athena-client 1.0.23

An unofficial Python SDK for interacting with the OHDSI Athena Concepts API.

athena-client

An unofficial Python SDK for interacting with the OHDSI Athena Concepts API. Easily search, explore, and analyze medical concepts without any additional setup.
Developed by Alvaro A. Alvarez P. ([e-mail]).
This project is provided as-is, without warranty of any kind.

Looking for advanced concept exploration, mapping, and best practices? See the Concept Exploration Guide for a comprehensive tutorial on robust usage, advanced workflows, and real-world examples.

Responsible Usage Notice: Please use this package responsibly. Avoid making excessive or automated requests to the Athena API, as this may result in your IP being rate-limited or blocked by the API provider. Always use filters and limits where possible, and respect the terms of service of the OHDSI Athena API.

Installation

Lightweight Installation (Recommended)

For core functionality with minimal dependencies:

pip install athena-client

This installs only the essential dependencies (5 packages) needed for basic Athena API operations like concept search and exploration.

Full Installation

For all features including CLI, pandas support, and database integration:

pip install "athena-client[full]"

Individual Extras

Install only the features you need:

pip install "athena-client[cli]"      # Command-line interface
pip install "athena-client[pandas]"   # pandas DataFrame support  
pip install "athena-client[yaml]"     # YAML format support
pip install "athena-client[crypto]"   # HMAC authentication
pip install "athena-client[db]"       # Database integration

Database-Specific Installation

For specific database integrations:

pip install "athena-client[postgres]"  # PostgreSQL support
pip install "athena-client[bigquery]"  # Google BigQuery support

---

Quick Start

from athena_client import Athena

# Initialize Athena client (uses public Athena  by default)
athena = Athena()

# For custom servers, specify the base_url:
# athena = Athena(base_url="https://your-athena-server.com/api/v1")

# Search for concepts
results = athena.search("aspirin")

# Different ways to handle results
concept_list = results.all()
top_three = results.top(3)
as_json = results.to_json()
# as_df = results.to_df()  # Requires: pip install "athena-client[pandas]"

# Detailed information for a specific concept
details = athena.details(concept_id=1127433)

# Concept relationships
relationships = athena.relationships(concept_id=1127433)

# Concept graph
graph = athena.graph(concept_id=1127433, depth=3)

# Comprehensive summary
summary = athena.summary(concept_id=1127433)

💡 Try the lightweight demo: python examples/lightweight_demo.py to see what works with minimal dependencies. 🔧 Try the server configuration demo: python examples/server_configuration_demo.py to see how to connect to different Athena servers.

---

Advanced Features

Query DSL for Complex Searches

Build sophisticated queries using the Query DSL:

from athena_client.query import Q

# Basic query types
q1 = Q.term("diabetes")           # Term search
q2 = Q.phrase("heart attack")     # Phrase search  
q3 = Q.exact('"Myocardial Infarction"')  # Exact match
q4 = Q.wildcard("aspir*")         # Wildcard search

# Complex combinations
complex_query = (Q.term("diabetes") & Q.term("type 2")) | Q.term("T2DM")
fuzzy_query = Q.term("aspirin").fuzzy(0.8)  # Fuzzy matching

# Use in search
results = athena.search(complex_query)

Advanced SearchResult Features

The SearchResult class provides rich functionality:

# Pagination
next_page = results.next_page()
prev_page = results.previous_page()

# Pagination info
print(f"Total elements: {results.total_elements}")
print(f"Total pages: {results.total_pages}")
print(f"Current page: {results.current_page}")
print(f"Page size: {results.page_size}")

# Facets and metadata
facets = results.facets

# Iteration and indexing
for concept in results:  # Iterate over concepts
    print(concept.name)

concept = results[0]  # Index access

Progress Tracking for Large Queries

The library automatically handles large queries with progress tracking:

# Large queries show progress automatically
results = athena.search("pain")  # Shows progress bar

# Custom progress tracking
from athena_client.utils import progress_context

with progress_context(total=1000, description="Searching..."):
    results = athena.search("large query")

Advanced CLI Usage

The CLI supports powerful filtering and output options:

# Advanced search with filters
athena search "aspirin" --fuzzy --domain Drug --vocabulary RxNorm --limit 10

# Relationships with filters
athena relationships 1127433 --relationship-id "Maps to" --only-standard

# Graph with custom parameters
athena graph 1127433 --depth 3 --zoom-level 4

# Multiple output formats
athena search "aspirin" --output json --limit 5
athena search "aspirin" --output csv | tail -n +2 > aspirin.csv

Concept Exploration (Advanced)

For advanced concept discovery and mapping:

import asyncio
from athena_client.concept_explorer import create_concept_explorer

async def explore_concepts():
    explorer = create_concept_explorer(athena)
    
    # Find standard concepts through exploration
    results = await explorer.find_standard_concepts(
        query="headache",
        max_exploration_depth=2,
        vocabulary_priority=['SNOMED', 'RxNorm']
    )
    
    # Map concepts with confidence scores
    mappings = await explorer.map_to_standard_concepts(
        query="migraine",
        target_vocabularies=['SNOMED'],
        confidence_threshold=0.7
    )
    
    # Get alternative query suggestions
    suggestions = await explorer.suggest_alternative_queries("heart attack")

asyncio.run(explore_concepts())

📚 For detailed concept exploration examples and best practices, see the Concept Exploration Guide.

