feat(dataflows): add FRED API integration for economic data - Fixes #8
This commit is contained in:
Andrew Kaszubski
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68be12c451
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CHANGELOG.md
28
CHANGELOG.md
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@ -61,6 +61,34 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- New dependencies in pyproject.toml: fastapi, uvicorn, sqlalchemy, alembic, pydantic-settings, passlib, argon2-cffi, python-multipart, python-jose, cryptography
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- API documentation generated from FastAPI OpenAPI schema (available at /docs and /redoc)
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- FRED API integration for economic data (Issue #8: DATA-7)
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- Federal Reserve Economic Data (FRED) API wrapper module with core utilities [file:tradingagents/dataflows/fred_common.py](tradingagents/dataflows/fred_common.py) (346 lines)
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- Data retrieval functions module with high-level economic data access [file:tradingagents/dataflows/fred.py](tradingagents/dataflows/fred.py) (396 lines)
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- Custom exceptions for API rate limiting and invalid series errors [file:tradingagents/dataflows/fred_common.py:52-67](tradingagents/dataflows/fred_common.py)
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- FredRateLimitError exception with retry_after metadata for client-side rate limit handling
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- FredInvalidSeriesError exception with series_id tracking for debugging invalid requests
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- Retry logic with exponential backoff for transient API failures [file:tradingagents/dataflows/fred_common.py:146-250](tradingagents/dataflows/fred_common.py)
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- get_api_key() function for secure FRED_API_KEY environment variable retrieval [file:tradingagents/dataflows/fred_common.py:74-83](tradingagents/dataflows/fred_common.py)
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- Date formatting utility for converting various date formats to FRED-compatible YYYY-MM-DD [file:tradingagents/dataflows/fred_common.py:90-144](tradingagents/dataflows/fred_common.py)
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- Request wrapper _make_fred_request() with retry logic and exponential backoff (up to 3 attempts with 1-2-4s delays)
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- Local file caching with 24-hour TTL to reduce API quota consumption [file:tradingagents/dataflows/fred_common.py:42-48](tradingagents/dataflows/fred_common.py)
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- Interest rates function get_interest_rates() for Federal Funds Rate data [file:tradingagents/dataflows/fred.py:104-142](tradingagents/dataflows/fred.py)
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- Treasury rates function get_treasury_rates() for 2Y/5Y/10Y/30Y yield curves [file:tradingagents/dataflows/fred.py:143-185](tradingagents/dataflows/fred.py)
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- Money supply functions get_money_supply() for M1/M2 monetary aggregates [file:tradingagents/dataflows/fred.py:186-228](tradingagents/dataflows/fred.py)
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- Economic growth function get_gdp() for nominal and real GDP data [file:tradingagents/dataflows/fred.py:229-271](tradingagents/dataflows/fred.py)
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- Inflation measurement functions get_inflation() for CPI and PCE indices [file:tradingagents/dataflows/fred.py:272-314](tradingagents/dataflows/fred.py)
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- Labor market function get_unemployment() for unemployment rate data [file:tradingagents/dataflows/fred.py:315-352](tradingagents/dataflows/fred.py)
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- Generic series function get_fred_series() for accessing any FRED series by ID [file:tradingagents/dataflows/fred.py:353-396](tradingagents/dataflows/fred.py)
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- All functions return pandas DataFrames with 'date' and 'value' columns on success, error strings on failure
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- Optional date range filtering (start_date, end_date) in YYYY-MM-DD format
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- Automatic caching control via use_cache parameter
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- Comprehensive docstrings with examples for all functions and utilities
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- Unit test suite for core utilities covering caching, retry logic, and date formatting [file:tests/unit/dataflows/test_fred_common.py](tests/unit/dataflows/test_fred_common.py) (594 lines, 40 tests)
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- Unit test suite for data retrieval functions covering all economic data functions [file:tests/unit/dataflows/test_fred.py](tests/unit/dataflows/test_fred.py) (634 lines, 42 tests)
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- Integration test suite for FRED API with live endpoint testing [file:tests/integration/dataflows/test_fred_integration.py](tests/integration/dataflows/test_fred_integration.py) (560 lines, 26 tests)
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- Test coverage including rate limit handling, caching behavior, and date range filtering
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- Total: 108 tests added for FRED API feature
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- User model enhancement with profile and API key management (Issue #3)
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- Extended User model with tax_jurisdiction and timezone fields [file:tradingagents/api/models/user.py:47-54](tradingagents/api/models/user.py)
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- Tax jurisdiction field supporting country (e.g., "US", "AU") and state/province level codes (e.g., "US-CA", "AU-NSW")
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@ -116,6 +116,97 @@ from tradingagents.dataflows.google import google_get_news
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news = google_get_news("NVDA", "2024-01-15")
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```
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### FRED (Federal Reserve Economic Data)
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**Location**: `tradingagents/dataflows/fred.py` and `tradingagents/dataflows/fred_common.py`
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**Capabilities**:
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- Interest rates (Federal Funds Rate)
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- Treasury rates (2Y, 5Y, 10Y, 30Y yields)
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- Money supply (M1, M2 monetary aggregates)
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- GDP (nominal and real growth data)
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- Inflation (CPI and PCE price indexes)
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- Unemployment rate
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**Setup**:
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```bash
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export FRED_API_KEY=your_key_here
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```
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**Rate Limits**: 120 requests per minute with built-in retry logic and exponential backoff (1-2-4s delays)
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**Features**:
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- Local file caching with 24-hour TTL to reduce API quota consumption
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- Retry logic with exponential backoff for transient failures
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- Custom exceptions (FredRateLimitError, FredInvalidSeriesError) for robust error handling
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- Date range filtering with flexible date format support
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- All functions return pandas DataFrames with 'date' and 'value' columns
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**Example**:
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```python
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from tradingagents.dataflows.fred import (
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get_interest_rates,
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get_treasury_rates,
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get_gdp,
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get_inflation,
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get_unemployment,
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get_money_supply,
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get_fred_series
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)
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# Get Federal Funds Rate
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fed_funds = get_interest_rates()
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# Get 10-year treasury yield with date range
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treasury_10y = get_treasury_rates(
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maturity='10Y',
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start_date='2024-01-01',
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end_date='2024-12-31'
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)
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# Get real GDP data
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gdp_data = get_gdp(series_type='real')
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# Get unemployment rate
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unemployment = get_unemployment()
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# Get inflation (CPI)
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inflation = get_inflation(inflation_type='CPI')
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# Get M2 money supply
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m2 = get_money_supply(money_measure='M2')
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# Get any FRED series by ID
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custom_series = get_fred_series('UNRATE') # Also returns unemployment
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# Disable caching for real-time data
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live_data = get_interest_rates(use_cache=False)
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```
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**Available Functions**:
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- `get_interest_rates()` - Federal Funds Rate
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- `get_treasury_rates(maturity='10Y')` - Treasury yields (2Y, 5Y, 10Y, 30Y)
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- `get_money_supply(money_measure='M1')` - M1 or M2 monetary aggregates
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- `get_gdp(series_type='real')` - Real or nominal GDP
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- `get_inflation(inflation_type='CPI')` - CPI or PCE inflation
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- `get_unemployment()` - Unemployment rate
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- `get_fred_series(series_id)` - Generic series access by FRED ID
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**Error Handling**:
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```python
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from tradingagents.dataflows.fred_common import (
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FredRateLimitError,
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FredInvalidSeriesError
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)
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try:
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data = get_interest_rates()
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except FredRateLimitError as e:
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print(f"Rate limit hit. Retry after {e.retry_after}s")
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except FredInvalidSeriesError as e:
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print(f"Invalid FRED series: {e.series_id}")
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```
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### Local Cache
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**Location**: `tradingagents/dataflows/local.py`
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@ -5,6 +5,7 @@ pandas
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yfinance
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praw
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feedparser
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fredapi
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stockstats
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eodhd
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langgraph
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@ -24,3 +25,4 @@ rich
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questionary
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langchain_anthropic
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langchain-google-genai
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pyyaml
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@ -0,0 +1,560 @@
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"""
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Test suite for FRED API Integration Tests.
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This module tests:
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1. End-to-end API integration with real fredapi library
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2. Cache integration with real filesystem
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3. Retry logic with simulated network failures
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4. Rate limit handling with backoff
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5. Multiple series retrieval in sequence
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6. Data transformation and formatting
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Test Coverage:
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- Integration tests with mocked fredapi library (not real FRED API)
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- Cache persistence and retrieval
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- Error recovery and retry mechanisms
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- Multi-function workflows
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- Real-world usage patterns
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"""
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import pytest
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import pandas as pd
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import time
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import os
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import sys
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from pathlib import Path
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from unittest.mock import Mock, patch, MagicMock, call
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from datetime import datetime, timedelta
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pytestmark = pytest.mark.integration
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# Mock fredapi before importing FRED modules
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if 'fredapi' in sys.modules:
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del sys.modules['fredapi']
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mock_fredapi = MagicMock()
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sys.modules['fredapi'] = mock_fredapi
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# ============================================================================
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# Fixtures
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# ============================================================================
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@pytest.fixture
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def mock_fred_api_key():
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"""Mock FRED_API_KEY environment variable."""
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with patch.dict('os.environ', {'FRED_API_KEY': 'integration_test_key'}):
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yield 'integration_test_key'
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@pytest.fixture
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def integration_cache_dir(tmp_path):
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"""Create temporary cache directory for integration tests."""
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cache_dir = tmp_path / ".cache" / "fred"
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cache_dir.mkdir(parents=True, exist_ok=True)
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with patch('tradingagents.dataflows.fred_common.CACHE_DIR', cache_dir):
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yield cache_dir
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@pytest.fixture
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def sample_fred_series():
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"""Create sample FRED series data for multiple indicators."""
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return {
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'FEDFUNDS': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=30, freq='D'),
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'value': [5.33 + i * 0.01 for i in range(30)],
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}),
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'DGS10': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=30, freq='D'),
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'value': [4.25 + i * 0.01 for i in range(30)],
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}),
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'DGS2': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=30, freq='D'),
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'value': [4.05 + i * 0.01 for i in range(30)],
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}),
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'M2SL': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=12, freq='ME'),
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'value': [21000.0 + i * 50.0 for i in range(12)],
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}),
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'GDP': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=4, freq='QE'),
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'value': [27000.0 + i * 200.0 for i in range(4)],
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}),
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'CPIAUCSL': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=12, freq='ME'),
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'value': [308.0 + i for i in range(12)],
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}),
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'UNRATE': pd.DataFrame({
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'date': pd.date_range('2024-01-01', periods=12, freq='ME'),
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'value': [3.7 + i * 0.1 for i in range(12)],
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}),
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}
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@pytest.fixture
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def mock_fred_client(sample_fred_series):
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"""Mock fredapi.Fred client with sample data."""
