### Basic EarthDaily v1 Client Setup

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

A complete example demonstrating the basic setup of the EarthDaily v1 client, including loading environment variables for authentication and initializing the `EDSClient`.

```python
from dotenv import load_dotenv
from earthdaily import EDSClient, EDSConfig

load_dotenv(".env")  # Load credentials
client = EDSClient(EDSConfig())
```

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

### Install EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Instructions for installing the EarthDaily Python Client using pip, including basic installation and options for platform API functionality, legacy v0 compatibility, or both.

```bash
pip install earthdaily
```

```bash
pip install earthdaily[platform]
```

```bash
pip install earthdaily[legacy]
```

```bash
pip install earthdaily[platform,legacy]
```

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

### Run EarthDaily Python Client Example

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/examples/GALLERY_HEADER.md

Execute a specific EarthDaily Python client example script from the command line. This command initiates the 'quick_start.py' example, demonstrating basic client usage.

```bash
python quick_start.py
```

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

### Install EarthDaily Python Client Dependencies

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/examples/GALLERY_HEADER.md

Install the required Python packages and optional components for the EarthDaily client using pip. The '[platform,legacy]' extras ensure all necessary functionalities, including backward compatibility, are available.

```bash
pip install earthdaily[platform,legacy]
```

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

### Install EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Provides various installation options for the EarthDaily Python client, including basic, platform-specific, legacy support, and full installations to suit different use cases.

```bash
pip install earthdaily
```

```bash
pip install earthdaily[platform]
```

```bash
pip install earthdaily[legacy]
```

```bash
pip install earthdaily[platform,legacy]
```

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

### Configure EarthDaily Client Authentication Environment Variables

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Example of a `.env` file structure required for authenticating the EarthDaily Python Client, specifying client ID, secret, authentication URL, and API URL.

```bash
# .env file (required)
EDS_CLIENT_ID=your_client_id
EDS_SECRET=your_client_secret
EDS_AUTH_URL=https://your-auth-url.com/oauth/token
EDS_API_URL=https://api.earthdaily.com
```

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

### EarthDaily Client v0 vs v1 Architectural Differences

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

A comparison table outlining the key architectural and functional differences between EarthDaily Python Client v0 (Legacy) and v1 (Current), covering main entry points, configuration, API access, STAC operations, error handling, and installation.

```APIDOC
Aspect: v0 (Legacy) -> v1 (Current)
Main Entry Point: Various modules -> EDSClient
Configuration: Manual setup -> EDSConfig
API Access: Datacube functionality -> Full platform API access
STAC Operations: Read-only via STAC client -> Full CRUD operations
Error Handling: Basic exceptions -> Comprehensive with EDSAPIError
Installation: Single package -> Optional dependencies (platform, legacy)
```

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

### Set EarthDaily Client Environment Variables

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/examples/GALLERY_HEADER.md

Configure necessary environment variables for authentication and API access before running EarthDaily Python client examples. These credentials and API endpoints are crucial for the client to function correctly.

```bash
export EDS_CLIENT_ID="your_client_id"
export EDS_SECRET="your_client_secret"
export EDS_AUTH_URL="your_auth_url"
export EDS_API_URL="https://api.earthdaily.com"
```

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

### Install Project Dependencies with Poetry

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Installs all project dependencies, including optional extras, using Poetry for dependency management.

```bash
poetry install --all-extras
```

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

### Set Up Pre-commit Hooks

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Installs the configured pre-commit hooks to automate code quality checks before commits.

```bash
pre-commit install
```

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

### EarthDaily Python Client v0 to v1 Breaking Changes

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Details the key breaking changes introduced in EarthDaily Python Client v1, specifically regarding client initialization, access patterns for legacy functionality, configuration requirements, and installation dependencies.

```APIDOC
Initialization:
  - Old: EarthDataStore()
  - New: EDSClient(EDSConfig())

Access Pattern (for v0 functionality):
  - Old: eds.method()
  - New: client.legacy.method()

Configuration:
  - Environment variables now required (e.g., via .env file)

Installation:
  - Optional dependencies available: [platform], [legacy]
```

