### Setup Django integration: install, configure, migrate

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/django_integration.rst.txt

Install the package with Django dependencies, add the app to INSTALLED_APPS, configure the FDC client settings, and run migrations to create the necessary database tables.

```bash
pip install usda-fdc[django]
```

```python
INSTALLED_APPS = [
    # ...
    'usda_fdc.django',
    # ...
]
```

```python
# USDA FDC settings
FDC_API_KEY = "your_api_key_here"
FDC_API_URL = "https://api.nal.usda.gov/fdc/v1"
FDC_CACHE_ENABLED = True
FDC_CACHE_TIMEOUT = 86400  # 24 hours in seconds
```

```bash
python manage.py migrate
```

--------------------------------

### Install Documentation Dependencies from requirements-docs.txt

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/installation.html

Installs documentation dependencies from the requirements-docs.txt file.

```bash
pip install -r requirements-docs.txt
```

--------------------------------

### Documentation Installation

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/installation.rst.txt

Installs the package with documentation dependencies using the extras or the requirements file.

```bash
pip install -e ".[docs]"
```

```bash
pip install -r requirements-docs.txt
```

--------------------------------

### Install with Documentation Dependencies

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/installation.html

Installs the package with documentation dependencies to build the documentation locally.

```bash
pip install -e ".[docs]"
```

--------------------------------

### Development Installation

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/installation.rst.txt

Installs the package with development dependencies using the extras or the requirements file.

```bash
pip install -e ".[dev]"
```

```bash
pip install -r requirements-dev.txt
```

--------------------------------

### Example: get nutrients in JSON format

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Gets nutrient information in JSON format using the --format json option.

```bash
fdc nutrients 1750340 --format json
```

--------------------------------

### Install Development Dependencies from requirements-dev.txt

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/installation.html

Installs development dependencies from the requirements-dev.txt file.

```bash
pip install -r requirements-dev.txt
```

--------------------------------

### Install usda-fdc from source

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/index.rst.txt

Clone the repository and install the package in editable mode for development.

```bash
git clone https://github.com/yourusername/usda_fdc.git
cd usda_fdc
pip install -e .
```

--------------------------------

### Install Django Dependencies from requirements-django.txt

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/installation.html

Installs Django dependencies from the requirements-django.txt file.

```bash
pip install -r requirements-django.txt
```

--------------------------------

### Install usda-fdc with pip

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/index.rst.txt

Install the usda-fdc package from PyPI using pip.

```bash
pip install usda-fdc
```

--------------------------------

### .env File Example

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/configuration.rst.txt

Example contents of a .env file for the USDA FDC client. Place this file in your project root and load it with python-dotenv.

```bash
FDC_API_KEY=your_api_key_here
FDC_API_URL=https://api.nal.usda.gov/fdc/v1
FDC_CACHE_ENABLED=True
FDC_CACHE_TIMEOUT=86400
```

--------------------------------

### Install development dependencies

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/contributing.rst.txt

Installs the package in editable mode along with development dependencies.

```bash
pip install -e ".[dev]"
```

--------------------------------

### Module imports and unit registry setup

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/utils.html

Imports required modules and initializes the Pint unit registry with common food measurement units.

```python
import re
from typing import Dict, Any, Optional, Tuple, Union
from pint import UnitRegistry, UndefinedUnitError, DimensionalityError

# Initialize unit registry
ureg = UnitRegistry()

# Define common food measurement units
ureg.define('serving = 1 = serving')
ureg.define('cup = 236.588 * milliliter = cup')
ureg.define('tablespoon = 14.7868 * milliliter = tbsp')
ureg.define('teaspoon = 4.92892 * milliliter = tsp')
ureg.define('ounce = 28.3495 * gram = oz')
ureg.define('pound = 453.592 * gram = lb')
ureg.define('slice = 1 = slice')
ureg.define('piece = 1 = piece')
```

--------------------------------

### Example: search for apple

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Searches for foods containing 'apple'.

```bash
fdc search "apple"
```

--------------------------------

### Command-line interface usage

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Shows common fdc CLI commands for searching foods, getting food details, getting nutrients, and listing foods.

```bash
# Search for foods
fdc search "apple" --page-size 5

# Get food details
fdc food 1750340

# Get nutrients for a food
fdc nutrients 1750340

# List foods
fdc list --page-size 10 --page-number 1
```

--------------------------------

### Django Integration Installation

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/installation.rst.txt

Installs the package with Django dependencies using the extras or the requirements file.

```bash
pip install -e ".[django]"
```

```bash
pip install -r requirements-django.txt
```

--------------------------------

### Install usda-fdc with Django dependencies

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/django_integration.html

Installs the USDA FDC library with Django integration dependencies.

```bash
pip install usda-fdc[django]

```

--------------------------------

### Example: list branded foods

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Lists only branded foods using the --data-type option.

```bash
fdc list --data-type "Branded"
```