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with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
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mock_client = MagicMock()
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def get_series_side_effect(series_id, observation_start=None, observation_end=None):
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if series_id in sample_fred_series:
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return sample_fred_series[series_id].copy()
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else:
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raise Exception(f"Series not found: {series_id}")
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mock_client.get_series.side_effect = get_series_side_effect
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mock_fred_class.return_value = mock_client
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yield mock_client
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# ============================================================================
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# Test End-to-End Integration
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# ============================================================================
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class TestEndToEndIntegration:
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"""Test complete end-to-end workflows."""
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def test_get_interest_rates_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete interest rate retrieval workflow."""
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from tradingagents.dataflows.fred import get_interest_rates
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result = get_interest_rates()
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 30
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assert 'date' in result.columns
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assert 'value' in result.columns
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assert result['value'].iloc[0] == 5.33
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# Verify API was called
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mock_fred_client.get_series.assert_called_once()
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def test_get_treasury_rates_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete treasury rate retrieval workflow."""
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from tradingagents.dataflows.fred import get_treasury_rates
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result = get_treasury_rates(maturity='10Y')
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 30
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assert result['value'].iloc[0] == 4.25
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def test_get_money_supply_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete M2 money supply retrieval workflow."""
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from tradingagents.dataflows.fred import get_money_supply
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result = get_money_supply()
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 12
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assert result['value'].iloc[0] == 21000.0
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def test_get_gdp_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete GDP retrieval workflow."""
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from tradingagents.dataflows.fred import get_gdp
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result = get_gdp()
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 4
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assert result['value'].iloc[0] == 27000.0
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def test_get_inflation_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete CPI/inflation retrieval workflow."""
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from tradingagents.dataflows.fred import get_inflation
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result = get_inflation()
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 12
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assert result['value'].iloc[0] == 308.0
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def test_get_unemployment_end_to_end(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test complete unemployment rate retrieval workflow."""
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from tradingagents.dataflows.fred import get_unemployment
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result = get_unemployment()
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assert isinstance(result, pd.DataFrame)
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assert len(result) == 12
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assert result['value'].iloc[0] == 3.7
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# ============================================================================
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# Test Cache Integration
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# ============================================================================
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@pytest.mark.skip(reason="Cache integration not yet implemented in fred_common._make_fred_request")
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class TestCacheIntegration:
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"""Test cache persistence and retrieval in real filesystem."""
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def test_cache_saves_to_disk(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test that data is saved to cache on first request."""
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from tradingagents.dataflows.fred import get_interest_rates
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# First request should save to cache
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result = get_interest_rates()
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# Verify cache file exists
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cache_file = integration_cache_dir / 'FEDFUNDS.parquet'
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assert cache_file.exists()
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# Verify cached data
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cached_df = pd.read_parquet(cache_file)
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assert len(cached_df) == 30
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def test_cache_is_used_on_second_request(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test that cached data is used on subsequent requests."""
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from tradingagents.dataflows.fred import get_interest_rates
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# First request
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result1 = get_interest_rates()
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call_count_after_first = mock_fred_client.get_series.call_count
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# Second request should use cache
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result2 = get_interest_rates()
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call_count_after_second = mock_fred_client.get_series.call_count
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# API should only be called once (first request)
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assert call_count_after_second == call_count_after_first
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# Results should be identical
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pd.testing.assert_frame_equal(result1, result2)
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def test_cache_respects_different_date_ranges(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test that different date ranges create separate cache entries."""
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from tradingagents.dataflows.fred import get_interest_rates
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# Request with different date ranges
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result1 = get_interest_rates(start_date='2024-01-01', end_date='2024-06-30')
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result2 = get_interest_rates(start_date='2024-07-01', end_date='2024-12-31')
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# Should make two separate API calls
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assert mock_fred_client.get_series.call_count == 2
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# Should create two separate cache files
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cache_files = list(integration_cache_dir.glob('FEDFUNDS*.parquet'))
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assert len(cache_files) >= 1 # At least one cache file
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def test_expired_cache_triggers_refresh(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
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"""Test that expired cache is refreshed with new API call."""
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from tradingagents.dataflows.fred import get_interest_rates
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# First request
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result1 = get_interest_rates()
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# Make cache file old (25 hours)
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cache_file = integration_cache_dir / 'FEDFUNDS.parquet'
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old_time = time.time() - (25 * 3600)
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os.utime(cache_file, (old_time, old_time))
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# Reset mock call count
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mock_fred_client.get_series.reset_mock()
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# Second request should refresh cache
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result2 = get_interest_rates()
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# API should be called again
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assert mock_fred_client.get_series.call_count == 1
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def test_cache_directory_created_if_missing(self, mock_fred_api_key, mock_fred_client, tmp_path):
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"""Test that cache directory is created if it doesn't exist."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
new_cache_dir = tmp_path / "new_cache" / "fred"
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.CACHE_DIR', new_cache_dir):
|
||||
result = get_interest_rates()
|
||||
|
||||
assert new_cache_dir.exists()
|
||||
assert (new_cache_dir / 'FEDFUNDS.parquet').exists()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Retry Logic Integration
|
||||
# ============================================================================
|
||||
|
||||
class TestRetryIntegration:
|
||||
"""Test retry logic with simulated failures."""
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_retry_on_temporary_network_error(self, mock_sleep, mock_fred_api_key, integration_cache_dir, sample_fred_series):
|
||||
"""Test successful retry after temporary network error."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
|
||||
# First call fails, second succeeds
|
||||
mock_client.get_series.side_effect = [
|
||||
Exception("Connection timeout"),
|
||||
sample_fred_series['FEDFUNDS']
|
||||
]
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 30
|
||||
|
||||
# Should have retried once
|
||||
assert mock_client.get_series.call_count == 2
|
||||
assert mock_sleep.call_count == 1
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_retry_exhaustion_returns_error(self, mock_sleep, mock_fred_api_key, integration_cache_dir):
|
||||
"""Test that exhausted retries return error string."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
mock_client.get_series.side_effect = Exception("Persistent error")
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
# Should retry max times
|
||||
assert mock_client.get_series.call_count >= 3
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_exponential_backoff_timing(self, mock_sleep, mock_fred_api_key, integration_cache_dir):
|
||||
"""Test that retry uses exponential backoff."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
mock_client.get_series.side_effect = Exception("Error")
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
# Check exponential backoff: 1s, 2s, 4s
|
||||
if mock_sleep.call_count >= 3:
|
||||
sleep_times = [call.args[0] for call in mock_sleep.call_args_list[:3]]
|
||||
assert sleep_times == [1, 2, 4]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Rate Limit Handling
|
||||
# ============================================================================
|
||||
|
||||
class TestRateLimitIntegration:
|
||||
"""Test rate limit error handling and recovery."""
|
||||
|
||||
def test_rate_limit_error_returns_error_string(self, mock_fred_api_key, integration_cache_dir):
|
||||
"""Test that rate limit error returns error string."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
mock_client.get_series.side_effect = FredRateLimitError("Rate limit exceeded", retry_after=60)
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "rate limit" in result.lower()
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_rate_limit_with_retry_after(self, mock_sleep, mock_fred_api_key, integration_cache_dir, sample_fred_series):
|
||||
"""Test rate limit with retry-after header."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
|
||||
# First call rate limited, second succeeds
|
||||
mock_client.get_series.side_effect = [
|
||||
FredRateLimitError("Rate limit", retry_after=5),
|
||||
sample_fred_series['FEDFUNDS']
|
||||
]
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
# Should respect retry-after (5 seconds)
|
||||
if mock_sleep.call_count > 0:
|
||||
assert 5 in [call.args[0] for call in mock_sleep.call_args_list]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Multi-Function Workflows
|
||||
# ============================================================================
|
||||
|
||||
class TestMultiFunctionWorkflows:
|
||||
"""Test realistic workflows using multiple functions."""
|
||||
|
||||
def test_retrieve_multiple_indicators(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test retrieving multiple economic indicators in sequence."""
|
||||
from tradingagents.dataflows.fred import (
|
||||
get_interest_rates,
|
||||
get_treasury_rates,
|
||||
get_money_supply,
|
||||
get_gdp,
|
||||
get_inflation,
|
||||
get_unemployment
|
||||
)
|
||||
|
||||
# Retrieve all indicators
|
||||
fed_funds = get_interest_rates()
|
||||
treasury_10y = get_treasury_rates(maturity='10Y')
|
||||
m2_supply = get_money_supply()
|
||||
gdp = get_gdp()
|
||||
cpi = get_inflation()
|
||||
unemployment = get_unemployment()
|
||||
|
||||
# All should succeed
|
||||
assert isinstance(fed_funds, pd.DataFrame)
|
||||
assert isinstance(treasury_10y, pd.DataFrame)
|
||||
assert isinstance(m2_supply, pd.DataFrame)
|
||||
assert isinstance(gdp, pd.DataFrame)
|
||||
assert isinstance(cpi, pd.DataFrame)
|
||||
assert isinstance(unemployment, pd.DataFrame)
|
||||
|
||||
# Verify data
|
||||
assert len(fed_funds) == 30
|
||||
assert len(treasury_10y) == 30
|
||||
assert len(m2_supply) == 12
|
||||
assert len(gdp) == 4
|
||||
assert len(cpi) == 12
|
||||
assert len(unemployment) == 12
|
||||
|
||||
def test_economic_dashboard_workflow(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test realistic economic dashboard data retrieval."""
|
||||
from tradingagents.dataflows.fred import (
|
||||
get_interest_rates,
|
||||
get_treasury_rates,
|
||||
get_inflation,
|
||||
get_unemployment
|
||||
)
|
||||
|
||||
# Dashboard data with date range
|
||||
start = '2024-01-01'
|
||||
end = '2024-12-31'
|
||||
|
||||
dashboard_data = {
|
||||
'fed_funds': get_interest_rates(start_date=start, end_date=end),
|
||||
'treasury_2y': get_treasury_rates(maturity='2Y', start_date=start, end_date=end),
|
||||
'treasury_10y': get_treasury_rates(maturity='10Y', start_date=start, end_date=end),
|
||||
'cpi': get_inflation(start_date=start, end_date=end),
|
||||
'unemployment': get_unemployment(start_date=start, end_date=end),
|
||||
}
|
||||
|
||||
# All should be DataFrames
|
||||
for key, value in dashboard_data.items():
|
||||
assert isinstance(value, pd.DataFrame), f"{key} should be DataFrame"
|
||||
assert len(value) > 0, f"{key} should have data"
|
||||
|
||||
def test_time_series_analysis_workflow(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test workflow for time series analysis with multiple series."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
# Retrieve multiple custom series
|
||||
series_ids = ['FEDFUNDS', 'DGS10', 'UNRATE']
|
||||
results = {}
|
||||
|
||||
for series_id in series_ids:
|
||||
results[series_id] = get_fred_series(series_id)
|
||||
|
||||
# Verify all retrieved successfully
|
||||
for series_id, df in results.items():
|
||||
assert isinstance(df, pd.DataFrame), f"{series_id} should be DataFrame"
|
||||
assert len(df) > 0, f"{series_id} should have data"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Error Recovery Integration
|
||||
# ============================================================================
|
||||
|
||||
class TestErrorRecoveryIntegration:
|
||||
"""Test error handling and recovery mechanisms."""
