### Testing Setup and Examples

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Provides setup instructions and example tests for the xpublish-edr API using pytest and TestClient.

```APIDOC
## Testing Setup and Examples

### Description
This section outlines how to set up a testing environment for xpublish-edr and includes example tests for querying data and verifying metadata.

### Setup
To run these tests, you need `pytest`, `xpublish`, `fastapi.testclient`, `xpublish_edr`, and `cf_xarray` installed.

### Fixture
- **test_client**: A pytest fixture that creates an xpublish REST instance with the CfEdrPlugin enabled and returns a TestClient for making requests.

### Example Tests

#### `test_position_query`
- **Purpose:** Tests the `/datasets/air/edr/position` endpoint with basic query parameters and checks for expected content in the response.
- **Request:** `GET /datasets/air/edr/position?coords=POINT(204 44)&f=csv`
- **Assertions:** Status code is 200, response text contains 'air' and 'lat,lon'.

#### `test_metadata`
- **Purpose:** Tests the root dataset endpoint (`/datasets/air/edr/`) to verify metadata retrieval, including available data queries.
- **Request:** `GET /datasets/air/edr/`
- **Assertions:** Status code is 200, response is JSON, contains 'id' equal to 'air', and 'position', 'area', 'cube' in 'data_queries'.

### Test Code Example
```python
import pytest
import xpublish
from fastapi.testclient import TestClient
from xpublish_edr import CfEdrPlugin
from cf_xarray.datasets import airds

@pytest.fixture
def test_client():
    # Create xpublish instance with EDR plugin
    rest = xpublish.Rest(
        {"air": airds},
        plugins={"edr": CfEdrPlugin()}
    )
    return TestClient(rest.app)

def test_position_query(test_client):
    response = test_client.get(
        "/datasets/air/edr/position?coords=POINT(204 44)&f=csv"
    )
    assert response.status_code == 200
    assert "air" in response.text
    assert "lat,lon" in response.text

def test_metadata(test_client):
    response = test_client.get("/datasets/air/edr/")
    assert response.status_code == 200
    data = response.json()
    assert data["id"] == "air"
    assert "position" in data["data_queries"]
    assert "area" in data["data_queries"]
    assert "cube" in data["data_queries"]
```
```

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

### Local Development Environment Setup (Bash/Conda)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

This command demonstrates how to set up a local development environment for the xpublish-edr project using Conda. It mirrors the environment creation process used in the CI, ensuring consistency. This requires Conda to be installed on the local machine.

```bash
conda create --name TEST python=3.8 --file requirements.txt --file requirements-dev.txt
```

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

### Travis CI Configuration for xpublish-edr (YAML)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

This YAML configuration defines the continuous integration pipeline for the xpublish-edr project using Travis CI. It includes environment setup, matrix builds for various Python versions and testing types (coding standards, tarball, docs), pre-installation steps using Conda, standard installation, and script execution for tests, packaging, and documentation deployment. Dependencies include Miniconda, pytest, check-manifest, twine, and doctr.

```yaml
language: minimal

sudo: false

env:
  global:
    - secure: "TOKEN"

matrix:
  fast_finish: true
  include:
    - name: "python-3.6"
      env: PY=3.6
    - name: "python-3.8"
      env: PY=3.8
    - name: "coding_standards"
      env: PY=3
    - name: "tarball"
      env: PY=3
    - name: "docs"
      env: PY=3

before_install:
  # Install miniconda and create TEST env.
  - |
    wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
    bash miniconda.sh -b -p $HOME/miniconda
    export PATH="$HOME/miniconda/bin:$PATH"
    conda config --set always_yes yes --set changeps1 no --set show_channel_urls true
    conda update --quiet conda
    conda config --add channels conda-forge --force
    conda config --set channel_priority strict
    conda create --name TEST python=$PY --file requirements.txt --file requirements-dev.txt
    source activate TEST
    conda info --all

install:
  - pip install -e . --no-deps --force-reinstall

script:
  - if [[ $TRAVIS_JOB_NAME == python-* ]]; then
      cp -r tests/ /tmp ;
      pushd /tmp && pytest -n 2 -rxs --cov=xpublish_edr tests && popd ;
    fi

  - if [[ $TRAVIS_JOB_NAME == 'tarball' ]]; then
      pip wheel . -w dist --no-deps ;
      check-manifest --verbose ;
      twine check dist/* ;
    fi

  - if [[ $TRAVIS_JOB_NAME == 'coding_standards' ]]; then
      pytest --flake8 -m flake8 ;
    fi

  - |
    if [[ $TRAVIS_JOB_NAME == 'docs' ]]; then
      set -e
      cp notebooks/tutorial.ipynb docs/source/
      pushd docs
      make clean html linkcheck
      popd
      if [[ -z "$TRAVIS_TAG" ]]; then
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html dev
      else
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html "version-$TRAVIS_TAG"
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html .
      fi
    fi