--------------------------------

### Example tests for FdcClient

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/testing.rst.txt

Example pytest tests for the FdcClient class, covering a successful search and an API error case. Uses a fixture to create a client with a test API key and mocks the _make_request method.

```python
import pytest
from unittest.mock import patch, MagicMock
from usda_fdc import FdcClient, FdcApiError

@pytest.fixture
def client():
    return FdcClient(api_key="test_key")

def test_search_success(client):
    # Mock the API response
    mock_response = {
        "totalHits": 1,
        "currentPage": 1,
        "totalPages": 1,
        "foods": [
            {
                "fdcId": 1234,
                "description": "Test Food",
                "dataType": "Branded"
            }
        ]
    }
    
    with patch.object(client, "_make_request", return_value=mock_response):
        result = client.search("test")
        
        assert result.total_hits == 1
        assert len(result.foods) == 1
        assert result.foods[0].fdc_id == 1234
        assert result.foods[0].description == "Test Food"

def test_search_api_error(client):
    with patch.object(client, "_make_request", side_effect=FdcApiError("API error")):
        with pytest.raises(FdcApiError):
            client.search("test")
```

--------------------------------

### fdc search command example

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/cli.html

Searches for foods using keywords, with options to control page size and page number.

```bash
fdc search "apple" --page-size 10 --page-number 1
```

--------------------------------

### Basic Error Handling with FdcClient

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/error_handling.html

Basic error handling example showing how to catch specific exceptions like FdcAuthError and FdcRateLimitError, with a fallback for generic FdcApiError and Exception.

```python
from usda_fdc import FdcClient, FdcApiError, FdcAuthError, FdcRateLimitError

client = FdcClient(api_key="your_api_key_here")

try:
    food = client.get_food(1750340)
except FdcAuthError:
    print("Authentication failed. Check your API key.")
except FdcRateLimitError:
    print("Rate limit exceeded. Try again later.")
except FdcApiError as e:
    print(f"API error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

```

--------------------------------

### Rate Limiting with RateLimitedClient

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/advanced_usage.html

Implement a rate-limited client by overriding `_make_request` to enforce a maximum number of requests per minute. The example sets `requests_per_minute=5` and uses `time.sleep` to wait between requests.

```python
import time
from usda_fdc import FdcClient

class RateLimitedClient(FdcClient):
    def __init__(self, api_key, requests_per_minute=10, **kwargs):
        super().__init__(api_key, **kwargs)
        self.requests_per_minute = requests_per_minute
        self.interval = 60 / requests_per_minute
        self.last_request_time = 0

    def _make_request(self, endpoint, method="GET", params=None, data=None):
        # Wait if needed
        current_time = time.time()
        time_since_last = current_time - self.last_request_time

        if time_since_last < self.interval:
            time.sleep(self.interval - time_since_last)

        # Make the request
        result = super()._make_request(endpoint, method, params, data)

        # Update last request time
        self.last_request_time = time.time()

        return result

# Use the rate-limited client
client = RateLimitedClient(
    api_key="your_api_key_here",
    requests_per_minute=5  # Maximum 5 requests per minute
)

```

--------------------------------

### Mock _make_request with unittest.mock

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/testing.rst.txt

Example unit test for the _make_request method using unittest.mock to patch requests.Session.request. Verifies the method returns the JSON response and that the request is called once.

```python
from unittest.mock import patch, MagicMock

@patch("requests.Session.request")
def test_make_request(mock_request, client):
    mock_response = MagicMock()
    mock_response.status_code = 200
    mock_response.json.return_value = {"key": "value"}
    mock_request.return_value = mock_response
    
    result = client._make_request("endpoint")
    
    assert result == {"key": "value"}
    mock_request.assert_called_once()
```

--------------------------------

### Custom API request with _make_request

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/advanced_usage.rst.txt

Use the low-level _make_request method for custom API requests. Requires an API key. The example shows a search for 'apple' with pagination and sorting parameters.

```python
from usda_fdc import FdcClient

client = FdcClient(api_key="your_api_key_here")

# Make a custom request
data = client._make_request(
    endpoint="foods/search",
    params={
        "query": "apple",
        "pageSize": 25,
        "pageNumber": 1,
        "sortBy": "dataType.keyword",
        "sortOrder": "asc"
    }
)
```

--------------------------------

### fdc nutrients command

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Gets nutrient information for a specific food by its FDC ID.

```bash
fdc nutrients 1750340
```

--------------------------------

### Unit conversion with convert_measurement and parse_unit_and_value

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/advanced_usage.rst.txt

Convert between measurement units and parse measurement strings. The example converts 1 cup to grams, parses '2.5 tbsp', and converts 1 oz to grams.

```python
from usda_fdc.utils import convert_measurement, parse_unit_and_value

# Convert between units
grams = convert_measurement(1, "cup", "g")
print(f"1 cup = {grams} grams")

# Parse a measurement string
amount, unit = parse_unit_and_value("2.5 tbsp")
print(f"Amount: {amount}, Unit: {unit}")

# Convert to grams
from usda_fdc.utils import convert_to_grams

grams = convert_to_grams(1, "oz")
print(f"1 oz = {grams} grams")
```