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

### Initialize EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Shows the updated method for initializing the EarthDaily client, moving from direct `EarthDataStore` instantiation in v0 to using `EDSConfig` and `EDSClient` in v1 for unified client management.

```python
# Old way - direct initialization
eds = EarthDataStore()
```

```python
# New way - unified client initialization
config = EDSConfig()
client = EDSClient(config)
```

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

### Create Datacubes with EarthDaily Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Compares the process of creating a datacube in v0 and v1, highlighting the use of `client.legacy.datacube` for v1's backward compatibility while maintaining similar functionality.

```python
# Load geometry and initialize
geometry = datasets.load_pivot()
eds = EarthDataStore()

# Create datacube in one step
s2_datacube = eds.datacube(
    "sentinel-2-l2a",
    assets=["blue", "green", "red", "nir"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native",
    clear_cover=50,
)
```

```python
# Load geometry and initialize client
from earthdaily.legacy.datasets import load_pivot

geometry = load_pivot()
client = EDSClient(EDSConfig())

# Create datacube using legacy functionality in v1
s2_datacube = client.legacy.datacube(
    "sentinel-2-l2a",
    assets=["blue", "green", "red", "nir"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native",
    clear_cover=50,
)
```

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

### Access Legacy Datacube Functionality in EarthDaily Client v1

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Shows how to utilize the legacy datacube functionality, which is accessible through the `client.legacy` interface in EarthDaily Python Client v1. This example demonstrates loading a pivot geometry and querying a datacube for specific assets and datetime ranges.

```python
from earthdaily.legacy.datasets import load_pivot

geometry = load_pivot()
datacube = client.legacy.datacube(
    "sentinel-2-l2a",
    assets=["blue", "green", "red"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native",
)
```

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

### Load Environment Variables for EarthDaily Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Python code snippet demonstrating how to load environment variables from a `.env` file using the `python-dotenv` library, which is required for client authentication.

```python
from dotenv import load_dotenv
load_dotenv(".env")  # Required for authentication
```

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

### Upload Data and Start EarthDaily Bulk Insert Job

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Prepares a JSONL file containing STAC items, uploads it to the bulk insert job, and then initiates the job.

```python
# Prepare STAC items file and upload
items_file = Path("./stac_items.jsonl")  # JSONL format
insert_job.upload(items_file)

# Start the job
insert_job.start()
```

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

### Discover Available Collections (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

A practical example of how to find and list all available STAC collections using the EarthDaily Python client's `pystac_client` module.

```python
# Find available collections
collections = client.platform.pystac_client.get_collections()
print([c.id for c in collections])
```

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

### Download Assets from Search Results (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

An example demonstrating how to iterate through STAC search results and download specific assets (e.g., 'blue', 'green', 'red' bands) for each item to a local path.

```python
# Download assets from search results
for item in items:
    client.platform.stac_item.download_item_assets(
        item,
        assets=["blue", "green", "red"],
        path="./downloads"
    )
```

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

### Migrate EarthDataStore v0 Code to EDSClient v1

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Compares the initialization and search patterns between the deprecated EarthDataStore (v0) and the new EDSClient (v1) for the EarthDaily Python Client. It highlights that v0 methods are now consistently accessible via the `client.legacy` attribute in v1.

```python
# v0 code
eds = EarthDataStore()
items = eds.search("sentinel-2-l2a", intersects=geometry)

# v1 equivalent - same functionality via client.legacy
client = EDSClient(EDSConfig())
items = client.legacy.search("sentinel-2-l2a", intersects=geometry)
```

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

### Upload Item IDs and Start EarthDaily Bulk Delete Job

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Prepares a file containing item IDs to be deleted, uploads it to the bulk delete job, and then starts the deletion process.

```python
# Prepare file with item IDs to delete
ids_file = Path("./items_to_delete.txt")
delete_job.upload(ids_file)

# Start the deletion
delete_job.start()
```