```

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

### Install and Run Pre-commit Hooks (CLI)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

Commands to install pre-commit hooks locally, run all hooks on all files in the project, and bypass pre-commit checks during a git commit. These are essential for setting up and utilizing pre-commit in a development workflow.

```default
pre-commit install

pre-commit run --all-files

git commit xpublish_edr/some-dot-pwhy.py --no-verify
```

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

### Package and Build Configuration with setup.cfg

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

The setup.cfg file configures package metadata, installation options, and tool-specific settings for building and checking the Python package. It specifies package name, description, author details, classifiers, dependencies, and exclusion patterns for source distributions.

```cfg
[metadata]
name = xpublish_edr
description = My Awesome module
author = AUTHOR NAME
author_email = AUTHOR@EMAIL.COM
url = https://github.com/ioos/ioos-python-package-skeleton
long_description = file: README.md
long_description_content_type = text/markdown
license = BSD-3-Clause
license_file = LICENSE.txt
classifiers =
    Development Status :: 5 - Production/Stable
    Intended Audience :: Science/Research
    Operating System :: OS Independent
    License :: OSI Approved :: BSD License
    Programming Language :: Python
    Programming Language :: Python :: 3
    Programming Language :: Python :: 3.6
    Programming Language :: Python :: 3.7
    Programming Language :: Python :: 3.8
    Topic :: Scientific/Engineering

[options]
zip_safe = False
install_requires =
    numpy
    requests
python_requires = >=3.6
packages = find:

[sdist]
formats = gztar

[check-manifest]
ignore =
    *.yml
    *.yaml
    .coveragerc
    docs
    docs/*
    *.enc
    notebooks
    notebooks/*
    tests
    tests/*

[flake8]
max-line-length = 105
select = C,E,F,W,B,B950
ignore = E203, E501, W503
exclude = xpublish_edr/_version.py
```

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

### LICENSE File Content Example (Text)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Provides a standard BSD-style license text for software distribution. It outlines the terms under which the software can be used, modified, and redistributed, including disclaimers of warranty.

```text
Copyright 2017 AUTHOR NAME


Redistribution and use in source and binary forms,
with or without modification,
are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice,
   this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors
   may be used to endorse or promote products derived from this software
   without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY
WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

```

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

### Travis CI Installation Steps (YAML)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Configures the `before_install` section of a Travis CI build. This involves downloading and setting up Miniconda, creating a specific Conda environment (TEST) with specified Python version and dependencies from `requirements.txt` and `requirements-dev.txt`, and activating the environment.

```yaml
before_install:
  # Install miniconda and create TEST env.
  - |
    wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
    bash miniconda.sh -b -p $HOME/miniconda
    export PATH="$HOME/miniconda/bin:$PATH"
    conda config --set always_yes yes --set changeps1 no --set show_channel_urls true
    conda update --quiet conda
    conda config --add channels conda-forge --force
    conda config --set channel_priority strict
    conda create --name TEST python=$PY --file requirements.txt --file requirements-dev.txt
    source activate TEST
    conda info --all

install:
  - pip install -e . --no-deps --force-reinstall