--------------------------------

### Cache popular foods with background tasks using async_task

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/django_integration.rst.txt

Define a function to cache popular foods and schedule it as a background task using Django Q's async_task. The example shows integration with task queues like Celery or Django Q.

```python
from usda_fdc.django import FdcCache

def cache_popular_foods():
    cache = FdcCache()
    popular_ids = [1750340, 1750341, 1750342]  # Example IDs
    cache.get_foods(popular_ids)

# Use with Celery, Django Q, or other task queues
from django_q.tasks import async_task

async_task(cache_popular_foods)
```

--------------------------------

### Set up pre-commit hooks

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/contributing.rst.txt

Sets up pre-commit hooks for the repository.

```bash
pre-commit install
```

--------------------------------

### Use .env file for API key

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Shows how to use a .env file to set the API key and then run a search.

```bash
# .env file
FDC_API_KEY=your_api_key_here

# Then run
fdc search "apple"
```

--------------------------------

### Build documentation locally

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/contributing.rst.txt

Builds the documentation locally using Sphinx's make html command and opens the generated HTML in a browser.

```bash
cd docs
make html
# Open _build/html/index.html in your browser
```

--------------------------------

### FdcClient.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes the FDC client with an API key and optional base URL. Sets up the session for making HTTP requests.

```APIDOC
## FdcClient.__init__()

### Description
Initializes the FDC client with an API key and optional base URL. Sets up the session for making HTTP requests.

### Method
Constructor

### Signature
`FdcClient(api_key: str, base_url: str = None)`

### Parameters
- **api_key** (str) - Required - The API key for authenticating with the USDA FDC API.
- **base_url** (str) - Optional - The base URL for the FDC API. Defaults to the official API endpoint.

### Attributes
- **api_key** (str) - The API key used for authentication.
- **base_url** (str) - The base URL for API requests.
- **session** (requests.Session) - The HTTP session used for making requests.
```

--------------------------------

### Food.__init__(fdc_id, description, data_type, publication_date=None, food_class=None, food_category=None, scientific_name=None, brand_owner=None, brand_name=None, ingredients=None, serving_size=None, serving_size_unit=None, household_serving_fulltext=None, nutrients=<factory>, food_portions=<factory>)

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/models.html

Constructor for the Food class. Initializes a Food object with all its attributes, including optional fields and lists of nutrients and food portions.

```APIDOC
## Food.__init__(fdc_id, description, data_type, publication_date=None, food_class=None, food_category=None, scientific_name=None, brand_owner=None, brand_name=None, ingredients=None, serving_size=None, serving_size_unit=None, household_serving_fulltext=None, nutrients=<factory>, food_portions=<factory>)

### Description
Initializes a Food instance.

### Parameters
- **fdc_id** (int) - Required - Food Data Central ID.
- **description** (str) - Required - Description of the food.
- **data_type** (str) - Required - Type of data (e.g., 'branded', 'survey').
- **publication_date** (str | None) - Optional - Publication date.
- **food_class** (str | None) - Optional - Food class.
- **food_category** (str | None) - Optional - Food category.
- **scientific_name** (str | None) - Optional - Scientific name.
- **brand_owner** (str | None) - Optional - Brand owner.
- **brand_name** (str | None) - Optional - Brand name.
- **ingredients** (str | None) - Optional - Ingredients list.
- **serving_size** (float | None) - Optional - Serving size.
- **serving_size_unit** (str | None) - Optional - Unit of serving size.
- **household_serving_fulltext** (str | None) - Optional - Household serving full text.
- **nutrients** (List[Nutrient]) - Optional - List of nutrients.
- **food_portions** (List[FoodPortion]) - Optional - List of food portions.

### Returns
- None
```

--------------------------------

### main()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Main entry point for the command-line interface. Parses arguments and dispatches to subcommands.

```APIDOC
## main()

### Description
Main entry point for the command-line interface. Parses arguments and dispatches to subcommands.

### Method
main

### Signature
`main(argv: List[str] = None)`

### Parameters
- **argv** (List[str]) - Optional - Command-line arguments. Defaults to sys.argv[1:].

### Returns
- **int** - Exit code.
```

--------------------------------

### list_foods

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/client.html

Get a paged list of foods.

```APIDOC
## list_foods(data_type=None, page_size=50, page_number=1, sort_by=None, sort_order=None)

### Description
Get a paged list of foods.

### Method
list_foods

### Parameters
- **data_type** (Optional[List[str]]) - Optional - Filter on specific data types.
- **page_size** (int) - Optional - Maximum number of results to return (1-200). Default: 50.
- **page_number** (int) - Optional - Page number to retrieve. Default: 1.
- **sort_by** (Optional[str]) - Optional - Field to sort by.
- **sort_order** (Optional[str]) - Optional - Sort direction ("asc" or "desc").

### Returns
A list of Food objects.
```