|
||||
|
||||
def test_invalid_series_recovers_gracefully(self, mock_fred_api_key, integration_cache_dir):
|
||||
"""Test that invalid series returns error string without crashing."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
mock_client.get_series.side_effect = Exception("Series not found")
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_fred_series('INVALID_SERIES')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
def test_missing_api_key_returns_error(self, integration_cache_dir):
|
||||
"""Test that missing API key returns error string."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
with patch.dict('os.environ', {}, clear=True):
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "api key" in result.lower()
|
||||
|
||||
def test_empty_data_returns_empty_dataframe(self, mock_fred_api_key, integration_cache_dir):
|
||||
"""Test that empty data is handled gracefully."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_client = MagicMock()
|
||||
mock_client.get_series.return_value = pd.DataFrame()
|
||||
mock_fred_class.return_value = mock_client
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 0
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Data Transformation Integration
|
||||
# ============================================================================
|
||||
|
||||
class TestDataTransformationIntegration:
|
||||
"""Test data formatting and transformation."""
|
||||
|
||||
def test_date_column_formatting(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test that date column is properly formatted."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert 'date' in result.columns
|
||||
assert pd.api.types.is_datetime64_any_dtype(result['date'])
|
||||
|
||||
def test_value_column_numeric(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test that value column is numeric."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert 'value' in result.columns
|
||||
assert pd.api.types.is_numeric_dtype(result['value'])
|
||||
|
||||
def test_no_null_values_in_valid_data(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test that valid data has no null values."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert result['date'].notna().all()
|
||||
assert result['value'].notna().all()
|
||||
|
||||
def test_data_sorted_by_date(self, mock_fred_api_key, mock_fred_client, integration_cache_dir):
|
||||
"""Test that data is sorted by date."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
# Check if dates are in ascending order
|
||||
assert result['date'].is_monotonic_increasing
|
||||
|
|
@ -0,0 +1,634 @@
|
|||
"""
|
||||
Test suite for FRED API Data Retrieval Functions (fred.py).
|
||||
|
||||
This module tests:
|
||||
1. get_interest_rates() - Federal funds rate retrieval
|
||||
2. get_treasury_rates() - Treasury yield retrieval
|
||||
3. get_money_supply() - M2 money supply retrieval
|
||||
4. get_gdp() - GDP data retrieval
|
||||
5. get_inflation() - CPI/inflation data retrieval
|
||||
6. get_unemployment() - Unemployment rate retrieval
|
||||
7. get_fred_series() - Generic FRED series retrieval
|
||||
|
||||
Test Coverage:
|
||||
- Unit tests for each data function
|
||||
- Default parameters and custom parameters
|
||||
- Date range filtering
|
||||
- Different series IDs and maturities
|
||||
- Error handling (returns error strings, not exceptions)
|
||||
- Cache integration
|
||||
- Empty data scenarios
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import pandas as pd
|
||||
from unittest.mock import Mock, patch, MagicMock
|
||||
from datetime import datetime, date
|
||||
|
||||
pytestmark = pytest.mark.unit
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Fixtures
|
||||
# ============================================================================
|
||||
|
||||
@pytest.fixture
|
||||
def mock_fred_request():
|
||||
"""Mock _make_fred_request function."""
|
||||
with patch('tradingagents.dataflows.fred._make_fred_request') as mock_request:
|
||||
yield mock_request
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_interest_rate_df():
|
||||
"""Create sample interest rate DataFrame."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='D'),
|
||||
'value': [5.33, 5.35, 5.37, 5.39, 5.40],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_treasury_rate_df():
|
||||
"""Create sample treasury rate DataFrame."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='D'),
|
||||
'value': [4.25, 4.27, 4.29, 4.31, 4.33],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_money_supply_df():
|
||||
"""Create sample M2 money supply DataFrame (billions)."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='ME'),
|
||||
'value': [21000.0, 21050.0, 21100.0, 21150.0, 21200.0],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_gdp_df():
|
||||
"""Create sample GDP DataFrame (billions)."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=4, freq='QE'),
|
||||
'value': [27000.0, 27200.0, 27400.0, 27600.0],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_cpi_df():
|
||||
"""Create sample CPI DataFrame."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='ME'),
|
||||
'value': [308.0, 309.0, 310.0, 311.0, 312.0],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_unemployment_df():
|
||||
"""Create sample unemployment rate DataFrame."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='ME'),
|
||||
'value': [3.7, 3.8, 3.9, 4.0, 4.1],
|
||||
})
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_interest_rates()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetInterestRates:
|
||||
"""Test federal funds rate retrieval."""
|
||||
|
||||
def test_get_interest_rates_success_default(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test successful retrieval with default parameters (FEDFUNDS)."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
assert 'date' in result.columns
|
||||
assert 'value' in result.columns
|
||||
mock_fred_request.assert_called_once_with('FEDFUNDS', start_date=None, end_date=None)
|
||||
|
||||
def test_get_interest_rates_with_date_range(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test retrieval with custom date range."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_interest_rates(start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_interest_rates_custom_series(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test retrieval with custom series ID."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_interest_rates(series_id='DFF')
|
||||
|
||||
mock_fred_request.assert_called_once_with('DFF', start_date=None, end_date=None)
|
||||
|
||||
def test_get_interest_rates_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string, not exception."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
mock_fred_request.side_effect = FredRateLimitError("Rate limit exceeded")
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "failed" in result.lower()
|
||||
assert "rate limit" in result.lower()
|
||||
|
||||
def test_get_interest_rates_empty_dataframe(self, mock_fred_request):
|
||||
"""Test handling of empty DataFrame response."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
mock_fred_request.return_value = pd.DataFrame()
|
||||
|
||||
result = get_interest_rates()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 0
|
||||
|
||||
def test_get_interest_rates_datetime_objects(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test retrieval with datetime objects instead of strings."""
|
||||
from tradingagents.dataflows.fred import get_interest_rates
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
start = datetime(2024, 1, 1)
|
||||
end = datetime(2024, 12, 31)
|
||||
|
||||
result = get_interest_rates(start_date=start, end_date=end)
|
||||
|
||||
# Should convert to string format
|
||||
assert mock_fred_request.called
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_treasury_rates()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetTreasuryRates:
|
||||
"""Test treasury yield retrieval."""
|
||||
|
||||
def test_get_treasury_rates_default_10y(self, mock_fred_request, sample_treasury_rate_df):
|
||||
"""Test successful retrieval of 10-year treasury (default)."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
mock_fred_request.return_value = sample_treasury_rate_df
|
||||
|
||||
result = get_treasury_rates()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fred_request.assert_called_once_with('DGS10', start_date=None, end_date=None)
|
||||
|
||||
def test_get_treasury_rates_2y(self, mock_fred_request, sample_treasury_rate_df):
|
||||
"""Test retrieval of 2-year treasury."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
mock_fred_request.return_value = sample_treasury_rate_df
|
||||
|
||||
result = get_treasury_rates(maturity='2Y')
|
||||
|
||||
mock_fred_request.assert_called_once_with('DGS2', start_date=None, end_date=None)
|
||||
|
||||
def test_get_treasury_rates_5y(self, mock_fred_request, sample_treasury_rate_df):
|
||||
"""Test retrieval of 5-year treasury."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
mock_fred_request.return_value = sample_treasury_rate_df
|
||||
|
||||
result = get_treasury_rates(maturity='5Y')
|
||||
|
||||
mock_fred_request.assert_called_once_with('DGS5', start_date=None, end_date=None)
|
||||
|
||||
def test_get_treasury_rates_30y(self, mock_fred_request, sample_treasury_rate_df):
|
||||
"""Test retrieval of 30-year treasury."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
mock_fred_request.return_value = sample_treasury_rate_df
|
||||
|
||||
result = get_treasury_rates(maturity='30Y')
|
||||
|
||||
mock_fred_request.assert_called_once_with('DGS30', start_date=None, end_date=None)
|
||||
|
||||
def test_get_treasury_rates_invalid_maturity(self, mock_fred_request):
|
||||
"""Test invalid maturity returns error string."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
result = get_treasury_rates(maturity='15Y')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "invalid" in result.lower()
|
||||
|
||||
def test_get_treasury_rates_with_date_range(self, mock_fred_request, sample_treasury_rate_df):
|
||||
"""Test retrieval with date range."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
|
||||
mock_fred_request.return_value = sample_treasury_rate_df
|
||||
|
||||
result = get_treasury_rates(maturity='10Y', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('DGS10', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_treasury_rates_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_treasury_rates
|
||||
from tradingagents.dataflows.fred_common import FredInvalidSeriesError
|
||||
|
||||
mock_fred_request.side_effect = FredInvalidSeriesError("Invalid series")
|
||||
|
||||
result = get_treasury_rates()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_money_supply()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetMoneySupply:
|
||||
"""Test money supply (M2) retrieval."""
|
||||
|
||||
def test_get_money_supply_default_m2(self, mock_fred_request, sample_money_supply_df):
|
||||
"""Test successful M2 money supply retrieval (default)."""
|
||||
from tradingagents.dataflows.fred import get_money_supply
|
||||
|
||||
mock_fred_request.return_value = sample_money_supply_df
|
||||
|
||||
result = get_money_supply()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fred_request.assert_called_once_with('M2SL', start_date=None, end_date=None)
|
||||
|
||||
def test_get_money_supply_m1(self, mock_fred_request, sample_money_supply_df):
|
||||
"""Test M1 money supply retrieval."""
|
||||
from tradingagents.dataflows.fred import get_money_supply
|
||||
|
||||
mock_fred_request.return_value = sample_money_supply_df
|
||||
|
||||
result = get_money_supply(measure='M1')
|
||||
|
||||
mock_fred_request.assert_called_once_with('M1SL', start_date=None, end_date=None)
|
||||
|
||||
def test_get_money_supply_with_date_range(self, mock_fred_request, sample_money_supply_df):
|
||||
"""Test money supply with date range."""
|
||||
from tradingagents.dataflows.fred import get_money_supply
|
||||
|
||||
mock_fred_request.return_value = sample_money_supply_df
|
||||
|
||||
result = get_money_supply(start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('M2SL', start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_money_supply_invalid_measure(self, mock_fred_request):
|
||||
"""Test invalid measure returns error string."""
|
||||
from tradingagents.dataflows.fred import get_money_supply
|
||||
|
||||
result = get_money_supply(measure='M5')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "invalid" in result.lower()
|
||||
|
||||
def test_get_money_supply_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_money_supply
|
||||
|
||||
mock_fred_request.side_effect = Exception("Network error")
|
||||
|
||||
result = get_money_supply()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_gdp()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetGDP:
|
||||
"""Test GDP data retrieval."""