```

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

### Project Dependencies Example (Text)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

A sample `requirements.txt` file listing project dependencies. It includes version specifiers and conditional dependencies based on Python version. Comments indicate potential conda-specific dependencies.

```text
OWSLib>=0.8.3
Jinja2>=2.7.3
functools32==3.2.3-2; python_version < '3.2'
#conda: libnetcdf
#conda: libgdal

```

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

### Project Structure Example

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Illustrates a typical directory structure for a Python package, including directories for documentation, tests, and the package source code itself. It highlights the common practice of placing tests outside the main module directory.

```tree
|-docs
| |-source
| | |-_static
| |-build
|-tests
|-ioos_pkg_skeleton
```

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

### Error Handling Examples

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Demonstrates how to handle common API errors such as invalid coordinates, incorrect parameter names, and unsupported data formats.

```APIDOC
## Error Handling Examples

### Description
This section provides examples of how to catch and interpret common error responses from the API when making requests with invalid parameters or formats.

### Method
GET

### Endpoint
`/datasets/{dataset_id}/edr/position` (examples use `/datasets/air/edr/position`)

### Error Scenarios

#### Invalid WKT coordinates
- **Status Code:** 422
- **Response Body:** `{"detail": "Could not parse coordinates to geometry, check the format of the 'coords' query parameter"}`
- **Request Example:**
  ```python
  import requests

  base_url = "http://localhost:9000"
  response = requests.get(
      f"{base_url}/datasets/air/edr/position",
      params={"coords": "(71, 41)"}  # Invalid WKT
  )
  if response.status_code == 422:
      print(f"Invalid geometry: {response.json()['detail']}")
  ```

#### Invalid parameter name
- **Status Code:** 404
- **Response Body:** `{"detail": "Error selecting from query: Invalid variable: 'temperature'"}`
- **Request Example:**
  ```python
  import requests

  base_url = "http://localhost:9000"
  response = requests.get(
      f"{base_url}/datasets/air/edr/position",
      params={"coords": "POINT(204 44)", "parameter-name": "temperature"}
  )
  if response.status_code == 404:
      print(f"Error: {response.json()['detail']}")
  ```

#### Invalid format
- **Status Code:** 404
- **Response Body:** `{"detail": "invalid_format is not a valid format for EDR position queries. Get `./position/formats` for valid formats"}`
- **Request Example:**
  ```python
  import requests

  base_url = "http://localhost:9000"
  response = requests.get(
      f"{base_url}/datasets/air/edr/position",
      params={"coords": "POINT(204 44)", "f": "invalid_format"}
  )
  if response.status_code == 404:
      print(f"Format error: {response.json()['detail']}")
  ```
```

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

### Calculate Meaning of Life with ioos_pkg_skeleton

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/tutorial.ipynb

This Python code snippet demonstrates how to use the `meaning_of_life` function from the `ioos_pkg_skeleton` library to calculate a result based on an input integer. It imports the necessary library and calls the function.

```python
import ioos_pkg_skeleton


ioos_pkg_skeleton.meaning_of_life(3)
```

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

### GET /edr/position/formats

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Retrieve a list of supported output formats for position queries. This endpoint helps users identify available data export formats.

```APIDOC
## GET /edr/position/formats

### Description
Retrieve list of supported output formats for position queries.

### Method
GET

### Endpoint
`/edr/position/formats`

### Response
#### Success Response (200)
- **cf_covjson** (string) - Description for CoverageJSON format.
- **csv** (string) - Description for CSV format.
- **geojson** (string) - Description for GeoJSON format.
- **nc** (string) - Description for NetCDF format.
- **parquet** (string) - Description for Parquet format.

#### Response Example
```json
{
  "cf_covjson": "Transform an xarray dataset to CoverageJSON using CF conventions",
  "csv": "Convert xarray Dataset to CSV format",
  "geojson": "Transform vectorized xarray dataset to GeoJSON",
  "nc": "Export xarray Dataset as NetCDF file",
  "parquet": "Convert xarray Dataset to Parquet format"
}
```
```