--------------------------------

### get_foods

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/client.html

Get detailed information for multiple foods by FDC ID.

```APIDOC
## get_foods(fdc_ids, format="full", nutrients=None)

### Description
Get detailed information for multiple foods by FDC ID.

### Method
get_foods

### Parameters
- **fdc_ids** (List[Union[str, int]]) - Required - List of FDC IDs (max 20).
- **format** (str) - Optional - The format of the response ("full" or "abridged"). Default: "full".
- **nutrients** (Optional[List[int]]) - Optional - List of up to 25 nutrient numbers to include.

### Returns
A list of Food objects.
```

--------------------------------

### SearchResultFood.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes a SearchResultFood object with its attributes.

```APIDOC
## SearchResultFood.__init__()

### Description
Initializes a SearchResultFood object with its attributes.

### Method
Constructor

### Signature
`SearchResultFood(fdc_id: int, description: str, data_type: str, publication_date: str = None, food_category: str = None, brand_owner: str = None, brand_name: str = None)`

### Parameters
- **fdc_id** (int) - Required - The FDC ID.
- **description** (str) - Required - The food description.
- **data_type** (str) - Required - The data type.
- **publication_date** (str) - Optional - The publication date.
- **food_category** (str) - Optional - The food category.
- **brand_owner** (str) - Optional - The brand owner.
- **brand_name** (str) - Optional - The brand name.
```

--------------------------------

### fdc nutrients FOOD_ID

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Get nutrient information for a specific food by its FDC ID.

```APIDOC
## fdc nutrients FOOD_ID

### Description
Get nutrient information for a specific food.

### Method
CLI

### Endpoint
fdc nutrients

### Parameters
#### Arguments
- **FOOD_ID** (integer) - Required - FDC ID of the food (e.g., 1750340)

### Request Example
```bash
fdc nutrients 1750340 --format json
```

### Response
#### Success Response
Nutrient information in the specified format.

```

--------------------------------

### Global options for fdc

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Lists global options that apply to all fdc commands: --api-key, --format, --version, --help.

```bash
--api-key KEY       FDC API key (can also be set via FDC_API_KEY environment variable)
--format FORMAT     Output format: json, pretty, or text (default: pretty)
--version           Show version and exit
--help              Show help message and exit
```

--------------------------------

### fdc food FOOD_ID

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Get detailed information about a specific food by its FDC ID.

```APIDOC
## fdc food FOOD_ID

### Description
Get detailed information about a specific food.

### Method
CLI

### Endpoint
fdc food

### Parameters
#### Arguments
- **FOOD_ID** (integer) - Required - FDC ID of the food (e.g., 1750340)

### Request Example
```bash
fdc food 1750340
```

### Response
#### Success Response
Detailed food information in the specified format.

```

--------------------------------

### fdc food command

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Gets detailed information about a specific food by its FDC ID.

```bash
fdc food 1750340
```

--------------------------------

### Food.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes a Food object with its attributes. Typically not called directly; use from_api_data instead.

```APIDOC
## Food.__init__()

### Description
Initializes a Food object with its attributes. Typically not called directly; use from_api_data instead.

### Method
Constructor

### Signature
`Food(fdc_id: int, description: str, data_type: str, publication_date: str = None, food_class: str = None, food_category: str = None, scientific_name: str = None, brand_owner: str = None, brand_name: str = None, ingredients: str = None, serving_size: float = None, serving_size_unit: str = None, household_serving_fulltext: str = None, nutrients: List[Nutrient] = None, food_portions: List[FoodPortion] = None)`

### Parameters
- **fdc_id** (int) - Required - The unique FDC ID.
- **description** (str) - Required - The food description.
- **data_type** (str) - Required - The data type (e.g., 'Foundation').
- **publication_date** (str) - Optional - The publication date.
- **food_class** (str) - Optional - The food class.
- **food_category** (str) - Optional - The food category.
- **scientific_name** (str) - Optional - The scientific name.
- **brand_owner** (str) - Optional - The brand owner.
- **brand_name** (str) - Optional - The brand name.
- **ingredients** (str) - Optional - The ingredients.
- **serving_size** (float) - Optional - The serving size.
- **serving_size_unit** (str) - Optional - The unit of serving size.
- **household_serving_fulltext** (str) - Optional - Household serving full text.
- **nutrients** (List[Nutrient]) - Optional - List of nutrients.
- **food_portions** (List[FoodPortion]) - Optional - List of food portions.
```

--------------------------------

### Set API key via environment variable

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Shows how to set the FDC_API_KEY environment variable and then run a search.

```bash
export FDC_API_KEY=your_api_key_here
fdc search "apple"
```

--------------------------------

### Filter foods by data type

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Filters foods by data type using the data_type parameter. Shows examples for 'Branded' and for 'Foundation' and 'SR Legacy'.

```python
# Get only branded foods
branded_foods = client.list_foods(data_type=["Branded"])

# Get foundation and SR Legacy foods
foundation_foods = client.list_foods(data_type=["Foundation", "SR Legacy"])
```

