additions and 118 deletions
+76 -118
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@@ -7,131 +7,86 @@ Semiconductor Patent & Analytics Report Core -- development priorities.
SPARC is a patent analysis platform with a working end-to-end pipeline:
Python/FastAPI backend, React/TypeScript frontend, PostgreSQL for persistence
and caching, Docker Compose for local development, and Gitea Actions CI/CD for
image builds and testing. Core features include patent retrieval via SerpAPI,
PDF parsing, LLM analysis via OpenRouter (multi-model: Claude, GPT-4o, Gemini,
Llama), batch processing, JWT authentication, analytics dashboard with patent
trend charts, scheduled recurring analysis with alerting, webhook notifications
(Slack/Discord), CSV and PDF export, S3/MinIO storage, side-by-side company
comparison, and dark mode.
---
## Completed
Items that have been implemented and merged into main.
### Security hardening
- ~~Rotate default JWT secret.~~ Startup check refuses to start with the
default secret in non-development environments.
- ~~CORS allow-origins are hardcoded.~~ Allowed origins are now configurable
via environment variable.
- ~~Database credentials in docker-compose.yml.~~ Compose references `.env`
for sensitive values.
### Error handling and resilience
- ~~`get_db_client()` creates a new `DatabaseClient` on every call.~~ Refactored
to a shared pooled singleton initialized at startup.
- ~~No rate limiting on auth endpoints.~~ Rate limiting middleware added to
`/auth/login` and `/auth/register`.
### Test coverage
- ~~API tests bypass authentication.~~ JWT auth integration tests added (33
cases covering registration, login, protected routes, token refresh, and
admin-only endpoints).
- ~~No test stage in CI.~~ Gitea Actions workflow now runs `pytest` and gates
the build.
- ~~No linting or type checking in CI.~~ `ruff` (Python) and `tsc --noEmit`
(TypeScript) added to CI pipeline.
### Backend
- ~~Add structured logging.~~ Python `logging` module used throughout.
- ~~Make LLM model configurable.~~ `MODEL` environment variable accepted;
multi-model support with per-analysis selection (GPT-4o, Gemini, Claude,
Llama).
- ~~SERP cache TTL hardcoded.~~ `SERP_CACHE_TTL_HOURS` exposed as env var.
- ~~Patent PDF storage.~~ S3/MinIO object storage backend added alongside
local filesystem. Volume mount requirement documented.
- ~~`analyze_single_patent` assumes local file.~~ Auto-download from cached
metadata link integrated.
- ~~`Patent.patent_id` typed as `int`.~~ Fixed to `str`.
### Frontend
- ~~No loading/error states.~~ Skeleton loaders and error states added to
Batch and Analytics pages.
- ~~No dark mode.~~ Full dark mode support with theme-aware chart colors.
- ~~Missing lockfile.~~ `package-lock.json` committed.
### Features (formerly P3)
- ~~Export analysis reports.~~ CSV and PDF export endpoints implemented.
- ~~Comparison view.~~ Side-by-side company patent portfolio comparison added.
- ~~Scheduled/recurring analysis.~~ APScheduler-based periodic re-analysis
with configurable interval and change-threshold alerting.
- ~~Webhook/notification support.~~ Slack, Discord, and generic HTTP POST
webhooks with retry logic.
- ~~Multi-model support.~~ Model picker in Analysis and Batch pages; backend
allow-list validation.
- ~~Patent trend charts.~~ Filing frequency and category distribution
visualizations added to Analytics page.
- ~~OpenAPI client generation.~~ TypeScript API client auto-generated from
FastAPI spec with CI freshness check.
image builds. Core features (patent retrieval via SerpAPI, PDF parsing, LLM
analysis via OpenRouter/Claude, batch processing, JWT authentication, analytics
dashboard) are all implemented and functional.
---
## P1 -- High Priority
These items address correctness, reliability, and coverage gaps that should be
These items address correctness, security, and reliability gaps that should be
resolved before broader production use.
### Resilience
### Security hardening
- **`_jobs` dict is in-memory only.** Job state is lost on API restart.
Persist job status in PostgreSQL or Redis so async batch results survive
restarts.
- **Rotate default JWT secret.** `auth.py` ships a fallback
`sparc-secret-key-change-in-production` that will be used if `JWT_SECRET` is
unset. Add a startup check that refuses to start with the default secret in
non-development environments.