|
||||
|
||||
def test_get_gdp_default_quarterly(self, mock_fred_request, sample_gdp_df):
|
||||
"""Test successful quarterly GDP retrieval (default)."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
mock_fred_request.return_value = sample_gdp_df
|
||||
|
||||
result = get_gdp()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 4
|
||||
mock_fred_request.assert_called_once_with('GDP', start_date=None, end_date=None)
|
||||
|
||||
def test_get_gdp_annual(self, mock_fred_request, sample_gdp_df):
|
||||
"""Test annual GDP retrieval."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
mock_fred_request.return_value = sample_gdp_df
|
||||
|
||||
result = get_gdp(frequency='annual')
|
||||
|
||||
mock_fred_request.assert_called_once_with('GDPA', start_date=None, end_date=None)
|
||||
|
||||
def test_get_gdp_real(self, mock_fred_request, sample_gdp_df):
|
||||
"""Test real GDP retrieval."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
mock_fred_request.return_value = sample_gdp_df
|
||||
|
||||
result = get_gdp(frequency='real')
|
||||
|
||||
mock_fred_request.assert_called_once_with('GDPC1', start_date=None, end_date=None)
|
||||
|
||||
def test_get_gdp_with_date_range(self, mock_fred_request, sample_gdp_df):
|
||||
"""Test GDP with date range."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
mock_fred_request.return_value = sample_gdp_df
|
||||
|
||||
result = get_gdp(start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('GDP', start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_gdp_invalid_frequency(self, mock_fred_request):
|
||||
"""Test invalid frequency returns error string."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
result = get_gdp(frequency='weekly')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "invalid" in result.lower()
|
||||
|
||||
def test_get_gdp_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_gdp
|
||||
|
||||
mock_fred_request.side_effect = Exception("API error")
|
||||
|
||||
result = get_gdp()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_inflation()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetInflation:
|
||||
"""Test inflation/CPI data retrieval."""
|
||||
|
||||
def test_get_inflation_default_cpi(self, mock_fred_request, sample_cpi_df):
|
||||
"""Test successful CPI retrieval (default)."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
mock_fred_request.return_value = sample_cpi_df
|
||||
|
||||
result = get_inflation()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fred_request.assert_called_once_with('CPIAUCSL', start_date=None, end_date=None)
|
||||
|
||||
def test_get_inflation_core_cpi(self, mock_fred_request, sample_cpi_df):
|
||||
"""Test core CPI retrieval (excluding food and energy)."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
mock_fred_request.return_value = sample_cpi_df
|
||||
|
||||
result = get_inflation(measure='CORE')
|
||||
|
||||
mock_fred_request.assert_called_once_with('CPILFESL', start_date=None, end_date=None)
|
||||
|
||||
def test_get_inflation_pce(self, mock_fred_request, sample_cpi_df):
|
||||
"""Test PCE price index retrieval."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
mock_fred_request.return_value = sample_cpi_df
|
||||
|
||||
result = get_inflation(measure='PCE')
|
||||
|
||||
mock_fred_request.assert_called_once_with('PCEPI', start_date=None, end_date=None)
|
||||
|
||||
def test_get_inflation_with_date_range(self, mock_fred_request, sample_cpi_df):
|
||||
"""Test inflation with date range."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
mock_fred_request.return_value = sample_cpi_df
|
||||
|
||||
result = get_inflation(start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('CPIAUCSL', start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_inflation_invalid_measure(self, mock_fred_request):
|
||||
"""Test invalid measure returns error string."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
result = get_inflation(measure='INVALID')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower() or "invalid" in result.lower()
|
||||
|
||||
def test_get_inflation_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_inflation
|
||||
|
||||
mock_fred_request.side_effect = Exception("API error")
|
||||
|
||||
result = get_inflation()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_unemployment()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetUnemployment:
|
||||
"""Test unemployment rate retrieval."""
|
||||
|
||||
def test_get_unemployment_default_unrate(self, mock_fred_request, sample_unemployment_df):
|
||||
"""Test successful unemployment rate retrieval (default)."""
|
||||
from tradingagents.dataflows.fred import get_unemployment
|
||||
|
||||
mock_fred_request.return_value = sample_unemployment_df
|
||||
|
||||
result = get_unemployment()
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fred_request.assert_called_once_with('UNRATE', start_date=None, end_date=None)
|
||||
|
||||
def test_get_unemployment_custom_series(self, mock_fred_request, sample_unemployment_df):
|
||||
"""Test unemployment with custom series ID."""
|
||||
from tradingagents.dataflows.fred import get_unemployment
|
||||
|
||||
mock_fred_request.return_value = sample_unemployment_df
|
||||
|
||||
result = get_unemployment(series_id='U6RATE')
|
||||
|
||||
mock_fred_request.assert_called_once_with('U6RATE', start_date=None, end_date=None)
|
||||
|
||||
def test_get_unemployment_with_date_range(self, mock_fred_request, sample_unemployment_df):
|
||||
"""Test unemployment with date range."""
|
||||
from tradingagents.dataflows.fred import get_unemployment
|
||||
|
||||
mock_fred_request.return_value = sample_unemployment_df
|
||||
|
||||
result = get_unemployment(start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('UNRATE', start_date='2020-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_unemployment_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_unemployment
|
||||
|
||||
mock_fred_request.side_effect = Exception("API error")
|
||||
|
||||
result = get_unemployment()
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_fred_series() - Generic Function
|
||||
# ============================================================================
|
||||
|
||||
class TestGetFredSeries:
|
||||
"""Test generic FRED series retrieval."""
|
||||
|
||||
def test_get_fred_series_success(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test successful generic series retrieval."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_fred_series('FEDFUNDS')
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fred_request.assert_called_once_with('FEDFUNDS', start_date=None, end_date=None)
|
||||
|
||||
def test_get_fred_series_with_date_range(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test generic series with date range."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_fred_series('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fred_request.assert_called_once_with('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
def test_get_fred_series_custom_series_id(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test generic series with any custom series ID."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
result = get_fred_series('SP500')
|
||||
|
||||
mock_fred_request.assert_called_once_with('SP500', start_date=None, end_date=None)
|
||||
|
||||
def test_get_fred_series_returns_error_string_on_failure(self, mock_fred_request):
|
||||
"""Test that errors return error string."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
mock_fred_request.side_effect = Exception("API error")
|
||||
|
||||
result = get_fred_series('INVALID')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
||||
def test_get_fred_series_invalid_series_id(self, mock_fred_request):
|
||||
"""Test generic series with invalid series ID."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
from tradingagents.dataflows.fred_common import FredInvalidSeriesError
|
||||
|
||||
mock_fred_request.side_effect = FredInvalidSeriesError("Series not found", series_id='INVALID')
|
||||
|
||||
result = get_fred_series('INVALID')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
assert "INVALID" in result or "series" in result.lower()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Edge Case Tests
|
||||
# ============================================================================
|
||||
|
||||
class TestEdgeCases:
|
||||
"""Test edge cases across all functions."""
|
||||
|
||||
def test_all_functions_handle_none_dates(self, mock_fred_request, sample_interest_rate_df):
|
||||
"""Test that all functions handle None dates properly."""
|
||||
from tradingagents.dataflows.fred import (
|
||||
get_interest_rates, get_treasury_rates, get_money_supply,
|
||||
get_gdp, get_inflation, get_unemployment, get_fred_series
|
||||
)
|
||||
|
||||
mock_fred_request.return_value = sample_interest_rate_df
|
||||
|
||||
# Should all succeed with None dates
|
||||
functions = [
|
||||
lambda: get_interest_rates(start_date=None, end_date=None),
|
||||
lambda: get_treasury_rates(start_date=None, end_date=None),
|
||||
lambda: get_money_supply(start_date=None, end_date=None),
|
||||
lambda: get_gdp(start_date=None, end_date=None),
|
||||
lambda: get_inflation(start_date=None, end_date=None),
|
||||
lambda: get_unemployment(start_date=None, end_date=None),
|
||||
lambda: get_fred_series('TEST', start_date=None, end_date=None),
|
||||
]
|
||||
|
||||
for func in functions:
|
||||
result = func()
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
|
||||
def test_all_functions_return_strings_on_error(self, mock_fred_request):
|
||||
"""Test that all functions return error strings, not exceptions."""
|
||||
from tradingagents.dataflows.fred import (
|
||||
get_interest_rates, get_treasury_rates, get_money_supply,
|
||||
get_gdp, get_inflation, get_unemployment, get_fred_series
|
||||
)
|
||||
|
||||
mock_fred_request.side_effect = Exception("Test error")
|
||||
|
||||
functions = [
|
||||
get_interest_rates,
|
||||
get_treasury_rates,
|
||||
get_money_supply,
|
||||
get_gdp,
|
||||
get_inflation,
|
||||
get_unemployment,
|
||||
lambda: get_fred_series('TEST'),
|
||||
]
|
||||
|
||||
for func in functions:
|
||||
result = func()
|
||||
assert isinstance(result, str), f"{func.__name__} should return string on error"
|
||||
assert "error" in result.lower() or "failed" in result.lower()
|
||||
|
||||
def test_empty_series_id_handled(self, mock_fred_request):
|
||||
"""Test handling of empty series ID."""
|
||||
from tradingagents.dataflows.fred import get_fred_series
|
||||
|
||||
result = get_fred_series('')
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert "error" in result.lower()
|
||||
|
|
@ -0,0 +1,594 @@
|
|||
"""
|
||||
Test suite for FRED API Core Utilities (fred_common.py).
|
||||
|
||||
This module tests:
|
||||
1. get_api_key() - API key retrieval from environment
|
||||
2. FredRateLimitError exception class - Rate limit handling
|
||||
3. FredInvalidSeriesError exception class - Invalid series handling
|
||||
4. format_date_for_fred() - Date format conversion
|
||||
5. _make_fred_request() - API request wrapper with retry logic
|
||||
6. _get_cache_path() - Cache file path generation
|
||||
7. _load_from_cache() - Cache data loading
|
||||
8. _save_to_cache() - Cache data saving
|
||||
|
||||
Test Coverage:
|
||||
- Unit tests for individual utility functions
|
||||
- Edge cases (missing API key, invalid dates, network errors)
|
||||
- Retry logic with exponential backoff
|
||||
- Cache hit/miss scenarios
|
||||
- Error handling and exception raising
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import pandas as pd
|
||||
import time
|
||||
import os
|
||||
from pathlib import Path
|
||||
from unittest.mock import Mock, patch, MagicMock, call
|
||||
from datetime import datetime, date, timedelta
|
||||
from typing import Optional
|
||||
|
||||
pytestmark = pytest.mark.unit
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Fixtures
|
||||
# ============================================================================
|
||||
|
||||
@pytest.fixture
|
||||
def mock_fred_api_key():
|
||||
"""Mock FRED_API_KEY environment variable."""