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

### Create STAC Item

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Provides an example of creating a new STAC item using the EarthDaily client's STAC item management functionality. It shows the structure of a basic STAC item dictionary and how to pass it to the `create_item` method.

```python
# Create a new STAC item
stac_item = {
    "type": "Feature",
    "stac_version": "1.0.0",
    "id": "example-item-123",
    "collection": "your-collection",
    "geometry": {"type": "Point", "coordinates": [-67.7, -37.8]},
    "properties": {"datetime": "2024-01-01T00:00:00Z"},
    "links": [],
    "assets": {}
}

client.platform.stac_item.create_item("your-collection", stac_item)
```

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

### Update EarthDaily Python Client Imports

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Demonstrates the change in import statements from the v0 client to the new v1 client, including `EDSClient`, `EDSConfig`, and `EDSAPIError` for enhanced error handling.

```python
# Old v0 imports
import earthdaily
from earthdaily import EarthDataStore, datasets
```

```python
# New v1 imports
from earthdaily import EDSClient, EDSConfig
from earthdaily.exceptions import EDSAPIError
```

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

### Search for STAC Items with EarthDaily Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Illustrates the different approaches to searching for STAC items in v0, v1 (using the new Platform API), and v1 (using legacy functionality for backward compatibility).

```python
items = eds.search(
    "sentinel-2-l2a",
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
)
```

```python
search_result = client.platform.pystac_client.search(
    collections=["sentinel-2-l2a"],
    datetime="2022-08-01T00:00:00Z/2022-08-09T00:00:00Z",
    max_items=50,
)
items = list(search_result.items())
```

```python
items = client.legacy.search(
    "sentinel-2-l2a",
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
)
```

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

### Initialize DataTables for Computation Times Table

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/sg_execution_times.rst

This JavaScript snippet initializes the DataTables library on an HTML table identified by the class 'sg-datatable'. It configures the table to be sortable, with a default descending order applied to the second column (Time), thereby enhancing the user experience for viewing computation times.

```JavaScript
$(document).ready( function () {
    $('table.sg-datatable').DataTable({order: [[1, 'desc']]});
} );
```

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

### Create a STAC Item using EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Demonstrates how to construct a STAC item dictionary with essential metadata and then use the client's platform API to create this item within a specified collection. This involves defining the item's type, version, ID, collection, geometry, properties, links, and assets.

```python
stac_item = {
    "type": "Feature",
    "stac_version": "1.0.0",
    "id": "example-item-123",
    "collection": "eda-labels-vessels",
    "geometry": {"type": "Point", "coordinates": [-67.7, -37.8]},
    "properties": {"datetime": "2017-12-08T14:38:16.000000Z"},
    "links": [],
    "assets": {},
}

client.platform.stac_item.create_item("eda-labels-vessels", stac_item)
```

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

### Search STAC Items with EarthDaily Platform API

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/migration-v0-to-v1.md

Illustrates how to perform a search for STAC items using the client's platform pystac_client interface. It shows how to filter results by specifying collections, a datetime range, and limiting the maximum number of items returned.

```python
search_result = client.platform.pystac_client.search(
    collections=["sentinel-2-l2a"],
    datetime="2024-06-01T00:00:00Z/2024-08-01T00:00:00Z",
    max_items=10,
)
items = list(search_result.items())
```

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

### Search Satellite Data with STAC

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Illustrates how to search for satellite data, specifically Sentinel-2 L2A imagery, using the STAC client within the EarthDaily platform API. The example specifies collections, a datetime range, and a maximum number of items to retrieve.

```python
# Search for Sentinel-2 data
search_result = client.platform.pystac_client.search(
    collections=["sentinel-2-l2a"],
    datetime="2024-06-01T00:00:00Z/2024-08-01T00:00:00Z",
    max_items=10
)
items = list(search_result.items())
```