- **CORS allow-origins are hardcoded.** `api.py` only permits
`localhost:3000` and `localhost:5173`. Make the allowed origins configurable
via environment variable so the dashboard works when deployed behind a real
domain.
- **Database credentials in docker-compose.yml.** The compose file embeds
`postgres:postgres` in plain text. Reference a `.env` file or Docker secrets
instead.
### Test coverage gaps
### Error handling and resilience
- **Export endpoint tests.** The CSV and PDF export endpoints (`/export/`)
lack test coverage. Add tests covering auth, success, 404, and edge cases.
*(Issue #1655)*
- **Tracked company admin endpoint tests.** The `/admin/tracked` CRUD
endpoints and scheduler integration lack test coverage. *(Issue #1656)*
- **`get_db_client()` in `auth.py` creates a new `DatabaseClient` on every
call.** This bypasses the connection pool and can exhaust database
connections under load. Refactor to share a single pooled client.
- **`_jobs` dict is in-memory only.** Job state is lost on API restart. Persist
job status in PostgreSQL or Redis so async batch results survive restarts.
- **No rate limiting on auth endpoints.** `/auth/login` and `/auth/register`
are unprotected against brute-force or abuse. Add rate limiting middleware.
### Test coverage for auth and admin
- The existing API tests (`tests/test_api.py`) bypass authentication entirely.
Add tests that exercise the JWT flow: registration, login, protected-route
access, token refresh, and admin-only endpoints.
---
## P2 -- Medium Priority
Improvements to reliability, test coverage, and code quality.
Improvements to usability, performance, and developer experience.
### Test coverage
### Backend
- **Webhook integration tests.** The retry logic, Slack/Discord payload
format, and multi-URL dispatch in `webhooks.py` need test coverage.
*(Issue #1657)*
- **S3/MinIO storage backend tests.** `storage.py` has local filesystem tests
but no unit tests for the S3 backend (read, write, exists, delete,
error handling). *(Issue #1660)*
- **`analyze_single_patent` auto-download path tests.** The auto-download
fallback (cache lookup, PDF download, FileNotFoundError) in
`analyzer.py` lacks test coverage. *(Issue #1661)*
- **Add structured logging.** Replace `print()` calls throughout `analyzer.py`,
`serp_api.py`, and `llm.py` with Python `logging` so log levels and
formatting are consistent.
- **Make LLM model configurable.** `llm.py` hardcodes
`anthropic/claude-3.5-sonnet`. Accept a `MODEL` environment variable to allow
switching models without code changes.
- **SERP cache TTL is hardcoded to 24 hours.** Expose `SERP_CACHE_TTL_HOURS`
as an environment variable in `config.py`.
- **Patent PDF storage.** PDFs are saved to a local `patents/` directory. For
containerized deployments, consider object storage (S3/MinIO) or at minimum
document the volume mount requirement more prominently.
- **`analyze_single_patent` assumes local file path.** The method constructs
`patents/{patent_id}.pdf` and reads from disk, but does not download the PDF
first. Either integrate the download step or document the prerequisite.
- **`Patent.patent_id` typed as `int` in `types.py` but used as `str`
everywhere.** Fix the type annotation to `str`.
### Code quality
### Frontend
- **Scheduler creates its own DatabaseClient.** `scheduler.py` bypasses the
application-level pooled client, creating a new connection on every tick.
Refactor to use `get_db_client()`. *(Issue #1658)*
- **No loading/error states on several pages.** The Batch and Analytics pages
would benefit from skeleton loaders and user-friendly error messages.
- **No dark mode.** Tailwind is configured but no dark variant is applied.
- **Missing `package-lock.json` or `pnpm-lock.yaml`.** The frontend has no
lockfile committed, leading to non-reproducible builds.
### API improvements
### CI/CD
- **API pagination.** The `/analyze/batch` and `/jobs` endpoints could benefit
from cursor-based pagination for large result sets.
- **Request validation improvements.** Add stricter input validation for
company names (disallow special characters, enforce length limits).
- **No test stage in the Gitea Actions workflow.** `build.yaml` builds and
pushes images but never runs `pytest`. Add a test job that gates the build.
- **No linting or type checking.** Add `ruff` (Python) and `tsc --noEmit`
(TypeScript) to CI.
---
@@ -139,20 +94,23 @@ Improvements to reliability, test coverage, and code quality.
Lower-urgency enhancements and future features.