|
||||
with patch.dict('os.environ', {'FRED_API_KEY': 'test_api_key_12345'}):
|
||||
yield 'test_api_key_12345'
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_fred_api_key_missing():
|
||||
"""Mock environment without FRED_API_KEY."""
|
||||
with patch.dict('os.environ', {}, clear=True):
|
||||
yield
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_fred_dataframe():
|
||||
"""Create a sample FRED data DataFrame."""
|
||||
return pd.DataFrame({
|
||||
'date': pd.date_range('2024-01-01', periods=5, freq='D'),
|
||||
'value': [5.33, 5.35, 5.37, 5.39, 5.40],
|
||||
})
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_fredapi():
|
||||
"""Mock fredapi.Fred class for testing."""
|
||||
with patch('tradingagents.dataflows.fred_common.Fred') as mock_fred_class:
|
||||
mock_fred_instance = MagicMock()
|
||||
mock_fred_class.return_value = mock_fred_instance
|
||||
yield mock_fred_instance
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_cache_dir(tmp_path):
|
||||
"""Create a temporary cache directory."""
|
||||
cache_dir = tmp_path / ".cache" / "fred"
|
||||
cache_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.CACHE_DIR', cache_dir):
|
||||
yield cache_dir
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test get_api_key()
|
||||
# ============================================================================
|
||||
|
||||
class TestGetApiKey:
|
||||
"""Test FRED API key retrieval from environment."""
|
||||
|
||||
def test_get_api_key_success(self, mock_fred_api_key):
|
||||
"""Test successful API key retrieval from environment."""
|
||||
from tradingagents.dataflows.fred_common import get_api_key
|
||||
|
||||
api_key = get_api_key()
|
||||
|
||||
assert api_key == 'test_api_key_12345'
|
||||
assert isinstance(api_key, str)
|
||||
assert len(api_key) > 0
|
||||
|
||||
def test_get_api_key_missing_raises_value_error(self, mock_fred_api_key_missing):
|
||||
"""Test that missing API key raises ValueError."""
|
||||
from tradingagents.dataflows.fred_common import get_api_key
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
get_api_key()
|
||||
|
||||
assert "FRED_API_KEY" in str(exc_info.value)
|
||||
assert "environment variable" in str(exc_info.value).lower()
|
||||
|
||||
def test_get_api_key_empty_string_raises_value_error(self):
|
||||
"""Test that empty API key string raises ValueError."""
|
||||
with patch.dict('os.environ', {'FRED_API_KEY': ''}):
|
||||
from tradingagents.dataflows.fred_common import get_api_key
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
get_api_key()
|
||||
|
||||
assert "FRED_API_KEY" in str(exc_info.value)
|
||||
|
||||
def test_get_api_key_whitespace_only_raises_value_error(self):
|
||||
"""Test that whitespace-only API key raises ValueError."""
|
||||
with patch.dict('os.environ', {'FRED_API_KEY': ' '}):
|
||||
from tradingagents.dataflows.fred_common import get_api_key
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
get_api_key()
|
||||
|
||||
assert "FRED_API_KEY" in str(exc_info.value)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Exception Classes
|
||||
# ============================================================================
|
||||
|
||||
class TestFredRateLimitError:
|
||||
"""Test FredRateLimitError exception class."""
|
||||
|
||||
def test_exception_creation_with_message(self):
|
||||
"""Test creating FredRateLimitError with just a message."""
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
error = FredRateLimitError("Rate limit exceeded")
|
||||
|
||||
assert str(error) == "Rate limit exceeded"
|
||||
assert isinstance(error, Exception)
|
||||
|
||||
def test_exception_creation_with_retry_after(self):
|
||||
"""Test FredRateLimitError with retry_after parameter."""
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
error = FredRateLimitError("Rate limit exceeded", retry_after=60)
|
||||
|
||||
assert str(error) == "Rate limit exceeded"
|
||||
assert error.retry_after == 60
|
||||
assert isinstance(error.retry_after, int)
|
||||
|
||||
def test_exception_inheritance(self):
|
||||
"""Test that FredRateLimitError inherits from Exception."""
|
||||
from tradingagents.dataflows.fred_common import FredRateLimitError
|
||||
|
||||
error = FredRateLimitError("Test")
|
||||
assert isinstance(error, Exception)
|
||||
|
||||
|
||||
class TestFredInvalidSeriesError:
|
||||
"""Test FredInvalidSeriesError exception class."""
|
||||
|
||||
def test_exception_creation_with_message(self):
|
||||
"""Test creating FredInvalidSeriesError with message."""
|
||||
from tradingagents.dataflows.fred_common import FredInvalidSeriesError
|
||||
|
||||
error = FredInvalidSeriesError("Invalid series: INVALID_ID")
|
||||
|
||||
assert str(error) == "Invalid series: INVALID_ID"
|
||||
assert isinstance(error, Exception)
|
||||
|
||||
def test_exception_creation_with_series_id(self):
|
||||
"""Test FredInvalidSeriesError with series_id parameter."""
|
||||
from tradingagents.dataflows.fred_common import FredInvalidSeriesError
|
||||
|
||||
error = FredInvalidSeriesError("Invalid series", series_id="INVALID_ID")
|
||||
|
||||
assert error.series_id == "INVALID_ID"
|
||||
|
||||
def test_exception_inheritance(self):
|
||||
"""Test that FredInvalidSeriesError inherits from Exception."""
|
||||
from tradingagents.dataflows.fred_common import FredInvalidSeriesError
|
||||
|
||||
error = FredInvalidSeriesError("Test")
|
||||
assert isinstance(error, Exception)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test format_date_for_fred()
|
||||
# ============================================================================
|
||||
|
||||
class TestFormatDateForFred:
|
||||
"""Test date format conversion for FRED API."""
|
||||
|
||||
def test_format_datetime_object(self):
|
||||
"""Test formatting datetime.datetime object."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
dt = datetime(2024, 1, 15, 10, 30, 45)
|
||||
result = format_date_for_fred(dt)
|
||||
|
||||
assert result == "2024-01-15"
|
||||
assert isinstance(result, str)
|
||||
|
||||
def test_format_date_object(self):
|
||||
"""Test formatting datetime.date object."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
d = date(2024, 1, 15)
|
||||
result = format_date_for_fred(d)
|
||||
|
||||
assert result == "2024-01-15"
|
||||
assert isinstance(result, str)
|
||||
|
||||
def test_format_string_yyyy_mm_dd(self):
|
||||
"""Test formatting string already in YYYY-MM-DD format."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
result = format_date_for_fred("2024-01-15")
|
||||
|
||||
assert result == "2024-01-15"
|
||||
|
||||
def test_format_string_mm_dd_yyyy(self):
|
||||
"""Test formatting string in MM/DD/YYYY format."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
result = format_date_for_fred("01/15/2024")
|
||||
|
||||
assert result == "2024-01-15"
|
||||
|
||||
def test_format_string_dd_mm_yyyy(self):
|
||||
"""Test formatting string in DD-MM-YYYY format."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
result = format_date_for_fred("15-01-2024")
|
||||
|
||||
assert result == "2024-01-15"
|
||||
|
||||
def test_format_timestamp(self):
|
||||
"""Test formatting Unix timestamp."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
# Unix timestamp for 2024-01-15 00:00:00 UTC
|
||||
timestamp = 1705276800
|
||||
result = format_date_for_fred(timestamp)
|
||||
|
||||
assert result == "2024-01-15"
|
||||
|
||||
def test_format_none_returns_none(self):
|
||||
"""Test that None input returns None."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
result = format_date_for_fred(None)
|
||||
|
||||
assert result is None
|
||||
|
||||
def test_format_invalid_string_raises_value_error(self):
|
||||
"""Test that invalid date string raises ValueError."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
format_date_for_fred("invalid-date")
|
||||
|
||||
assert "date" in str(exc_info.value).lower()
|
||||
|
||||
def test_format_future_date(self):
|
||||
"""Test formatting future date."""
|
||||
from tradingagents.dataflows.fred_common import format_date_for_fred
|
||||
|
||||
future = datetime.now() + timedelta(days=365)
|
||||
result = format_date_for_fred(future)
|
||||
|
||||
assert isinstance(result, str)
|
||||
assert len(result) == 10 # YYYY-MM-DD format
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test _make_fred_request()
|
||||
# ============================================================================
|
||||
|
||||
class TestMakeFredRequest:
|
||||
"""Test FRED API request wrapper with retry logic."""
|
||||
|
||||
def test_successful_request_returns_dataframe(self, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test successful API request returns DataFrame."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
mock_fredapi.get_series.return_value = sample_fred_dataframe
|
||||
|
||||
result = _make_fred_request('FEDFUNDS')
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fredapi.get_series.assert_called_once_with('FEDFUNDS', observation_start=None, observation_end=None)
|
||||
|
||||
def test_request_with_date_range(self, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test API request with start and end dates."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
mock_fredapi.get_series.return_value = sample_fred_dataframe
|
||||
|
||||
result = _make_fred_request('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
mock_fredapi.get_series.assert_called_once_with(
|
||||
'FEDFUNDS',
|
||||
observation_start='2024-01-01',
|
||||
observation_end='2024-12-31'
|
||||
)
|
||||
|
||||
def test_rate_limit_429_raises_rate_limit_error(self, mock_fred_api_key, mock_fredapi):
|
||||
"""Test that 429 response raises FredRateLimitError."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request, FredRateLimitError
|
||||
|
||||
# Mock HTTP 429 error
|
||||
error = Exception("429 Client Error: Too Many Requests")
|
||||
mock_fredapi.get_series.side_effect = error
|
||||
|
||||
with pytest.raises(FredRateLimitError) as exc_info:
|
||||
_make_fred_request('FEDFUNDS')
|
||||
|
||||
assert "rate limit" in str(exc_info.value).lower()
|
||||
|
||||
def test_invalid_series_raises_invalid_series_error(self, mock_fred_api_key, mock_fredapi):
|
||||
"""Test that invalid series ID raises FredInvalidSeriesError."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request, FredInvalidSeriesError
|
||||
|
||||
# Mock series not found error
|
||||
error = Exception("Series not found")
|
||||
mock_fredapi.get_series.side_effect = error
|
||||
|
||||
with pytest.raises(FredInvalidSeriesError) as exc_info:
|
||||
_make_fred_request('INVALID_SERIES_ID')
|
||||
|
||||
assert "INVALID_SERIES_ID" in str(exc_info.value)
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_network_timeout_retries_three_times(self, mock_sleep, mock_fred_api_key, mock_fredapi):
|
||||
"""Test that network timeout triggers retry with exponential backoff."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
# Mock timeout error
|
||||
timeout_error = Exception("Connection timeout")
|
||||
mock_fredapi.get_series.side_effect = timeout_error
|
||||
|
||||
with pytest.raises(Exception) as exc_info:
|
||||
_make_fred_request('FEDFUNDS', max_retries=3)
|
||||
|
||||
# Should retry 3 times (total 4 attempts including initial)
|
||||
assert mock_fredapi.get_series.call_count == 4
|
||||
|
||||
# Should sleep with exponential backoff: 1s, 2s, 4s
|
||||
assert mock_sleep.call_count == 3
|
||||
sleep_calls = [call.args[0] for call in mock_sleep.call_args_list]
|
||||
assert sleep_calls == [1, 2, 4]
|
||||
|
||||
@patch('tradingagents.dataflows.fred_common.time.sleep')
|
||||
def test_retry_succeeds_on_second_attempt(self, mock_sleep, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test successful retry after initial failure."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
# First call fails, second succeeds
|
||||
mock_fredapi.get_series.side_effect = [
|
||||
Exception("Temporary error"),
|
||||
sample_fred_dataframe
|
||||
]
|
||||
|
||||
result = _make_fred_request('FEDFUNDS', max_retries=3)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert mock_fredapi.get_series.call_count == 2
|
||||
assert mock_sleep.call_count == 1
|
||||
|
||||
def test_empty_dataframe_returns_empty(self, mock_fred_api_key, mock_fredapi):
|
||||
"""Test that empty DataFrame is returned when no data available."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
empty_df = pd.DataFrame()
|
||||
mock_fredapi.get_series.return_value = empty_df
|
||||
|
||||
result = _make_fred_request('FEDFUNDS')
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 0
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Test Cache Functions
|
||||
# ============================================================================
|
||||
|
||||
class TestGetCachePath:
|
||||
"""Test cache file path generation."""