--------------------------------

### Get multiple foods by FDC IDs

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Retrieves information for multiple foods at once using a list of FDC IDs and prints each food's description and data type.

```python
# Get multiple foods by FDC ID
foods = client.get_foods([1750340, 1750341, 1750342])

# Process foods
for food in foods:
    print(f"{food.description} ({food.data_type})")
```

--------------------------------

### Import and initialize FdcClient with API key

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Loads the API key from a .env file using python-dotenv and initializes the FdcClient. Requires the FDC_API_KEY environment variable to be set.

```python
from usda_fdc import FdcClient
import os
from dotenv import load_dotenv

# Load API key from .env file
load_dotenv()
api_key = os.getenv("FDC_API_KEY")

# Initialize client
client = FdcClient(api_key)
```

--------------------------------

### FoodPortion.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes a FoodPortion object with its attributes.

```APIDOC
## FoodPortion.__init__()

### Description
Initializes a FoodPortion object with its attributes.

### Method
Constructor

### Signature
`FoodPortion(id: int, amount: float, gram_weight: float, portion_description: str = None, modifier: str = None, measure_unit: str = None)`

### Parameters
- **id** (int) - Required - The portion ID.
- **amount** (float) - Required - The amount.
- **gram_weight** (float) - Required - The gram weight.
- **portion_description** (str) - Optional - The portion description.
- **modifier** (str) - Optional - The modifier.
- **measure_unit** (str) - Optional - The measure unit.
```

--------------------------------

### Client Initialization with API Key and Custom URL

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/configuration.rst.txt

Initialize the FdcClient with an API key and optionally a custom base URL. The base_url overrides the default API endpoint.

```python
from usda_fdc import FdcClient

# Basic initialization with API key
client = FdcClient(api_key="your_api_key_here")

# Custom API URL
client = FdcClient(
    api_key="your_api_key_here",
    base_url="https://custom-api-url.example.com"
)
```

--------------------------------

### Get food details by FDC ID

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Retrieves detailed information for a specific food using its FDC ID, including description, data type, brand name, and nutrient amounts.

```python
# Get food by FDC ID
food = client.get_food(1750340)

# Print food details
print(f"Food: {food.description}")
print(f"Data Type: {food.data_type}")
print(f"Brand: {food.brand_name}")

# Print nutrients
print("\nNutrients:")
for nutrient in food.nutrients:
    print(f"{nutrient.name}: {nutrient.amount} {nutrient.unit_name}")
```

--------------------------------

### Initialize FdcClient with API key and base URL

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/client.html

Initializes the FDC client with an optional API key and base URL. If no API key is provided, it falls back to the FDC_API_KEY environment variable; if neither is available, a ValueError is raised. The default base URL is https://api.nal.usda.gov/fdc/v1/.

```python
class FdcClient:
    """
    Client for interacting with the USDA Food Data Central API.
    
    Attributes:
        api_key (str): The API key for authenticating with the FDC API.
        base_url (str): The base URL for the FDC API.
        session (requests.Session): A session object for making HTTP requests.
    """
    

    def __init__(
        self, 
        api_key: Optional[str] = None, 
        base_url: str = "https://api.nal.usda.gov/fdc/v1/"
    ):
        """
        Initialize the FDC client.
        
        Args:
            api_key: The API key for authenticating with the FDC API.
                If not provided, will look for FDC_API_KEY environment variable.
            base_url: The base URL for the FDC API.
        
        Raises:
            ValueError: If no API key is provided or found in environment variables.
        """
        self.api_key = api_key or os.environ.get("FDC_API_KEY")
        if not self.api_key:
            raise ValueError(
                "No API key provided. Pass api_key parameter or set FDC_API_KEY environment variable."
            )
        
        self.base_url = base_url
        self.session = requests.Session()
```

--------------------------------

### FdcClient.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/dev/contributing.html

Initializes a new FdcClient instance with the provided API key and base URL. This constructor sets up the client for making requests to the USDA Food Data Central API.

```APIDOC
## FdcClient.__init__()

### Description
Initializes a new FdcClient instance with the provided API key and base URL. This constructor sets up the client for making requests to the USDA Food Data Central API.

### Method
Constructor

### Signature
`FdcClient(api_key: str, base_url: str = "https://api.nal.usda.gov/fdc/v1")`

### Parameters
- **api_key** (str) - Required - The API key for authenticating with the USDA FDC API.
- **base_url** (str) - Optional - The base URL for the FDC API. Defaults to `https://api.nal.usda.gov/fdc/v1`.

### Attributes
- **api_key** (str) - The API key used for authentication.
- **base_url** (str) - The base URL for the API.
- **session** (requests.Session) - The HTTP session used for making requests.
```