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

### Get Supported Output Formats (bash)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Retrieve a list of supported output formats for position queries via a curl command. The response is a JSON object mapping format names to their descriptions.

```bash
curl http://localhost:9000/edr/position/formats

# Response:
{
  "cf_covjson": "Transform an xarray dataset to CoverageJSON using CF conventions",
  "csv": "Convert xarray Dataset to CSV format",
  "geojson": "Transform vectorized xarray dataset to GeoJSON",
  "nc": "Export xarray Dataset as NetCDF file",
  "parquet": "Convert xarray Dataset to Parquet format"
}
```

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

### Retrieve Meaning of Life Information via URL with ioos_pkg_skeleton

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/tutorial.ipynb

This Python code snippet shows how to retrieve information related to the 'meaning of life' using the `meaning_of_life_url` function from the `ioos_pkg_skeleton` library. It involves importing the library and calling the function, which returns a descriptive string.

```python
import ioos_pkg_skeleton


ioos_pkg_skeleton.meaning_of_life_url()
```

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

### GET /datasets/ensemble/edr/position

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Retrieves data subsets from ensemble datasets based on specified coordinates, datetime, band, and ensemble member range.

```APIDOC
## GET /datasets/ensemble/edr/position

### Description
This endpoint allows users to select specific data based on spatial coordinates, time, a particular band, and a range of ensemble members. It's useful for analyzing specific slices of ensemble forecast data.

### Method
GET

### Endpoint
`/datasets/ensemble/edr/position`

### Parameters
#### Query Parameters
- **coords** (string) - Required - The geographic coordinates in WKT format (e.g., `POINT(-120 40)`).
- **datetime** (string) - Required - The specific date and time for the data query (e.g., `2023-01-01`).
- **band** (string) - Required - The identifier for the specific band of data to retrieve (e.g., `3`).
- **member** (string) - Required - The range of ensemble members to include (e.g., `5/10`).
- **f** (string) - Optional - The desired output format for the data (e.g., `nc` for NetCDF).

### Request Example
```python
import requests

response = requests.get(
    "http://localhost:9000/datasets/ensemble/edr/position",
    params={
        "coords": "POINT(-120 40)",
        "datetime": "2023-01-01",
        "band": "3",
        "member": "5/10",
        "f": "nc"
    }
)
```

### Response
#### Success Response (200)
- Returns NetCDF data for the specified band and ensemble members.
```

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

### Setup Test Client with xpublish and CfEdrPlugin

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

This snippet shows how to set up a testing environment for xpublish-edr using pytest and FastAPI's TestClient. It initializes an xpublish Rest instance with the CfEdrPlugin and sample data, then defines two test functions to verify position queries and metadata retrieval via the API. Dependencies include 'pytest', 'xpublish', 'fastapi.testclient', 'xpublish_edr', and 'cf_xarray.datasets'.

```python
import pytest
import xpublish
from fastapi.testclient import TestClient
from xpublish_edr import CfEdrPlugin
from cf_xarray.datasets import airds

@pytest.fixture
def test_client():
    # Create xpublish instance with EDR plugin
    rest = xpublish.Rest(
        {"air": airds},
        plugins={"edr": CfEdrPlugin()}
    )
    return TestClient(rest.app)

def test_position_query(test_client):
    response = test_client.get(
        "/datasets/air/edr/position?coords=POINT(204 44)&f=csv"
    )
    assert response.status_code == 200
    assert "air" in response.text
    assert "lat,lon" in response.text

def test_metadata(test_client):
    response = test_client.get("/datasets/air/edr/")
    assert response.status_code == 200
    data = response.json()
    assert data["id"] == "air"
    assert "position" in data["data_queries"]
    assert "area" in data["data_queries"]
    assert "cube" in data["data_queries"]
```