|
||||
|
||||
def test_get_cache_path_basic(self, mock_cache_dir):
|
||||
"""Test basic cache path generation."""
|
||||
from tradingagents.dataflows.fred_common import _get_cache_path
|
||||
|
||||
cache_path = _get_cache_path('FEDFUNDS')
|
||||
|
||||
assert isinstance(cache_path, Path)
|
||||
assert cache_path.name == 'FEDFUNDS.parquet'
|
||||
assert cache_path.parent == mock_cache_dir
|
||||
|
||||
def test_get_cache_path_with_dates(self, mock_cache_dir):
|
||||
"""Test cache path includes date range in filename."""
|
||||
from tradingagents.dataflows.fred_common import _get_cache_path
|
||||
|
||||
cache_path = _get_cache_path('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
assert isinstance(cache_path, Path)
|
||||
assert 'FEDFUNDS' in cache_path.name
|
||||
assert '2024-01-01' in cache_path.name
|
||||
assert '2024-12-31' in cache_path.name
|
||||
assert cache_path.suffix == '.parquet'
|
||||
|
||||
def test_get_cache_path_special_characters(self, mock_cache_dir):
|
||||
"""Test cache path with series ID containing special characters."""
|
||||
from tradingagents.dataflows.fred_common import _get_cache_path
|
||||
|
||||
cache_path = _get_cache_path('DGS10')
|
||||
|
||||
assert isinstance(cache_path, Path)
|
||||
assert cache_path.name == 'DGS10.parquet'
|
||||
|
||||
|
||||
class TestLoadFromCache:
|
||||
"""Test loading data from cache."""
|
||||
|
||||
def test_load_from_cache_hit(self, mock_cache_dir, sample_fred_dataframe):
|
||||
"""Test successful cache load when file exists."""
|
||||
from tradingagents.dataflows.fred_common import _load_from_cache, _save_to_cache
|
||||
|
||||
# Save to cache first
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
sample_fred_dataframe.to_parquet(cache_path)
|
||||
|
||||
# Load from cache
|
||||
result = _load_from_cache('FEDFUNDS')
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
assert list(result.columns) == list(sample_fred_dataframe.columns)
|
||||
|
||||
def test_load_from_cache_miss_returns_none(self, mock_cache_dir):
|
||||
"""Test cache miss returns None when file doesn't exist."""
|
||||
from tradingagents.dataflows.fred_common import _load_from_cache
|
||||
|
||||
result = _load_from_cache('NONEXISTENT_SERIES')
|
||||
|
||||
assert result is None
|
||||
|
||||
def test_load_from_cache_expired_returns_none(self, mock_cache_dir, sample_fred_dataframe):
|
||||
"""Test expired cache returns None."""
|
||||
from tradingagents.dataflows.fred_common import _load_from_cache
|
||||
|
||||
# Save to cache
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
sample_fred_dataframe.to_parquet(cache_path)
|
||||
|
||||
# Mock old modification time (25 hours ago)
|
||||
old_time = time.time() - (25 * 3600)
|
||||
os.utime(cache_path, (old_time, old_time))
|
||||
|
||||
# Load from cache with 24hr TTL
|
||||
result = _load_from_cache('FEDFUNDS', cache_ttl_hours=24)
|
||||
|
||||
assert result is None
|
||||
|
||||
def test_load_from_cache_corrupted_returns_none(self, mock_cache_dir):
|
||||
"""Test corrupted cache file returns None."""
|
||||
from tradingagents.dataflows.fred_common import _load_from_cache
|
||||
|
||||
# Create corrupted cache file
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
cache_path.write_text("corrupted data")
|
||||
|
||||
result = _load_from_cache('FEDFUNDS')
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestSaveToCache:
|
||||
"""Test saving data to cache."""
|
||||
|
||||
def test_save_to_cache_success(self, mock_cache_dir, sample_fred_dataframe):
|
||||
"""Test successful cache save."""
|
||||
from tradingagents.dataflows.fred_common import _save_to_cache
|
||||
|
||||
_save_to_cache('FEDFUNDS', sample_fred_dataframe)
|
||||
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
assert cache_path.exists()
|
||||
|
||||
# Verify data can be loaded
|
||||
loaded_df = pd.read_parquet(cache_path)
|
||||
assert len(loaded_df) == 5
|
||||
|
||||
def test_save_to_cache_creates_directory(self, tmp_path, sample_fred_dataframe):
|
||||
"""Test that cache directory is created if it doesn't exist."""
|
||||
from tradingagents.dataflows.fred_common import _save_to_cache
|
||||
|
||||
new_cache_dir = tmp_path / "new_cache" / "fred"
|
||||
|
||||
with patch('tradingagents.dataflows.fred_common.CACHE_DIR', new_cache_dir):
|
||||
_save_to_cache('FEDFUNDS', sample_fred_dataframe)
|
||||
|
||||
assert new_cache_dir.exists()
|
||||
cache_path = new_cache_dir / 'FEDFUNDS.parquet'
|
||||
assert cache_path.exists()
|
||||
|
||||
def test_save_to_cache_overwrites_existing(self, mock_cache_dir, sample_fred_dataframe):
|
||||
"""Test that existing cache file is overwritten."""
|
||||
from tradingagents.dataflows.fred_common import _save_to_cache
|
||||
|
||||
# Save initial data
|
||||
_save_to_cache('FEDFUNDS', sample_fred_dataframe)
|
||||
|
||||
# Save new data
|
||||
new_df = pd.DataFrame({
|
||||
'date': pd.date_range('2024-06-01', periods=3, freq='D'),
|
||||
'value': [6.0, 6.1, 6.2],
|
||||
})
|
||||
_save_to_cache('FEDFUNDS', new_df)
|
||||
|
||||
# Verify new data
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
loaded_df = pd.read_parquet(cache_path)
|
||||
assert len(loaded_df) == 3
|
||||
assert loaded_df['value'].iloc[0] == 6.0
|
||||
|
||||
def test_save_empty_dataframe(self, mock_cache_dir):
|
||||
"""Test saving empty DataFrame to cache."""
|
||||
from tradingagents.dataflows.fred_common import _save_to_cache
|
||||
|
||||
empty_df = pd.DataFrame()
|
||||
_save_to_cache('FEDFUNDS', empty_df)
|
||||
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
assert cache_path.exists()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Integration Tests for Cache + Request
|
||||
# ============================================================================
|
||||
|
||||
class TestCacheIntegration:
|
||||
"""Test integration between cache and request functions."""
|
||||
|
||||
def test_request_uses_cache_when_available(self, mock_cache_dir, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test that cached data is used instead of API call."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request, _save_to_cache
|
||||
|
||||
# Save to cache
|
||||
_save_to_cache('FEDFUNDS', sample_fred_dataframe)
|
||||
|
||||
# Request should use cache (mock API should not be called)
|
||||
result = _make_fred_request('FEDFUNDS', use_cache=True)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 5
|
||||
mock_fredapi.get_series.assert_not_called()
|
||||
|
||||
def test_request_bypasses_cache_when_disabled(self, mock_cache_dir, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test that cache is bypassed when use_cache=False."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request, _save_to_cache
|
||||
|
||||
# Save to cache
|
||||
_save_to_cache('FEDFUNDS', sample_fred_dataframe)
|
||||
|
||||
# Configure mock
|
||||
mock_fredapi.get_series.return_value = sample_fred_dataframe
|
||||
|
||||
# Request should bypass cache
|
||||
result = _make_fred_request('FEDFUNDS', use_cache=False)
|
||||
|
||||
mock_fredapi.get_series.assert_called_once()
|
||||
|
||||
def test_request_saves_to_cache_after_api_call(self, mock_cache_dir, mock_fred_api_key, mock_fredapi, sample_fred_dataframe):
|
||||
"""Test that API response is saved to cache."""
|
||||
from tradingagents.dataflows.fred_common import _make_fred_request
|
||||
|
||||
mock_fredapi.get_series.return_value = sample_fred_dataframe
|
||||
|
||||
# Make request
|
||||
result = _make_fred_request('FEDFUNDS', use_cache=True)
|
||||
|
||||
# Verify cache file was created
|
||||
cache_path = mock_cache_dir / 'FEDFUNDS.parquet'
|
||||
assert cache_path.exists()
|
||||
|
||||
# Verify cached data
|
||||
cached_df = pd.read_parquet(cache_path)
|
||||
assert len(cached_df) == 5
|
||||
|
|
@ -0,0 +1,396 @@
|
|||
"""
|
||||
FRED API Data Retrieval Functions.
|
||||
|
||||
This module provides high-level functions for retrieving economic data from FRED:
|
||||
- Interest rates (Federal Funds Rate)
|
||||
- Treasury rates (2Y, 5Y, 10Y, 30Y yields)
|
||||
- Money supply (M1, M2)
|
||||
- GDP (nominal and real)
|
||||
- Inflation (CPI, PCE)
|
||||
- Unemployment rate
|
||||
- Generic series retrieval
|
||||
|
||||
All functions return pandas DataFrames on success or error strings on failure.
|
||||
Functions automatically handle caching, retry logic, and error recovery.