--------------------------------

### Nutrient.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes a Nutrient object with its attributes.

```APIDOC
## Nutrient.__init__()

### Description
Initializes a Nutrient object with its attributes.

### Method
Constructor

### Signature
`Nutrient(id: int, name: str, amount: float, unit_name: str, nutrient_nbr: int = None, rank: int = None)`

### Parameters
- **id** (int) - Required - The nutrient ID.
- **name** (str) - Required - The nutrient name.
- **amount** (float) - Required - The amount of the nutrient.
- **unit_name** (str) - Required - The unit name (e.g., 'g', 'mg').
- **nutrient_nbr** (int) - Optional - The nutrient number.
- **rank** (int) - Optional - The rank.
```

--------------------------------

### Clone the repository

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/contributing.rst.txt

Clones the forked repository and navigates into the project directory.

```bash
git clone https://github.com/yourusername/usda_fdc.git
cd usda_fdc
```

--------------------------------

### Use FdcCache to search and get foods with caching

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/django_integration.rst.txt

Use FdcCache to search and retrieve food data with automatic caching in Django models and cache. The force_refresh=True parameter bypasses the cache and fetches from the API.

```python
from usda_fdc.django import FdcCache

# Initialize the cache
cache = FdcCache()

# Search for foods (results will be cached)
results = cache.search("apple")

# Get a food by FDC ID (will be cached in database)
food = cache.get_food(1750340)

# Get multiple foods (will use database cache when available)
foods = cache.get_foods([1750340, 1750341, 1750342])

# Force refresh from API
food = cache.get_food(1750340, force_refresh=True)
```

--------------------------------

### fdc list command with options

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Lists foods with pagination, with options for data type, page size, and page number.

```bash
fdc list --page-size 10 --page-number 1
```

```bash
--data-type TYPE    Filter by data type (can be specified multiple times)
--page-size SIZE    Results per page (default: 10)
--page-number NUM   Page number (default: 1)
```

--------------------------------

### Upload to PyPI

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Upload the built distribution packages to PyPI.

```bash
python -m twine upload dist/*
```

--------------------------------

### Extend Food model with custom methods

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/advanced_usage.rst.txt

Extend the Food model to add custom calculations. The EnhancedFood class adds methods to calculate calories per gram and protein percentage. Requires an API key and a valid food ID (example uses 1750340).

```python
from usda_fdc import FdcClient
from usda_fdc.models import Food

class EnhancedFood(Food):
    def calculate_calories_per_gram(self):
        for nutrient in self.nutrients:
            if nutrient.name == "Energy" and nutrient.unit_name == "kcal":
                return nutrient.amount / 100  # per gram
        return 0
    
    def calculate_protein_percentage(self):
        energy = 0
        protein_energy = 0
        
        for nutrient in self.nutrients:
            if nutrient.name == "Energy" and nutrient.unit_name == "kcal":
                energy = nutrient.amount
            elif nutrient.name == "Protein" and nutrient.unit_name == "g":
                # Protein has 4 calories per gram
                protein_energy = nutrient.amount * 4
        
        if energy > 0:
            return (protein_energy / energy) * 100
        return 0

# Use the enhanced class
client = FdcClient(api_key="your_api_key_here")
food_data = client.get_food(1750340)

# Convert to enhanced food
enhanced_food = EnhancedFood(
    fdc_id=food_data.fdc_id,
    description=food_data.description,
    data_type=food_data.data_type,
    nutrients=food_data.nutrients,
    food_portions=food_data.food_portions
)

print(f"Calories per gram: {enhanced_food.calculate_calories_per_gram()}")
print(f"Protein percentage: {enhanced_food.calculate_protein_percentage()}%")
```

--------------------------------

### Query food data with Django ORM using FoodModel and NutrientModel

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/django_integration.rst.txt

Query food data directly using Django's ORM with FoodModel and NutrientModel. The example filters branded foods and retrieves foods with protein amount greater than 20, using select_related to optimize queries.

```python
from usda_fdc.django.models import FoodModel, NutrientModel

# Query foods directly using Django's ORM
branded_foods = FoodModel.objects.filter(data_type="Branded")

# Get foods with specific nutrients
high_protein = NutrientModel.objects.filter(
    name="Protein",
    amount__gt=20
).select_related('food')

for nutrient in high_protein:
    print(f"{nutrient.food.description}: {nutrient.amount}g protein")
```

--------------------------------

### Set next development version

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Set the next development version in usda_fdc/__init__.py after releasing.

```python
__version__ = "X.Y+1.0.dev0"
```

--------------------------------

### CLI Configuration with Environment Variable and Argument

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/configuration.rst.txt

Configure the CLI using an environment variable or a command-line argument. Set FDC_API_KEY or pass --api-key to the fdc command.

```bash
# Set environment variable
export FDC_API_KEY=your_api_key_here

# Use the CLI
fdc search "apple"

# Or provide the API key as an argument
fdc --api-key your_api_key_here search "apple"
```

--------------------------------

### Create git tag

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Create an annotated git tag for the release version.

```bash
git tag -a vX.Y.Z -m "Version X.Y.Z"
```

--------------------------------

### Build distribution packages

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Build distribution packages. Creates both a source distribution and a wheel in the dist/ directory.

```bash
python -m build
```