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

### Position Query - Multiple Points (bash)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Query data at multiple geographic locations simultaneously using a curl command. This example retrieves data at multiple points in CSV format for the 'air' parameter.

```bash
# Get data at multiple points in CSV format
curl "http://localhost:9000/datasets/air/edr/position?coords=MULTIPOINT((202%2043),(205%2045))&f=csv&parameter-name=air"

# Response (CSV):
time,lat,lon,air
2013-01-01T00:00:00,43.0,202.0,241.2
2013-01-01T06:00:00,43.0,202.0,242.5
2013-01-01T00:00:00,45.0,205.0,243.1
2013-01-01T06:00:00,45.0,205.0,244.0
```

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

### GET /datasets/{dataset_id}/edr/

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Retrieve OGC EDR collection metadata for a specific dataset. This includes spatial and temporal extents, available parameters, and query capabilities.

```APIDOC
## GET /datasets/{dataset_id}/edr/

### Description
Retrieve OGC EDR collection metadata for a specific dataset including extents, parameters, and query capabilities.

### Method
GET

### Endpoint
`/datasets/{dataset_id}/edr/`

### Parameters
#### Path Parameters
- **dataset_id** (string) - Required - The identifier of the dataset to retrieve metadata for.

### Response
#### Success Response (200)
- **id** (string) - The unique identifier of the dataset.
- **title** (string) - The title of the dataset.
- **description** (string) - A detailed description of the dataset.
- **extent** (object) - Spatial and temporal extents of the dataset.
  - **spatial** (object)
    - **bbox** (array) - Bounding box coordinates [[min_lon, min_lat, max_lon, max_lat]].
    - **crs** (string) - Coordinate reference system identifier.
  - **temporal** (object)
    - **interval** (array) - Temporal interval [start_time, end_time].
    - **values** (array) - List of available temporal values or ranges.
- **crs** (array) - List of supported Coordinate Reference Systems.
- **output_formats** (array) - List of supported output formats.
- **data_queries** (object) - Available data query types (position, area, cube).
- **parameter_names** (array) - List of parameter names available in the dataset.

#### Response Example
```json
{
  "id": "air",
  "title": "4x daily NMC reanalysis (1948)",
  "description": "Data is from NMC initialized reanalysis\n(4x/day)...",
  "extent": {
    "spatial": {
      "bbox": [[200.0, 15.0, 322.5, 75.0]],
      "crs": "EPSG:4326"
    },
    "temporal": {
      "interval": ["2013-01-01T00:00:00", "2013-01-01T18:00:00"],
      "values": ["2013-01-01T00:00:00/2013-01-01T18:00:00"]
    }
  },
  "crs": ["EPSG:4326"],
  "output_formats": ["cf_covjson", "csv", "geojson", "nc", "parquet"],
  "data_queries": {
    "position": {...},
    "area": {...},
    "cube": {...}
  },
  "parameter_names": ["air"]
}
```
```

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

### Position Query - Single Point (bash)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Extract data at a specific geographic point using WKT POINT format via a curl command. This example retrieves temperature at a single point for all time steps and returns data in CoverageJSON format.

```bash
# Get temperature at a single point, all time steps
curl "http://localhost:9000/datasets/air/edr/position?coords=POINT(204%2044)"

# Response (CoverageJSON):
{
  "type": "Coverage",
  "domain": {
    "type": "Domain",
    "domainType": "Grid",
    "axes": {
      "x": {"values": [205.0]},
      "y": {"values": [45.0]},
      "t": {"values": ["2013-01-01T00:00:00", "2013-01-01T06:00:00", ...]
    }
  },
  "parameters": {
    "air": {
      "type": "Parameter",
      "description": {"en": "Air temperature"},
      "unit": {"label": {"en": "degK"}},
      "observedProperty": {"id": "air_temperature"}
    }
  },
  "ranges": {
    "air": {
      "type": "NdArray",
      "dataType": "float",
      "values": [241.2, 242.5, 243.1, 244.0]
    }
  }
}
```