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

### Initialize EarthDaily Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Demonstrates how to initialize the EarthDaily client using `EDSConfig`. This can be done by loading credentials from a '.env' file using `dotenv` or by providing the client ID, secret, and API URLs directly to the `EDSConfig` constructor.

```python
from dotenv import load_dotenv
from earthdaily import EDSClient, EDSConfig

# Load environment variables
load_dotenv(".env")

# Initialize client
config = EDSConfig()
client = EDSClient(config)
```

```python
# Direct configuration (without .env file)
config = EDSConfig(
    client_id="your_client_id",
    client_secret="your_client_secret",
    token_url="https://your-auth-url.com/oauth/token",
    api_url="https://api.earthdaily.com"
)
client = EDSClient(config)
```

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

### Build Python Package Distributions

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Builds the wheel and source distributions of the Python package, placing them in the `dist/` directory.

```bash
poetry build
```

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

### Create Analysis-Ready Datacube (EarthDaily Legacy)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Demonstrates how to create an analysis-ready datacube using the legacy interface. It specifies collections, assets, geometry, datetime, and applies cloud masking and clear pixel filtering, with an option to aggregate by date.

```python
from earthdaily.legacy.datasets import load_pivot

# Load sample geometry
geometry = load_pivot()

# Create analysis-ready datacube
datacube = client.legacy.datacube(
    collections="sentinel-2-l2a",
    assets=["blue", "green", "red", "nir"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native",  # Apply cloud masking
    clear_cover=50,      # Minimum 50% clear pixels
    groupby_date="mean"  # Aggregate by date
)
```

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

### EarthDaily Client Architecture Overview

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Outlines the main modules and their functionalities within the EarthDaily Python client. It distinguishes between the modern `client.platform` for new API access and `client.legacy` for backward compatibility with v0 features.

```APIDOC
client.platform: Modern platform API access
  pystac_client: STAC catalog search
  stac_item: STAC item CRUD operations
  bulk_search: Bulk search operations
  bulk_insert: Bulk data insertion
  bulk_delete: Bulk data deletion

client.legacy: v0 compatibility layer
  datacube(): Create analysis-ready datacubes
  search(): Legacy search functionality
  Access to existing v0 methods
```

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

### Run All Project Tests Locally with Tox

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Executes all configured tests across multiple Python environments using Tox via Poetry.

```bash
poetry run tox
```

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

### Clone EarthDaily Python Client Repository

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Clones the EarthDaily Python Client repository from GitHub and navigates into the project directory.

```bash
git clone git@github.com:earthdaily/earthdaily-python-client.git
cd earthdaily-python-client
```

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

### Configure EarthDaily Client Environment Variables

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Shows how to set up environment variables for EarthDaily client credentials and API URLs by creating a '.env' file in your project root. These variables are crucial for authentication and connecting to the EarthDaily platform.

```bash
# .env
EDS_CLIENT_ID=your_client_id
EDS_SECRET=your_client_secret
EDS_AUTH_URL=https://your-auth-url.com/oauth/token
EDS_API_URL=https://api.earthdaily.com
```

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

### Access Legacy Datacube Functionality

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Demonstrates how to use the legacy v0 datacube functionality through the EarthDaily client. It shows loading a pivot geometry and creating an analysis-ready datacube with specified assets, intersection geometry, and datetime range.

```python
from earthdaily.legacy.datasets import load_pivot

# Load geometry and create datacube
geometry = load_pivot()
datacube = client.legacy.datacube(
    "sentinel-2-l2a",
    assets=["blue", "green", "red", "nir"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native"
)
```

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

### Create Multi-Collection Datacube (EarthDaily Legacy)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Illustrates creating a datacube from multiple STAC collections, specifying common assets, intersecting geometry, and datetime. It also includes an option for cross-calibration between collections.

```python
# Create datacube from multiple collections
datacube = client.legacy.datacube(
    collections=["sentinel-2-l2a", "landsat-c2l2-sr"],
    assets=["red", "green", "blue"],
    intersects=geometry,
    datetime="2022-08",
    cross_calibration_collection="landsat-c2l2-sr"
)
```