|
||||
|
||||
Usage:
|
||||
from tradingagents.dataflows.fred import get_interest_rates, get_treasury_rates
|
||||
|
||||
# Get federal funds rate
|
||||
data = get_interest_rates()
|
||||
|
||||
# Get 10-year treasury yield with date range
|
||||
data = get_treasury_rates(maturity='10Y', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
Requirements:
|
||||
- fredapi package: pip install fredapi
|
||||
- FRED_API_KEY environment variable must be set
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
from typing import Union, Optional
|
||||
from .fred_common import (
|
||||
_make_fred_request,
|
||||
FredRateLimitError,
|
||||
FredInvalidSeriesError,
|
||||
)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# FRED Series ID Mappings
|
||||
# ============================================================================
|
||||
|
||||
FRED_SERIES = {
|
||||
# Interest Rates
|
||||
'FEDFUNDS': 'FEDFUNDS', # Federal Funds Effective Rate
|
||||
'EFFR': 'FEDFUNDS', # Alias for Federal Funds Rate
|
||||
|
||||
# Treasury Rates
|
||||
'DGS2': 'DGS2', # 2-Year Treasury Constant Maturity Rate
|
||||
'DGS5': 'DGS5', # 5-Year Treasury Constant Maturity Rate
|
||||
'DGS10': 'DGS10', # 10-Year Treasury Constant Maturity Rate
|
||||
'DGS30': 'DGS30', # 30-Year Treasury Constant Maturity Rate
|
||||
|
||||
# Money Supply
|
||||
'M1SL': 'M1SL', # M1 Money Stock
|
||||
'M2SL': 'M2SL', # M2 Money Stock
|
||||
|
||||
# GDP
|
||||
'GDP': 'GDP', # Gross Domestic Product (nominal)
|
||||
'GDPC1': 'GDPC1', # Real Gross Domestic Product
|
||||
|
||||
# Inflation
|
||||
'CPIAUCSL': 'CPIAUCSL', # Consumer Price Index for All Urban Consumers
|
||||
'PCEPI': 'PCEPI', # Personal Consumption Expenditures Price Index
|
||||
|
||||
# Unemployment
|
||||
'UNRATE': 'UNRATE', # Unemployment Rate
|
||||
}
|
||||
|
||||
# Treasury maturity mappings
|
||||
TREASURY_MATURITIES = {
|
||||
'2Y': 'DGS2',
|
||||
'5Y': 'DGS5',
|
||||
'10Y': 'DGS10',
|
||||
'30Y': 'DGS30',
|
||||
}
|
||||
|
||||
# Money supply measure mappings
|
||||
MONEY_SUPPLY_MEASURES = {
|
||||
'M1': 'M1SL',
|
||||
'M2': 'M2SL',
|
||||
}
|
||||
|
||||
# GDP frequency mappings
|
||||
GDP_FREQUENCIES = {
|
||||
'quarterly': 'GDP',
|
||||
'real': 'GDPC1',
|
||||
'nominal': 'GDP',
|
||||
'annual': 'GDPA',
|
||||
}
|
||||
|
||||
# Inflation measure mappings
|
||||
INFLATION_MEASURES = {
|
||||
'CPI': 'CPIAUCSL',
|
||||
'CORE': 'CPILFESL',
|
||||
'PCE': 'PCEPI',
|
||||
}
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Data Retrieval Functions
|
||||
# ============================================================================
|
||||
|
||||
def get_interest_rates(
|
||||
series_id: str = 'FEDFUNDS',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve interest rate data from FRED.
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID (default: 'FEDFUNDS' for Federal Funds Rate)
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
use_cache: Whether to use caching (default: True)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_interest_rates() # Get federal funds rate
|
||||
>>> data = get_interest_rates(start_date='2024-01-01', end_date='2024-12-31')
|
||||
"""
|
||||
try:
|
||||
# Make API request
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series ID '{series_id}'. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving interest rate data: {e}"
|
||||
|
||||
|
||||
def get_treasury_rates(
|
||||
maturity: str = '10Y',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve Treasury yield data from FRED.
|
||||
|
||||
Args:
|
||||
maturity: Treasury maturity ('2Y', '5Y', '10Y', or '30Y', default: '10Y')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_treasury_rates() # Get 10-year yield
|
||||
>>> data = get_treasury_rates(maturity='2Y', start_date='2024-01-01')
|
||||
"""
|
||||
try:
|
||||
# Map maturity to series ID
|
||||
series_id = TREASURY_MATURITIES.get(maturity)
|
||||
if not series_id:
|
||||
return f"Error: Invalid maturity '{maturity}'. Valid options: {list(TREASURY_MATURITIES.keys())}"
|
||||
|
||||
# Make API request (caching handled internally)
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving treasury rate data: {e}"
|
||||
|
||||
|
||||
def get_money_supply(
|
||||
measure: str = 'M2',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve money supply data from FRED.
|
||||
|
||||
Args:
|
||||
measure: Money supply measure ('M1' or 'M2', default: 'M2')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns (values in billions) on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_money_supply() # Get M2 money supply
|
||||
>>> data = get_money_supply(measure='M1', start_date='2024-01-01')
|
||||
"""
|
||||
try:
|
||||
# Map measure to series ID
|
||||
series_id = MONEY_SUPPLY_MEASURES.get(measure)
|
||||
if not series_id:
|
||||
return f"Error: Invalid measure '{measure}'. Valid options: {list(MONEY_SUPPLY_MEASURES.keys())}"
|
||||
|
||||
# Make API request (caching handled internally)
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving money supply data: {e}"
|
||||
|
||||
|
||||
def get_gdp(
|
||||
frequency: str = 'quarterly',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve GDP data from FRED.
|
||||
|
||||
Args:
|
||||
frequency: GDP type ('quarterly', 'nominal', 'real', or 'annual', default: 'quarterly')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns (values in billions) on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_gdp() # Get quarterly nominal GDP
|
||||
>>> data = get_gdp(frequency='real', start_date='2024-01-01')
|
||||
"""
|
||||
try:
|
||||
# Map frequency to series ID
|
||||
series_id = GDP_FREQUENCIES.get(frequency)
|
||||
if not series_id:
|
||||
return f"Error: Invalid frequency '{frequency}'. Valid options: {list(GDP_FREQUENCIES.keys())}"
|
||||
|
||||
# Make API request (caching handled internally)
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving GDP data: {e}"
|
||||
|
||||
|
||||
def get_inflation(
|
||||
measure: str = 'CPI',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve inflation data from FRED.
|
||||
|
||||
Args:
|
||||
measure: Inflation measure ('CPI', 'CORE', or 'PCE', default: 'CPI')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns (index values) on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_inflation() # Get CPI data
|
||||
>>> data = get_inflation(measure='PCE', start_date='2024-01-01')
|
||||
"""
|
||||
try:
|
||||
# Map measure to series ID
|
||||
series_id = INFLATION_MEASURES.get(measure)
|
||||
if not series_id:
|
||||
return f"Error: Invalid measure '{measure}'. Valid options: {list(INFLATION_MEASURES.keys())}"
|
||||
|
||||
# Make API request (caching handled internally)
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving inflation data: {e}"
|
||||
|
||||
|
||||
def get_unemployment(
|
||||
series_id: str = 'UNRATE',
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve unemployment rate data from FRED.
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID (default: 'UNRATE' for U.S. unemployment rate)
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns (percentage) on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_unemployment() # Get U.S. unemployment rate
|
||||
>>> data = get_unemployment(start_date='2024-01-01', end_date='2024-12-31')
|
||||
"""
|
||||
try:
|
||||
# Make API request
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series ID '{series_id}'. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving unemployment data: {e}"
|
||||
|
||||
|
||||
def get_fred_series(
|
||||
series_id: str,
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
use_cache: bool = True
|
||||
) -> Union[pd.DataFrame, str]:
|
||||
"""
|
||||
Retrieve any FRED series data by series ID.
|
||||
|
||||
This is a generic function that can retrieve any FRED series.
|
||||
Use specific functions (get_interest_rates, get_treasury_rates, etc.)
|
||||
for better validation and error messages.
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID (e.g., 'FEDFUNDS', 'DGS10', 'UNRATE')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame with 'date' and 'value' columns on success
|
||||
str with error message on failure
|
||||
|
||||
Examples:
|
||||
>>> data = get_fred_series('FEDFUNDS') # Get federal funds rate
|
||||
>>> data = get_fred_series('DGS10', start_date='2024-01-01')
|
||||
"""
|
||||
try:
|
||||
# Validate series_id
|
||||
if not series_id or not isinstance(series_id, str):
|
||||
return "Error: series_id must be a non-empty string"
|
||||
|
||||
# Make API request (caching handled internally)
|
||||
data = _make_fred_request(series_id, start_date=start_date, end_date=end_date)
|
||||
|
||||
return data
|
||||
|
||||
except FredRateLimitError as e:
|
||||
return f"Error: FRED API rate limit exceeded. Please try again later. Details: {e}"
|
||||
except FredInvalidSeriesError as e:
|
||||
return f"Error: Invalid FRED series ID '{series_id}'. Details: {e}"
|
||||
except ValueError as e:
|
||||
return f"Error: Invalid input parameters. Details: {e}"
|
||||
except Exception as e:
|
||||
return f"Error retrieving FRED series data: {e}"
|
||||
|
|
@ -0,0 +1,346 @@
|
|||
"""
|
||||
FRED API Core Utilities.
|
||||
|
||||
This module provides core utilities for accessing the Federal Reserve Economic Data (FRED) API:
|
||||
- API key management
|
||||
- Custom exceptions for rate limiting and invalid series
|
||||
- Date formatting for FRED API
|
||||
- Request wrapper with retry logic and exponential backoff
|
||||
- Cache management for reducing API calls
|
||||
|
||||
Usage:
|
||||
from tradingagents.dataflows.fred_common import get_api_key, _make_fred_request
|
||||
|
||||
api_key = get_api_key()
|
||||
data = _make_fred_request('FEDFUNDS', start_date='2024-01-01', end_date='2024-12-31')
|
||||
|
||||
Requirements:
|
||||
- fredapi package: pip install fredapi
|
||||
- FRED_API_KEY environment variable must be set
|
||||
"""
|
||||
|
||||
import os
|
||||
import time
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Optional, Union
|
||||
|
||||
# Try to import fredapi, but allow it to be mocked in tests
|
||||
try:
|
||||
from fredapi import Fred
|
||||
except ImportError:
|
||||
Fred = None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Configuration
|
||||
# ============================================================================
|
||||
|
||||
# Cache directory for FRED data
|
||||
CACHE_DIR = Path.home() / ".cache" / "fred"
|
||||
CACHE_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Cache TTL in hours
|
||||
CACHE_TTL_HOURS = 24
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Custom Exceptions
|
||||
# ============================================================================
|
||||
|
||||
class FredRateLimitError(Exception):
|
||||
"""Exception raised when FRED API rate limit is exceeded."""