--------------------------------

### Update version in usda_fdc/__init__.py

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Set the version number in usda_fdc/__init__.py before releasing. Replace X.Y.Z with the actual version.

```python
__version__ = "X.Y.Z"
```

--------------------------------

### Run pre-commit on all files

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/contributing.rst.txt

Runs all pre-commit hooks on all files to automatically apply formatting and linting checks.

```bash
pre-commit run --all-files
```

--------------------------------

### list_command()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Handles the 'list' CLI command. Lists foods with optional filtering.

```APIDOC
## list_command()

### Description
Handles the 'list' CLI command. Lists foods with optional filtering.

### Method
list_command

### Signature
`list_command(args)`

### Parameters
- **args** (Namespace) - Required - Parsed command-line arguments.

### Returns
- **int** - Exit code.
```

--------------------------------

### Create release commit

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Commit the version and changelog changes for the release.

```bash
git add usda_fdc/__init__.py CHANGELOG.md
git commit -m "Release vX.Y.Z"
```

--------------------------------

### fdc command syntax

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Shows the general syntax for the fdc CLI: fdc [options] <command> [command-options].

```bash
fdc [options] <command> [command-options]
```

--------------------------------

### Mock requests.Session.request with unittest.mock

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/dev/testing.html

Shows how to mock the requests.Session.request method using unittest.mock for unit tests.

```python
from unittest.mock import patch, MagicMock

@patch("requests.Session.request")
def test_make_request(mock_request, client):
    mock_response = MagicMock()
    mock_response.status_code = 200
    mock_response.json.return_value = {"key": "value"}
    mock_request.return_value = mock_response

    result = client._make_request("endpoint")

    assert result == {"key": "value"}
    mock_request.assert_called_once()

```

--------------------------------

### usda_fdc.cli source: list_command and main

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/cli.html

The source code for the usda_fdc.cli module includes two functions: list_command and main. list_command handles the 'list' subcommand, using FdcClient to fetch foods and printing them with format_output, exiting on FdcApiError. main sets up the argparse CLI with subcommands search, food, nutrients, and list, loads environment variables, and requires an API key from --api-key or FDC_API_KEY.

```python
def list_command(args: argparse.Namespace) -> None:
    """Handle list command."""
    client = FdcClient(args.api_key)
    try:
        foods = client.list_foods(
            data_type=args.data_type,
            page_size=args.page_size,
            page_number=args.page_number
        )
        
        print(f"Listing {len(foods)} foods (page {args.page_number}):")
        for food in foods:
            print(format_output(food, args.format))
            if args.format != "json":
                print("-" * 40)
    except FdcApiError as e:
        print(f"Error: {e}", file=sys.stderr)
        sys.exit(1)
```

```python
def main() -> None:
    """Main entry point for the CLI."""
    # Load environment variables from .env file
    load_dotenv()
    
    # Create the top-level parser
    parser = argparse.ArgumentParser(
        prog="fdc",
        description="USDA Food Data Central (FDC) command-line interface"
    )
    parser.add_argument(
        "--version", 
        action="version", 
        version=f"%(prog)s {__version__}"
    )
    parser.add_argument(
        "--api-key", 
        default=os.environ.get("FDC_API_KEY"),
        help="FDC API key (can also be set via FDC_API_KEY environment variable)"
    )
    parser.add_argument(
        "--format", 
        choices=["json", "pretty", "text"], 
        default="pretty",
        help="Output format (default: pretty)"
    )
    
    # Create subparsers for commands
    subparsers = parser.add_subparsers(dest="command", help="Command to execute")
    
    # Search command
    search_parser = subparsers.add_parser("search", help="Search for foods")
    search_parser.add_argument("query", help="Search query")
    search_parser.add_argument("--data-type", nargs="+", help="Filter by data type")
    search_parser.add_argument("--page-size", type=int, default=10, help="Results per page")
    search_parser.add_argument("--page-number", type=int, default=1, help="Page number")
    search_parser.set_defaults(func=search_command)
    
    # Food command
    food_parser = subparsers.add_parser("food", help="Get food details")
    food_parser.add_argument("fdc_id", help="FDC ID of the food")
    food_parser.set_defaults(func=food_command)
    
    # Nutrients command
    nutrients_parser = subparsers.add_parser("nutrients", help="Get food nutrients")
    nutrients_parser.add_argument("fdc_id", help="FDC ID of the food")
    nutrients_parser.set_defaults(func=nutrients_command)
    
    # List command
    list_parser = subparsers.add_parser("list", help="List foods")
    list_parser.add_argument("--data-type", nargs="+", help="Filter by data type")
    list_parser.add_argument("--page-size", type=int, default=10, help="Results per page")
    list_parser.add_argument("--page-number", type=int, default=1, help="Page number")
    list_parser.set_defaults(func=list_command)
    
    # Parse arguments
    args = parser.parse_args()
    
    # Check if API key is provided
    if not args.api_key:
        print("Error: No API key provided. Use --api-key or set FDC_API_KEY environment variable.", file=sys.stderr)
        sys.exit(1)
    
    # Execute command if provided
    if hasattr(args, "func"):
        args.func(args)
    else:
        parser.print_help()


if __name__ == "__main__":
    main()
```

--------------------------------

### list_command()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_modules/usda_fdc/client.html

Handles the 'list' CLI command.

```APIDOC
## list_command()

### Description
Executes the list command, listing foods with optional filters.

### Method
list_command

### Signature
`list_command(args: argparse.Namespace) -> None`

### Parameters
- **args** (argparse.Namespace) - Required - Parsed command-line arguments.

### Returns
- **None** - This function does not return a value.