---

Server Configuration

The athena-client can connect to different Athena API servers. By default, it connects to the public OHDSI Athena API at https://athena.ohdsi.org/api/v1.

Connecting to Different Servers

Method 1: Direct Configuration (Recommended)

from athena_client import Athena

# Connect to a custom Athena server
athena = Athena(base_url="https://your-athena-server.com/api/v1")

# Connect with authentication
athena = Athena(
    base_url="https://your-athena-server.com/api/v1",
    token="your-bearer-token"
)

# Connect with HMAC authentication
athena = Athena(
    base_url="https://your-athena-server.com/api/v1",
    client_id="your-client-id",
    private_key="your-private-key"
)

Method 2: Environment Variables

Set environment variables for persistent configuration:

# Set the base URL
export ATHENA_BASE_URL="https://your-athena-server.com/api/v1"

# Set authentication (optional)
export ATHENA_TOKEN="your-bearer-token"
export ATHENA_CLIENT_ID="your-client-id"
export ATHENA_PRIVATE_KEY="your-private-key"

Method 3: .env File

Create a .env file in your project directory:

ATHENA_BASE_URL=https://your-athena-server.com/api/v1
ATHENA_TOKEN=your-bearer-token
ATHENA_CLIENT_ID=your-client-id
ATHENA_PRIVATE_KEY=your-private-key

CLI Server Configuration

Configure the CLI to use a different server:

# Use command-line options (--base-url applies to all commands)
athena --base-url "https://your-athena-server.com/api/v1" search "aspirin"
athena --base-url "https://your-athena-server.com/api/v1" details 1127433

# Use environment variables
export ATHENA_BASE_URL="https://your-athena-server.com/api/v1"
athena search "aspirin"

Advanced Configuration Options

The client supports additional configuration for different server environments:

from athena_client import Athena

# Custom timeout and retry settings for slower servers
athena = Athena(
    base_url="https://your-athena-server.com/api/v1",
    timeout=60,           # 60 second timeout
    max_retries=5,        # 5 retry attempts
    enable_throttling=True  # Respect server rate limits
)

# Disable throttling for local development servers
athena = Athena(
    base_url="http://localhost:8080/api/v1",
    enable_throttling=False
)

Configuration Precedence

Settings are applied in this order (highest to lowest priority):

1. Direct parameters in Athena() constructor
2. Environment variables (e.g., ATHENA_BASE_URL)
3. Default values (public OHDSI Athena API)

Common Server Scenarios

Scenario	Configuration
Public OHDSI Athena	Athena() (default)
Private Athena Instance	Athena(base_url="https://your-server.com/api/v1")
Local Development	Athena(base_url="http://localhost:8080/api/v1")
Authenticated Server	Athena(base_url="...", token="...")
High-Latency Network	Athena(base_url="...", timeout=120, max_retries=5)

---

CLI Quick Start

Athena CLI allows rapid concept search and exploration:

# Install CLI first: pip install "athena-client[cli]"
athena search "aspirin" --limit 3 --output json
athena details 1127433
athena relationships 1127433
athena graph 1127433 --depth 3
athena summary 1127433

# For custom servers, use --base-url:
# athena --base-url "https://your-athena-server.com/api/v1" search "aspirin"

CLI Command Reference

Command	Description	Example
search	Search for concepts	athena search "aspirin" --limit 5
details	Get concept details	athena details 1127433
relationships	Get concept relationships	athena relationships 1127433
graph	Get concept graph	athena graph 1127433 --depth 2
summary	Get comprehensive summary	athena summary 1127433
generate-set	Generate concept set (experimental)	athena generate-set "diabetes"

Output Formats

The CLI supports multiple output formats:

# JSON output
athena search "aspirin" --output json

# YAML output (requires: pip install "athena-client[yaml]")
athena search "aspirin" --output yaml

# CSV output
athena search "aspirin" --output csv

# Pretty table (default)
athena search "aspirin" --output pretty

# Export to file
athena search "aspirin" --output json | tail -n +2 > aspirin.json

---

Dependency Comparison

Installation Method	Dependencies	Size	Features
pip install athena-client	5 packages	~2MB	Core API functionality
pip install "athena-client[cli]"	+2 packages	~5MB	+ Command-line interface
pip install "athena-client[pandas]"	+1 package	~15MB	+ DataFrame support
pip install "athena-client[yaml]"	+1 package	~1MB	+ YAML format support
pip install "athena-client[crypto]"	+1 package	~4MB	+ HMAC authentication
pip install "athena-client[db]"	+2 packages	~3MB	+ Database integration
pip install "athena-client[full]"	+6 packages	~25MB	All features

---

Experimental: Database Integration (Advanced Users)

Warning: Database integration features are experimental, subject to change, and may encounter errors.