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

### Jinja2 Template for Python Class API Documentation

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/templates/class.rst

This template defines the structure for automatically generating API documentation for a Python class using Sphinx. It includes directives to display class details, inherited members, special methods, and dynamically lists public methods and attributes using `autosummary`.

```APIDOC
{{ fullname | escape | underline}}

.. currentmodule:: {{ module }}

.. autoclass:: {{ objname }}
   :members:
   :show-inheritance:
   :inherited-members:
   :special-members: __call__, __add__, __mul__

   {% block methods %}
   {% if methods %}
   .. rubric:: {{ _('Methods') }}

   .. autosummary::
      :nosignatures:
   {% for item in methods %}
      {%- if not item.startswith('_') %}
      ~{{ name }}.{{ item }}
      {%- endif -%}
   {%- endfor %}
   {% endif %}
   {% endblock %}

   {% block attributes %}
   {% if attributes %}
   .. rubric:: {{ _('Attributes') }}

   .. autosummary::
   {% for item in attributes %}
      ~{{ name }}.{{ item }}
   {%- endfor %}
   {% endif %}
   {% endblock %}
```

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

### Push Local Branch to Origin

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Pushes the current feature branch to the remote origin repository.

```bash
git push origin feature/your-feature-name
```

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

### Run Specific Tox Test Environments

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Executes specific test environments like linting, formatting checks, or type checking using Tox.

```bash
poetry run tox -e lint     # Run linting
poetry run tox -e format   # Check formatting
poetry run tox -e mypy     # Run type checking
```

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

### Create Bulk STAC Item Insert Job (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Sets up a bulk insert job for STAC items, defining error handling ('CONTINUE' or 'STOP') and conflict resolution modes ('SKIP' or 'OVERRIDE').

```python
# Create bulk insert job
insert_job = client.platform.bulk_insert.create(
    collection_id="your-collection",
    error_handling_mode="CONTINUE",  # or "STOP"
    conflict_resolution_mode="SKIP"  # or "OVERRIDE"
)
```

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

### Jinja2 Template for Project Version Display

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/templates/versions.html

This Jinja2 template snippet is responsible for rendering a list of available project versions. It checks for a `current_version` and then iterates through `versions.tags` and `versions.branches` to create hyperlinked lists. This is typically used in documentation portals or release pages to navigate between different software versions.

```Jinja2
{%- if current_version %}\n\nOther Versions v: {{ current_version.name }}\n\n{%- if versions.tags %}\n\nTags\n\n{%- for item in versions.tags %}\n\n[{{ item.name }}]({{ item.url }})\n\n{%- endfor %}\n\n{%- endif %} {%- if versions.branches %}\n\nBranches\n\n{%- for item in versions.branches %}\n\n[{{ item.name }}]({{ item.url }})\n\n{%- endfor %}\n\n{%- endif %}\n\n{%- endif %}
```

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

### Download STAC Item Assets with EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Shows how to download specific assets (e.g., 'blue', 'green', 'red' bands) from a STAC item to a local directory, with an option to limit concurrent downloads.

```python
# Download item assets
downloads = client.platform.stac_item.download_assets(
    item=item,
    asset_keys=["blue", "green", "red"],
    output_dir="./downloads",
    max_workers=3
)
```

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

### Jinja2 Template for Sphinx Automodule Documentation

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/templates/custom.rst

This template defines the layout for Sphinx documentation pages, utilizing Jinja2 control flow (if, for blocks) to conditionally include `automodule`, `autosummary`, and `rubric` directives. It's intended to be used by Sphinx's autodoc extension to generate API reference documentation for Python projects, dynamically populating sections for functions, classes, and exceptions based on the module's contents.

```Jinja2
Project: /earthdaily/earthdaily-python-client
Content:
{{ objname }}
{{ underline }}

.. automodule:: {{ fullname }}

   {% block functions %}
   {% if functions %}
   .. rubric:: Functions prout

   .. autosummary::
      :toctree: {{ objname }}
      :template: function.rst
   {% for item in functions %}
      {{ item }}
   {%- endfor %}
   {% endif %}
   {% endblock %}

   {% block classes %}
   {% if classes %}
   .. rubric:: Classes

   .. autosummary::
      :toctree: {{ objname }}
      :template: class.rst
   {% for item in classes %}
      {{ item }}
   {%- endfor %}
   {% endif %}
   {% endblock %}

   {% block exceptions %}
   {% if exceptions %}
   .. rubric:: Exceptions

   .. autosummary::
   {% for item in exceptions %}
      {{ item }}
   {%- endfor %}
   {% endif %}
   {% endblock %}
```