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

### GET /datasets/{dataset_id}/edr/position

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Perform a position query to extract data at specific geographic coordinates. Supports single points, multiple points, time ranges, and interpolation.

```APIDOC
## GET /datasets/{dataset_id}/edr/position

### Description
Extract data at a specific geographic point or multiple points. Supports filtering by time, interpolation methods, and selecting specific parameters.

### Method
GET

### Endpoint
`/datasets/{dataset_id}/edr/position`

### Parameters
#### Path Parameters
- **dataset_id** (string) - Required - The identifier of the dataset.

#### Query Parameters
- **coords** (string) - Required - Well-Known Text (WKT) format for coordinates (e.g., `POINT(lon lat)` or `MULTIPOINT((lon1 lat1),(lon2 lat2))`).
- **datetime** (string) - Optional - Specifies the time range or specific timestamp (e.g., `YYYY-MM-DDTHH:MM:SS/YYYY-MM-DDTHH:MM:SS` or a single timestamp).
- **method** (string) - Optional - Interpolation method to use if `datetime` specifies a range (e.g., `linear`).
- **f** (string) - Optional - Desired output format (e.g., `cf_covjson`, `csv`). Defaults to `cf_covjson`.
- **parameter-name** (string or array) - Optional - The name(s) of the parameter(s) to retrieve.

### Response
#### Success Response (200)
The response format depends on the `f` query parameter. Examples include CoverageJSON, CSV, GeoJSON, etc.

#### Response Example (CoverageJSON for single point)
```json
{
  "type": "Coverage",
  "domain": {
    "type": "Domain",
    "domainType": "Grid",
    "axes": {
      "x": {"values": [205.0]},
      "y": {"values": [45.0]},
      "t": {"values": ["2013-01-01T00:00:00", "2013-01-01T06:00:00", ...] }
    }
  },
  "parameters": {
    "air": {
      "type": "Parameter",
      "description": {"en": "Air temperature"},
      "unit": {"label": {"en": "degK"}},
      "observedProperty": {"id": "air_temperature"}
    }
  },
  "ranges": {
    "air": {
      "type": "NdArray",
      "dataType": "float",
      "values": [241.2, 242.5, 243.1, 244.0]
    }
  }
}
```

#### Response Example (CSV for multiple points)
```csv
time,lat,lon,air
2013-01-01T00:00:00,43.0,202.0,241.2
2013-01-01T06:00:00,43.0,202.0,242.5
2013-01-01T00:00:00,45.0,205.0,243.1
2013-01-01T06:00:00,45.0,205.0,244.0
```

#### Response Example (CSV with interpolation)
```csv
time,lat,lon,air
2013-01-01T00:00:00,44.5,204.5,241.75
2013-01-01T06:00:00,44.5,204.5,242.85
2013-01-01T12:00:00,44.5,204.5,243.25
```
```

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

### Query with Custom Dimensions (Python)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Shows how to query data along arbitrary dimensions beyond the standard time, latitude, longitude, and elevation. This example assumes a dataset with dimensions including 'member'.

```python
import requests

# Dataset has dimensions: time, lat, lon, band, member

```

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

### Position Query with Time Range and Interpolation (bash)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Select data for a specific time period using linear interpolation via a curl command. This example retrieves interpolated temperature at exact coordinates for a given date range and returns data in CSV format.

```bash
# Get interpolated temperature at exact coordinates for date range
curl "http://localhost:9000/datasets/air/edr/position?coords=POINT(204.5%2044.5)&datetime=2013-01-01T00:00:00/2013-01-01T12:00:00&method=linear&f=csv"

# Response: CSV with linearly interpolated values at exact coordinates
time,lat,lon,air
2013-01-01T00:00:00,44.5,204.5,241.75
2013-01-01T06:00:00,44.5,204.5,242.85
2013-01-01T12:00:00,44.5,204.5,243.25
```