```

--------------------------------

### Run integration tests with API key

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/testing.rst.txt

Sets the FDC_API_KEY environment variable and runs integration tests. Requires a valid API key.

```bash
# Set API key for integration tests
export FDC_API_KEY=your_api_key_here

# Run integration tests
pytest tests/integration/
```

--------------------------------

### Run Django migrations for FDC

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/django_integration.html

Runs Django migrations to create the necessary database tables for the FDC cache.

```bash
python manage.py migrate

```

--------------------------------

### SearchResult.__init__()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/api/cli.html

Initializes a SearchResult object with its attributes.

```APIDOC
## SearchResult.__init__()

### Description
Initializes a SearchResult object with its attributes.

### Method
Constructor

### Signature
`SearchResult(foods: List[SearchResultFood], total_hits: int, current_page: int, total_pages: int)`

### Parameters
- **foods** (List[SearchResultFood]) - Required - The list of food results.
- **total_hits** (int) - Required - The total number of hits.
- **current_page** (int) - Required - The current page number.
- **total_pages** (int) - Required - The total number of pages.
```

--------------------------------

### List foods with pagination

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/quickstart.rst.txt

Lists foods with pagination using page_size and page_number parameters, and shows how to retrieve the next page.

```python
# List foods with pagination
foods = client.list_foods(page_size=10, page_number=1)

# Process foods
for food in foods:
    print(f"{food.description} (FDC ID: {food.fdc_id})")

# Get next page
next_page = client.list_foods(page_size=10, page_number=2)
```

--------------------------------

### Cache food data with background tasks

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/django_integration.html

Shows how to cache large datasets using background tasks with Django Q or other task queues.

```python
from usda_fdc.django import FdcCache

def cache_popular_foods():
    cache = FdcCache()
    popular_ids = [1750340, 1750341, 1750342]  # Example IDs
    cache.get_foods(popular_ids)

# Use with Celery, Django Q, or other task queues
from django_q.tasks import async_task

async_task(cache_popular_foods)

```

--------------------------------

### Run integration-marked tests

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/testing.rst.txt

Runs tests marked with the integration marker. These tests are skipped by default.

```bash
pytest -m integration
```

--------------------------------

### Push commit and tag to GitHub

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/releasing.rst.txt

Push the release commit and tag to GitHub.

```bash
git push origin main
git push origin vX.Y.Z
```

--------------------------------

### list_foods()

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/genindex.html

Lists all available food items.

```APIDOC
## list_foods()

### Description
Lists all available food items.

### Method
GET

### Endpoint
`/foods`

### Parameters
#### Query Parameters
- **page** (integer) - Optional - Page number for pagination.
- **page_size** (integer) - Optional - Number of results per page.

### Response
#### Success Response (200)
- **foods** (array) - List of food items.

#### Response Example
```json
{
  "foods": [
    {
      "id": "12345",
      "description": "Example food"
    }
  ]
}
```
```

--------------------------------

### Add usda_fdc.django to INSTALLED_APPS

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/user/django_integration.html

Adds the usda_fdc.django app to Django's INSTALLED_APPS in settings.py.

```python
INSTALLED_APPS = [
    # ...
    'usda_fdc.django',
    # ...
]

```

--------------------------------

### fdc search command with options

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/user/cli.rst.txt

Searches for foods using keywords, with options for data type, page size, and page number.

```bash
fdc search "apple" --page-size 10 --page-number 1
```

```bash
--data-type TYPE    Filter by data type (can be specified multiple times)
--page-size SIZE    Results per page (default: 10)
--page-number NUM   Page number (default: 1)
```

--------------------------------

### Run code style tools manually

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/dev/contributing.html

Runs Black, isort, flake8, and mypy manually on the source and test directories.

```bash
# Format code
black usda_fdc tests

# Sort imports
isort usda_fdc tests

# Lint code
flake8 usda_fdc tests

# Type check
mypy usda_fdc

```

--------------------------------

### Run tests with pytest

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/dev/testing.html

Runs the test suite for the USDA FDC Python Client using pytest.

```bash
pytest

```

--------------------------------

### Run tests with coverage

Source: https://usda-fdc.readthedocs.io/en/v0.1.1/_sources/dev/testing.rst.txt

Runs tests with coverage for the usda_fdc package.

```bash
pytest --cov=usda_fdc
```