|
||||
def __init__(self, message: str, retry_after: Optional[int] = None):
|
||||
super().__init__(message)
|
||||
self.retry_after = retry_after
|
||||
|
||||
|
||||
class FredInvalidSeriesError(Exception):
|
||||
"""Exception raised when FRED series ID is invalid or not found."""
|
||||
def __init__(self, message: str, series_id: Optional[str] = None):
|
||||
super().__init__(message)
|
||||
self.series_id = series_id
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# API Key Management
|
||||
# ============================================================================
|
||||
|
||||
def get_api_key() -> str:
|
||||
"""
|
||||
Retrieve the FRED API key from environment variables.
|
||||
|
||||
Returns:
|
||||
str: The FRED API key
|
||||
|
||||
Raises:
|
||||
ValueError: If FRED_API_KEY environment variable is not set or empty
|
||||
"""
|
||||
api_key = os.getenv("FRED_API_KEY")
|
||||
if not api_key or not api_key.strip():
|
||||
raise ValueError("FRED_API_KEY environment variable is not set")
|
||||
return api_key
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Date Formatting
|
||||
# ============================================================================
|
||||
|
||||
def format_date_for_fred(date_input: Union[str, datetime, 'date', int, None]) -> Optional[str]:
|
||||
"""
|
||||
Convert various date formats to YYYY-MM-DD format required by FRED API.
|
||||
|
||||
Args:
|
||||
date_input: Date as string, datetime/date object, timestamp (int), or None
|
||||
|
||||
Returns:
|
||||
Date string in YYYY-MM-DD format, or None if input is None
|
||||
|
||||
Raises:
|
||||
ValueError: If date format is invalid or unsupported
|
||||
"""
|
||||
if date_input is None:
|
||||
return None
|
||||
|
||||
# Handle datetime.date objects (not datetime)
|
||||
if hasattr(date_input, 'year') and hasattr(date_input, 'month') and hasattr(date_input, 'day'):
|
||||
if not isinstance(date_input, datetime):
|
||||
# It's a date object
|
||||
return f"{date_input.year:04d}-{date_input.month:02d}-{date_input.day:02d}"
|
||||
|
||||
if isinstance(date_input, str):
|
||||
# Try multiple date formats
|
||||
date_formats = [
|
||||
"%Y-%m-%d", # 2024-01-15
|
||||
"%m/%d/%Y", # 01/15/2024
|
||||
"%d-%m-%Y", # 15-01-2024
|
||||
]
|
||||
|
||||
for fmt in date_formats:
|
||||
try:
|
||||
dt = datetime.strptime(date_input, fmt)
|
||||
return dt.strftime("%Y-%m-%d")
|
||||
except ValueError:
|
||||
continue
|
||||
|
||||
# If no format matched, raise error
|
||||
raise ValueError(f"Invalid date format: {date_input}. Expected YYYY-MM-DD, MM/DD/YYYY, or DD-MM-YYYY")
|
||||
|
||||
elif isinstance(date_input, datetime):
|
||||
return date_input.strftime("%Y-%m-%d")
|
||||
|
||||
elif isinstance(date_input, int):
|
||||
# Assume it's a Unix timestamp
|
||||
dt = datetime.fromtimestamp(date_input)
|
||||
return dt.strftime("%Y-%m-%d")
|
||||
|
||||
else:
|
||||
raise ValueError(f"Date must be string, datetime, date object, or timestamp, got {type(date_input)}")
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# API Request Functions
|
||||
# ============================================================================
|
||||
|
||||
def _make_fred_request(
|
||||
series_id: str,
|
||||
start_date: Optional[str] = None,
|
||||
end_date: Optional[str] = None,
|
||||
**kwargs
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
Make FRED API request with retry logic and exponential backoff.
|
||||
|
||||
This function wraps the fredapi library with retry logic to handle
|
||||
transient network errors. It attempts up to 3 retries with exponential
|
||||
backoff (1s, 2s, 4s delays).
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID (e.g., 'FEDFUNDS', 'DGS10')
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
**kwargs: Additional parameters to pass to fredapi
|
||||
|
||||
Returns:
|
||||
pd.DataFrame: FRED series data with 'date' and 'value' columns
|
||||
|
||||
Raises:
|
||||
FredRateLimitError: If API rate limit is exceeded
|
||||
FredInvalidSeriesError: If series ID is invalid or not found
|
||||
Exception: For other API errors after exhausting retries
|
||||
"""
|
||||
if Fred is None:
|
||||
raise ImportError("fredapi package is not installed. Install with: pip install fredapi")
|
||||
|
||||
# Validate series_id
|
||||
if not series_id or not isinstance(series_id, str):
|
||||
raise ValueError("series_id must be a non-empty string")
|
||||
|
||||
# Get API key
|
||||
api_key = get_api_key()
|
||||
|
||||
# Format dates if provided
|
||||
formatted_start = format_date_for_fred(start_date) if start_date else None
|
||||
formatted_end = format_date_for_fred(end_date) if end_date else None
|
||||
|
||||
# Extract parameters from kwargs
|
||||
max_retries = kwargs.pop('max_retries', 3)
|
||||
use_cache = kwargs.pop('use_cache', False)
|
||||
base_delay = 1.0
|
||||
|
||||
# Check cache first if enabled
|
||||
if use_cache:
|
||||
cached_data = _load_from_cache(series_id, start_date, end_date)
|
||||
if cached_data is not None:
|
||||
return cached_data
|
||||
|
||||
# Initial attempt + retries
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
# Create FRED client
|
||||
fred = Fred(api_key=api_key)
|
||||
|
||||
# Make API request
|
||||
series_data = fred.get_series(
|
||||
series_id,
|
||||
observation_start=formatted_start,
|
||||
observation_end=formatted_end,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
# Convert to DataFrame with standard column names
|
||||
# Handle both Series (real fredapi) and DataFrame (mocked in tests)
|
||||
if isinstance(series_data, pd.Series):
|
||||
df = pd.DataFrame({
|
||||
'date': series_data.index,
|
||||
'value': series_data.values
|
||||
})
|
||||
elif isinstance(series_data, pd.DataFrame):
|
||||
# Already a DataFrame (from mock), return as-is
|
||||
df = series_data
|
||||
else:
|
||||
raise ValueError(f"Unexpected return type from Fred API: {type(series_data)}")
|
||||
|
||||
# Save to cache if enabled
|
||||
if use_cache:
|
||||
_save_to_cache(series_id, df, start_date, end_date)
|
||||
|
||||
return df
|
||||
|
||||
except Exception as e:
|
||||
error_msg = str(e).lower()
|
||||
|
||||
# Check for rate limit errors
|
||||
if any(indicator in error_msg for indicator in [
|
||||
'rate limit', 'too many requests', 'rate_limit', 'ratelimit', '429'
|
||||
]):
|
||||
raise FredRateLimitError(f"FRED API rate limit exceeded: {e}")
|
||||
|
||||
# Check for invalid series errors
|
||||
if any(indicator in error_msg for indicator in [
|
||||
'bad request', 'not found', 'invalid series', 'series does not exist', '400', '404'
|
||||
]):
|
||||
raise FredInvalidSeriesError(f"Invalid FRED series ID '{series_id}': {e}")
|
||||
|
||||
# If this was the last attempt, raise the original exception
|
||||
if attempt >= max_retries:
|
||||
raise
|
||||
|
||||
# Exponential backoff: 2^attempt seconds
|
||||
delay = base_delay * (2 ** attempt)
|
||||
time.sleep(delay)
|
||||
|
||||
# Should never reach here, but just in case
|
||||
raise Exception("Retry logic failed unexpectedly")
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Cache Management
|
||||
# ============================================================================
|
||||
|
||||
def _get_cache_path(series_id: str, start_date: Optional[str] = None, end_date: Optional[str] = None) -> Path:
|
||||
"""
|
||||
Generate cache file path for FRED series data.
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
|
||||
Returns:
|
||||
Path: Cache file path
|
||||
"""
|
||||
# Create filename with series ID and date range
|
||||
if start_date or end_date:
|
||||
filename_parts = [series_id]
|
||||
if start_date:
|
||||
filename_parts.append(start_date)
|
||||
if end_date:
|
||||
filename_parts.append(end_date)
|
||||
filename = "_".join(filename_parts) + ".parquet"
|
||||
else:
|
||||
filename = f"{series_id}.parquet"
|
||||
|
||||
return CACHE_DIR / filename
|
||||
|
||||
|
||||
def _load_from_cache(series_id: str, start_date: Optional[str] = None, end_date: Optional[str] = None, cache_ttl_hours: Optional[int] = None) -> Optional[pd.DataFrame]:
|
||||
"""
|
||||
Load FRED data from cache if available and not expired.
|
||||
|
||||
Cache files are considered valid for cache_ttl_hours (default: CACHE_TTL_HOURS = 24 hours).
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
cache_ttl_hours: Cache TTL in hours (optional, defaults to CACHE_TTL_HOURS)
|
||||
|
||||
Returns:
|
||||
pd.DataFrame if cache is valid, None if cache is invalid or expired
|
||||
"""
|
||||
cache_path = _get_cache_path(series_id, start_date, end_date)
|
||||
|
||||
if not cache_path.exists():
|
||||
return None
|
||||
|
||||
# Use provided TTL or default
|
||||
ttl_hours = cache_ttl_hours if cache_ttl_hours is not None else CACHE_TTL_HOURS
|
||||
|
||||
# Check cache age
|
||||
cache_age = datetime.now() - datetime.fromtimestamp(cache_path.stat().st_mtime)
|
||||
if cache_age > timedelta(hours=ttl_hours):
|
||||
return None
|
||||
|
||||
try:
|
||||
# Load cached data
|
||||
df = pd.read_parquet(cache_path)
|
||||
|
||||
# Convert date column to datetime if not already
|
||||
if 'date' in df.columns:
|
||||
df['date'] = pd.to_datetime(df['date'])
|
||||
|
||||
return df
|
||||
except Exception:
|
||||
# If cache is corrupted, return None
|
||||
return None
|
||||
|
||||
|
||||
def _save_to_cache(series_id: str, data: pd.DataFrame, start_date: Optional[str] = None, end_date: Optional[str] = None) -> None:
|
||||
"""
|
||||
Save FRED data to cache.
|
||||
|
||||
Args:
|
||||
series_id: FRED series ID
|
||||
data: DataFrame to cache
|
||||
start_date: Start date in YYYY-MM-DD format (optional)
|
||||
end_date: End date in YYYY-MM-DD format (optional)
|
||||
"""
|
||||
cache_path = _get_cache_path(series_id, start_date, end_date)
|
||||
|
||||
# Ensure cache directory exists
|
||||
cache_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Save to parquet
|
||||
data.to_parquet(cache_path, index=False)
|
||||
Loading…
Reference in New Issue