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

### Query Specific Ensemble Member and Band in NetCDF

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

This snippet demonstrates how to query a specific band and an ensemble member range from a dataset using the xpublish-edr API. It makes a GET request and saves the NetCDF response to a file. Dependencies include the 'requests' library.

```python
import requests

response = requests.get(
    "http://localhost:9000/datasets/ensemble/edr/position",
    params={
        "coords": "POINT(-120 40)",
        "datetime": "2023-01-01",
        "band": "3",
        "member": "5/10",  # Range notation for member dimension
        "f": "nc"
    }
)

# Returns NetCDF with data for band=3, members 5-10
with open("ensemble_subset.nc", "wb") as f:
    f.write(response.content)
```

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

### Handle API Errors for Invalid Coordinates, Parameters, and Formats

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

This Python code illustrates how to handle common API errors when querying xpublish-edr. It shows specific examples for invalid WKT coordinates, non-existent parameter names, and unsupported output formats, checking the response status code and extracting error messages from the JSON response. Dependencies include the 'requests' library.

```python
import requests

base_url = "http://localhost:9000"

# Invalid WKT coordinates
response = requests.get(
    f"{base_url}/datasets/air/edr/position",
    params={"coords": "(71, 41)"}
)
if response.status_code == 422:
    print(f"Invalid geometry: {response.json()['detail']}")
    # Output: "Could not parse coordinates to geometry, check the format of the 'coords' query parameter"

# Invalid parameter name
response = requests.get(
    f"{base_url}/datasets/air/edr/position",
    params={"coords": "POINT(204 44)", "parameter-name": "temperature"}
)
if response.status_code == 404:
    print(f"Error: {response.json()['detail']}")
    # Output: "Error selecting from query: Invalid variable: 'temperature'"

# Invalid format
response = requests.get(
    f"{base_url}/datasets/air/edr/position",
    params={"coords": "POINT(204 44)", "f": "invalid_format"}
)
if response.status_code == 404:
    print(f"Format error: {response.json()['detail']}")
    # Output: "invalid_format is not a valid format for EDR position queries. Get `./position/formats` for valid formats"
```

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

### Get Collection Metadata (bash)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Retrieve OGC EDR collection metadata for a specific dataset using a curl command. The response includes dataset ID, title, description, spatial and temporal extents, CRS, supported output formats, query capabilities, and parameter names.

```bash
curl http://localhost:9000/datasets/air/edr/

# Response includes:
{
  "id": "air",
  "title": "4x daily NMC reanalysis (1948)",
  "description": "Data is from NMC initialized reanalysis\n(4x/day)...",
  "extent": {
    "spatial": {
      "bbox": [[200.0, 15.0, 322.5, 75.0]],
      "crs": "EPSG:4326"
    },
    "temporal": {
      "interval": ["2013-01-01T00:00:00", "2013-01-01T18:00:00"],
      "values": ["2013-01-01T00:00:00/2013-01-01T18:00:00"]
    }
  },
  "crs": ["EPSG:4326"],
  "output_formats": ["cf_covjson", "csv", "geojson", "nc", "parquet"],
  "data_queries": {
    "position": {...},
    "area": {...},
    "cube": {...}
  },
  "parameter_names": ["air"]
}
```

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

### Simplified setup.py with setuptools-scm (Python)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

A minimal `setup.py` file leveraging `setuptools-scm` for automated version management. It configures `setuptools` to generate the package version from source control tags and writes it to a specified file.

```python
from setuptools import setup

setup(
    use_scm_version={
        "write_to": "xpublish_edr/_version.py",
        "write_to_template": '__version__ = "{version}" ',
        "tag_regex": r"^(?P<prefix>v)?(?P<version>[^\+]+)(?P<suffix>.*)?$",
    }
)
```