Experimental database integration allows validation and concept set generation against your local OMOP database. Use these features cautiously.

Installation for Database Support

For specific database integrations:

• PostgreSQL:

  pip install "athena-client[postgres]"
  

• Google BigQuery:

  pip install "athena-client[bigquery]"
  

• All database support:

  pip install "athena-client[db]"
  

Reducing Dependency Conflicts (Advanced)

To minimize dependency issues:

• Use specific extras when installing.
• For BigQuery integration, use Python 3.9 and SQLAlchemy < 1.5.0.

Database Usage Example

import asyncio
from athena_client import Athena

DB_CONNECTION_STRING = "postgresql://user:pass@localhost/omop_cdm"

async def main():
    athena = Athena()
    concept_set = await athena.generate_concept_set(
        query="Type 2 Diabetes",
        db_connection_string=DB_CONNECTION_STRING
    )
    print(concept_set)

asyncio.run(main())

---

Experimental CLI Database Example

export OMOP_DB_CONNECTION="postgresql://user:pass@localhost/omop"
athena generate-set "Type 2 Diabetes" --output json

---

Error Handling & Retry Logic

The library provides robust error handling and automatic retry:

from athena_client import Athena

# Automatic retry on network errors
athena = Athena(max_retries=3, timeout=30)

# Per-call retry configuration
results = athena.search(
    "aspirin",
    auto_retry=True,
    max_retries=5,
    retry_delay=2.0,
    show_progress=True
)

# Disable retry for specific calls
results = athena.search("aspirin", auto_retry=False)

Error Types

• NetworkError: DNS, connection, socket issues
• TimeoutError: Request timeout
• ClientError: 4xx HTTP status codes
• ServerError: 5xx HTTP status codes
• AuthenticationError: 401/403
• RateLimitError: 429
• ValidationError: Data validation
• APIError: API-specific errors

📚 For detailed error handling examples and troubleshooting, see the Concept Exploration Guide.

---

Troubleshooting Common Issues

• Dependency installation problems: Ensure Python version compatibility and correct extras.
• PostgreSQL build errors: Install PostgreSQL development tools (brew install postgresql on macOS).
• BigQuery SQLAlchemy conflicts: Only use Python 3.9 with BigQuery integration.
• Connection issues: Verify your server URL and network connectivity. Use --base-url or ATHENA_BASE_URL environment variable to specify custom servers.

---

Exporting CLI Results to Files (JSON, YAML, CSV)

You can export CLI search results to various formats:

# Install CLI first: pip install "athena-client[cli]"
# For YAML support: pip install "athena-client[yaml]"

athena search "aspirin" --output json | tail -n +2 > aspirin_concepts.json
athena search "aspirin" --output yaml | tail -n +2 > aspirin_concepts.yaml
athena search "aspirin" --output csv  | tail -n +2 > aspirin_concepts.csv

Note: The tail -n +2 removes warning lines (such as large query warnings) to ensure the output file is valid for the chosen format.

---

Version Compatibility

• Python: >= 3.9, < 3.13
• SQLAlchemy: >= 1.4.0 (BigQuery limited to <1.5.0)
• pandas: >= 1.3.0, < 3.0.0
• pydantic: >= 2.0.0
• httpx: >= 0.18.0
• cryptography: >= 36.0.0

---

Examples & Demos

The library includes several example scripts to demonstrate its capabilities:

• examples/lightweight_demo.py - Core functionality with minimal dependencies
• examples/server_configuration_demo.py - Connecting to different Athena servers
• examples/error_handling_demo.py - Error handling and retry logic
• examples/retry_throttling_demo.py - Advanced retry and throttling features
• examples/large_query_demo.py - Handling large queries with progress tracking
• examples/graph_demo.py - Concept graph exploration and analysis
• examples/concept_exploration_demo.py - Advanced concept discovery features

Run any example with:

python examples/example_name.py

---

What's Next?

• 📚 Concept Exploration Guide - Advanced usage, best practices, and real-world examples
• 🔧 Contributing Guide - How to contribute to the project
• 🗺️ Roadmap - Planned features and enhancements
• 📦 Lightweight Installation Guide - Detailed dependency management