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

### Run Tests for Specific Python Versions

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Executes project tests using Tox for a particular Python version, such as 3.10, 3.11, or 3.12.

```bash
poetry run tox -e py310  # for Python 3.10
poetry run tox -e py311  # for Python 3.11
poetry run tox -e py312  # for Python 3.12
```

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

### Handle API Errors (EarthDaily Python Client)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Shows how to implement basic error handling for API calls using a try-except block to catch `EDSAPIError` specifically, providing a robust way to manage potential issues.

```python
from earthdaily.exceptions import EDSAPIError

try:
    search_result = client.platform.pystac_client.search(
        collections=["invalid-collection"]
    )
except EDSAPIError as e:
    print(f"API Error: {e}")
```

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

### Create STAC Item via Platform API

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Shows how to create a STAC item using the `create_item` method of `client.platform.stac_item`. This method allows specifying the collection ID, the item's data, and the desired return format (dictionary, JSON, or pystac object).

```python
# Create a new STAC item
item = client.platform.stac_item.create_item(
    collection_id="your-collection",
    item_data={
        "type": "Feature",
        "stac_version": "1.0.0",
        "id": "item-123",
        "geometry": {"type": "Point", "coordinates": [-67.7, -37.8]},
        "properties": {"datetime": "2024-01-01T00:00:00Z"}
    },
    return_format="dict"  # "dict", "json", or "pystac"
)
```

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

### Create Bulk STAC Search Job (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Initiates a bulk search job for STAC items across specified collections, datetime ranges, and bounding boxes. It also allows setting a limit on results and an export format, then prints the job ID.

```python
# Create a bulk search job
search_job = client.platform.bulk_search.create(
    collections=["sentinel-2-l2a"],
    datetime="2024-01-01T00:00:00Z/2024-02-01T00:00:00Z",
    bbox=[-74.2, 40.6, -73.9, 40.9],  # NYC area
    limit=1000,
    export_format="json"
)
print(f"Job ID: {search_job.job_id}")
```

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

### Create New Feature or Bugfix Branch

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Creates and switches to a new Git branch for developing a feature or bugfix.

```bash
git checkout -b feature/your-feature-name
```

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

### Jinja2 Template for Sphinx Python Class API Doc Generation

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/docs/templates/custom-class-template.rst

This template provides the core structure for generating API documentation for Python classes in Sphinx. It uses Jinja2 logic to conditionally include sections for methods and attributes, applying Sphinx directives like `autoclass` for overall class documentation and `autosummary` for concise listings of methods and attributes, filtering out private members.

```Jinja2
{{ fullname | escape | underline}}

.. currentmodule:: {{ module }}

.. autoclass:: {{ objname }}
   :members:
   :show-inheritance:
   :inherited-members:
   :special-members: __call__, __add__, __mul__

   {% block methods %}
   {% if methods %}
   .. rubric:: {{ _('Methods') }}

   .. autosummary::
      :nosignatures:
   {% for item in methods %}
      {%- if not item.startswith('_') %}
      ~{{ name }}.{{ item }}
      {%- endif -%}
   {%- endfor %}
   {% endif %}
   {% endblock %}

   {% block attributes %}
   {% if attributes %}
   .. rubric:: {{ _('Attributes') }}

   .. autosummary::
   {% for item in attributes %}
      ~{{ name }}.{{ item }}
   {%- endfor %}
   {% endif %}
   {% endblock %}
```

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

### Commit Code Changes to Git

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/CONTRIBUTING.md

Stages all modified files and commits them to the current Git branch with a specified message.

```bash
git add .
git commit -m "your commit message"
```