- **Historical analysis diffing.** Show what changed between two analysis runs
for the same company, highlighting new patents and score shifts.
- **Patent classification tagging.** Automatically tag patents by technology
domain (AI, semiconductors, materials science) using LLM classification.
- **User-level API keys.** Allow users to generate personal API keys for
programmatic access without JWT token refresh.
- **Batch export.** Export analysis results for multiple companies at once as
a ZIP archive.
- **Rate limiting dashboard.** Surface rate limit status and usage statistics
in the admin panel.
- **Async webhook delivery.** Move webhook delivery to a background task queue
(e.g., Celery, arq) to avoid blocking the scheduler.
- **Multi-tenant support.** Scope analysis results and tracked companies per
user or organization.
- **Export analysis reports.** Allow users to download analysis results as PDF
or CSV from the dashboard.
- **Comparison view.** Side-by-side comparison of two companies' patent
portfolios.
- **Scheduled/recurring analysis.** Periodically re-analyze tracked companies
and alert on significant changes.
- **Webhook/notification support.** Send alerts (Slack, Discord, email) when
batch jobs complete or when a company's innovation score changes
significantly.
- **Multi-model support.** Let users choose between LLM providers per analysis
(e.g., GPT-4o, Gemini, Claude) and compare outputs.
- **Patent trend charts.** Visualize patent filing frequency and technology
category distribution over time in the Analytics page.
- **API pagination.** The `/analyze/batch` and `/jobs` endpoints could benefit
from cursor-based pagination for large result sets.
- **OpenAPI client generation.** Auto-generate the TypeScript API client from
the FastAPI OpenAPI spec to keep frontend types in sync.
---
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@@ -0,0 +1,224 @@
"""Tests for export endpoints: CSV and PDF export of analysis results.
Covers issue #1655:
- GET /export/{company_name} (CSV export)
- GET /export/{company_name}/pdf (PDF export)
All tests mock the database layer and use JWT auth fixtures from test_auth patterns.
"""
from datetime import datetime, timezone
from unittest.mock import MagicMock, patch
import pytest
from fastapi.testclient import TestClient
from SPARC.api import app
from SPARC.auth import create_access_token
@pytest.fixture
def client():
"""Create test client."""
return TestClient(app)
@pytest.fixture(autouse=True)
def mock_db():
"""Mock the database client used by export and auth endpoints."""
db = MagicMock()
# Default: user exists for auth
db.get_user_by_id.return_value = {
"id": 1,
"email": "user@test.com",
"role": "user",
"created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
}
# Mock get_conn for export queries
mock_cursor = MagicMock()
mock_conn = MagicMock()
mock_conn.cursor.return_value.__enter__ = MagicMock(return_value=mock_cursor)
mock_conn.cursor.return_value.__exit__ = MagicMock(return_value=False)
db.get_conn.return_value.__enter__ = MagicMock(return_value=mock_conn)
db.get_conn.return_value.__exit__ = MagicMock(return_value=False)
db._mock_cursor = mock_cursor
with patch("SPARC.api.get_db_client", return_value=db), \
patch("SPARC.auth.get_db_client", return_value=db):
yield db
def _auth_header():
"""Create an Authorization header with a valid access token."""
token = create_access_token(1, "user@test.com", "user")
return {"Authorization": f"Bearer {token}"}
def _sample_rows():
"""Return sample llm_messages rows as tuples (matching cursor.fetchall format)."""
return [
(
"NVIDIA",
"company_analysis",
"anthropic/claude-3.5-sonnet",
"Strong AI patent portfolio with focus on GPU architectures.",
datetime(2025, 6, 15, 10, 30, 0),
),
(
"NVIDIA",
"patent_analysis",
"openai/gpt-4o",
"Patent US-12345678-B2 covers novel tensor core design.",
datetime(2025, 6, 14, 9, 0, 0),
),
]
class TestCSVExport:
"""GET /export/{company_name} -- CSV export."""
def test_csv_export_success(self, client, mock_db):
"""Valid company with results returns a CSV file."""
mock_db._mock_cursor.fetchall.return_value = _sample_rows()
response = client.get("/export/NVIDIA", headers=_auth_header())
assert response.status_code == 200
assert response.headers["content-type"].startswith("text/csv")
assert "attachment" in response.headers.get("content-disposition", "")
assert "sparc_nvidia_export.csv" in response.headers["content-disposition"]
# Verify CSV content (CSV uses \r\n line endings)
lines = response.text.strip().split("\n")
assert len(lines) == 3 # header + 2 data rows
assert lines[0].strip() == "company_name,analysis_type,model,analysis,timestamp"
assert "NVIDIA" in lines[1]
assert "company_analysis" in lines[1]
def test_csv_export_no_results_returns_404(self, client, mock_db):
"""Unknown company returns 404."""
mock_db._mock_cursor.fetchall.return_value = []
response = client.get("/export/nonexistent", headers=_auth_header())
assert response.status_code == 404
assert "No analysis results found" in response.json()["detail"]
def test_csv_export_unauthenticated_returns_401(self, client):
"""Request without token returns 401."""
response = client.get("/export/NVIDIA")
assert response.status_code == 401
def test_csv_export_invalid_token_returns_401(self, client):
"""Request with invalid token returns 401."""
response = client.get(
"/export/NVIDIA",
headers={"Authorization": "Bearer invalid.token.here"},
)
assert response.status_code == 401
def test_csv_export_filename_sanitization(self, client, mock_db):
"""Company names with spaces get sanitized in the filename."""
mock_db._mock_cursor.fetchall.return_value = [
(
"Tesla Motors",
"company_analysis",
"anthropic/claude-3.5-sonnet",
"EV patent portfolio analysis.",
datetime(2025, 6, 15, 10, 0, 0),
),
]
response = client.get("/export/Tesla Motors", headers=_auth_header())
assert response.status_code == 200
assert "tesla_motors" in response.headers["content-disposition"]
def test_csv_export_single_row(self, client, mock_db):
"""Single analysis result produces valid CSV with one data row."""
mock_db._mock_cursor.fetchall.return_value = [_sample_rows()[0]]
response = client.get("/export/NVIDIA", headers=_auth_header())
assert response.status_code == 200
lines = response.text.strip().split("\n")
assert len(lines) == 2 # header + 1 data row
class TestPDFExport:
"""GET /export/{company_name}/pdf -- PDF report export."""
def test_pdf_export_success(self, client, mock_db):
"""Valid company with results returns a PDF file."""
mock_db._mock_cursor.fetchall.return_value = _sample_rows()
response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
assert response.status_code == 200
assert response.headers["content-type"] == "application/pdf"
assert "attachment" in response.headers.get("content-disposition", "")
# PDF files start with %PDF
assert response.content[:4] == b"%PDF"
def test_pdf_export_no_results_returns_404(self, client, mock_db):
"""Unknown company returns 404."""
mock_db._mock_cursor.fetchall.return_value = []
response = client.get("/export/nonexistent/pdf", headers=_auth_header())
assert response.status_code == 404
assert "No analysis results found" in response.json()["detail"]
def test_pdf_export_unauthenticated_returns_401(self, client):
"""Request without token returns 401."""
response = client.get("/export/NVIDIA/pdf")
assert response.status_code == 401
def test_pdf_export_invalid_token_returns_401(self, client):
"""Request with invalid token returns 401."""
response = client.get(
"/export/NVIDIA/pdf",
headers={"Authorization": "Bearer invalid.token.here"},
)
assert response.status_code == 401
def test_pdf_export_filename_contains_date(self, client, mock_db):
"""PDF filename includes the analysis date."""
mock_db._mock_cursor.fetchall.return_value = _sample_rows()
response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
assert response.status_code == 200
disposition = response.headers["content-disposition"]
assert "nvidia-analysis-" in disposition
assert ".pdf" in disposition
def test_pdf_export_special_chars_in_response(self, client, mock_db):
"""Analysis text with XML-special chars (<, >, &) does not break PDF generation."""
rows = [
(
"TestCo",
"company_analysis",
"anthropic/claude-3.5-sonnet",
"Revenue > $1B & growth <20% for Q4. Test <html> escaping.",
datetime(2025, 6, 15, 10, 0, 0),
),
]
mock_db._mock_cursor.fetchall.return_value = rows
response = client.get("/export/TestCo/pdf", headers=_auth_header())
assert response.status_code == 200
assert response.content[:4] == b"%PDF"
def test_pdf_export_multiple_analyses(self, client, mock_db):
"""Multiple analysis records produce a valid PDF with content."""
mock_db._mock_cursor.fetchall.return_value = _sample_rows()
response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
assert response.status_code == 200
# PDF should have reasonable size (more than just headers)
assert len(response.content) > 500