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

### List Available STAC Collections (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Retrieves and prints the IDs of all available STAC collections from the EarthDaily platform.

```python
# List available collections
collections = client.platform.pystac_client.get_collections()
for collection in collections:
    print(f"Collection: {collection.id}")
```

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

### Create Bulk STAC Item Delete Job (EarthDaily Python)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Initializes a bulk delete job for items within a specified collection.

```python
# Create bulk delete job
delete_job = client.platform.bulk_delete.create(
    collection_id="your-collection"
)
```

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

### Monitor EarthDaily Bulk Insert Job Progress

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Fetches and displays the current progress of a bulk insert job, including the count of items successfully written and the count of items with errors.

```python
# Check insert job status
job_status = client.platform.bulk_insert.fetch(insert_job.job_id)
print(f"Items written: {job_status.items_written_count}")
print(f"Errors: {job_status.items_error_count}")
```

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

### Perform Standard STAC Search with EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Executes a standard STAC API search for items based on collections, datetime, bounding box, and maximum item limits. It then processes and prints the number of found items.

```python
# Search for items using STAC API
search_results = client.platform.pystac_client.search(
    collections=["sentinel-2-l2a"],
    datetime="2024-01-01T00:00:00Z/2024-02-01T00:00:00Z",
    bbox=[-74.2, 40.6, -73.9, 40.9],
    max_items=50
)

# Process results
items = list(search_results.items())
print(f"Found {len(items)} items")
```

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

### Download EarthDaily Bulk Search Results

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Downloads the results of a completed bulk search job to a specified local directory. This operation is conditional on the job status being 'COMPLETED'.

```python
# Download search results when completed
if job_status.status == "COMPLETED":
    job_status.download_assets(save_location=Path("./bulk_results"))
```

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

### Monitor EarthDaily Bulk Delete Job Progress

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Fetches and displays the current progress of a bulk delete job, including the count of items successfully deleted and the count of items with errors.

```python
# Check delete job status
job_status = client.platform.bulk_delete.fetch(delete_job.job_id)
print(f"Items deleted: {job_status.items_deleted_count}")
print(f"Errors: {job_status.items_error_count}")
```

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

### Read STAC Item via Platform API

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Demonstrates how to retrieve a specific STAC item using the `get_item` method of `client.platform.stac_item`. You need to provide the collection ID, the item ID, and can specify the desired return format for the item.

```python
# Get a specific item
item = client.platform.stac_item.get_item(
    collection_id="your-collection",
    item_id="item-123",
    return_format="pystac"
)
```

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

### Monitor EarthDaily Bulk Search Job Status

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Fetches and displays the current status and asset count of a previously created bulk search job using its job ID.

```python
# Check job status
job_status = client.platform.bulk_search.fetch(search_job.job_id)
print(f"Status: {job_status.status}")
print(f"Assets: {len(job_status.assets)}")
```

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

### Search STAC Items (EarthDaily Legacy Interface)

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Performs a STAC item search using the legacy client interface, filtering by collections, intersecting geometry, datetime range, and a maximum limit.

```python
# Search for items (legacy interface)
items = client.legacy.search(
    collections="sentinel-2-l2a",
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    limit=100
)
print(f"Found {len(items)} items")
```

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

### Update STAC Item via Platform API

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Illustrates how to update an existing STAC item using the `update_item` method of `client.platform.stac_item`. This method requires the collection ID, item ID, and a dictionary containing the data to be updated within the item's properties.

```python
# Update an existing item
updated_item = client.platform.stac_item.update_item(
    collection_id="your-collection",
    item_id="item-123",
    item_data={"properties": {"updated": "2024-01-02T00:00:00Z"}},
    return_format="dict"
)
```

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

### Delete STAC Item using EarthDaily Python Client

Source: https://github.com/earthdaily/earthdaily-python-client/blob/main/README.md

Demonstrates how to delete a specific STAC item from a collection using its collection ID and item ID.

```python
client.platform.stac_item.delete_item(
    collection_id="your-collection",
    item_id="item-123"
)
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.