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

### Setuptools Configuration with SCM Versioning (Python)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Configures setuptools for package building, specifically integrating with Source Code Management (SCM) for versioning. It defines how the package version is written to a file and the regular expression used to parse version tags.

```python
from setuptools import setup

setup(
    use_scm_version={
        "write_to": "ioos_pkg_skeleton/_version.py",
        "write_to_template": '__version__ = "{version}"',
        "tag_regex": r"^(?P<prefix>v)?(?P<version>[^\+]+)(?P<suffix>.*)?$",
    }
)


```

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

### Development Dependencies with requirements-dev.txt

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

The requirements-dev.txt file lists all dependencies necessary for development, including tools for code styling, testing, documentation generation, and building the package. This ensures a consistent development environment.

```default
# code style/consistency
black
flake8
flake8-builtins
flake8-comprehensions
flake8-mutable
flake8-print
isort
pylint
pytest-flake8
# checks and tests
check-manifest
pytest
pytest-cov
pytest-xdist
pre-commit
# documentation
doctr
nbsphinx
sphinx
# build
setuptools_scm
twine
wheel
```

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

### Travis CI: Build Documentation

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Sets up Travis CI to build project documentation when the job name is 'docs'. It copies a tutorial notebook, navigates to the docs directory, cleans and builds HTML documentation, and deploys it using 'doctr' based on whether a tag is present.

```yaml
  - |
    if [[ $TRAVIS_JOB_NAME == 'docs' ]]; then
      set -e
      cp notebooks/tutorial.ipynb docs/source/
      pushd docs
      make clean html linkcheck
      popd
      if [[ -z "$TRAVIS_TAG" ]]; then
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html dev
      else
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html "version-$TRAVIS_TAG"
        python -m doctr deploy --build-tags --key-path github_deploy_key.enc --built-docs docs/_build/html .
      fi
    fi

```

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

### Pre-commit Configuration (.pre-commit-config.yaml)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

Configuration file for pre-commit, specifying various hooks from different repositories to enforce code style, check for errors, and manage dependencies. It includes hooks for trailing whitespace, AST checks, debug statements, end-of-file fixing, docstring validation, large file detection, requirements file fixing, sorting file contents, linting with flake8, sorting imports with isort, generating isort configuration, code formatting with black, and type checking with mypy.

```yaml
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
  rev: v3.1.0
  hooks:
    - id: trailing-whitespace
      exclude: tests/data
    - id: check-ast
    - id: debug-statements
    - id: end-of-file-fixer
    - id: check-docstring-first
    - id: check-added-large-files
    - id: requirements-txt-fixer
    - id: file-contents-sorter
      files: requirements-dev.txt

- repo: https://gitlab.com/pycqa/flake8
  rev: 3.7.9
  hooks:
    - id: flake8
      exclude: docs/source/conf.py
      args: [--max-line-length=105, --ignore=E203,E501,W503, --select=select=C,E,F,W,B,B950]

- repo: https://github.com/pre-commit/mirrors-isort
  rev: v4.3.21
  hooks:
  - id: isort
    additional_dependencies: [toml]
    args: [--project=xpublish_edr, --multi-line=3, --lines-after-imports=2, --lines-between-types=1, --trailing-comma, --force-grid-wrap=0, --use-parentheses, --line-width=88]

- repo: https://github.com/asottile/seed-isort-config
  rev: v2.1.1
  hooks:
    - id: seed-isort-config

- repo: https://github.com/psf/black
  rev: stable
  hooks:
  - id: black
    language_version: python3

- repo: https://github.com/pre-commit/mirrors-mypy
  rev: v0.770
  hooks:
  - id: mypy
    exclude: docs/source/conf.py
    args: [--ignore-missing-imports]

```

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

### Source Distribution Manifest with MANIFEST.in

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

The MANIFEST.in file specifies additional files to be included in the source distribution (sdist) of the package. This is crucial for ensuring that all necessary files, such as README, LICENSE, and Python modules, are packaged correctly.

```default
include *.txt
include LICENSE # Please consider the Windows users and use .txt
include README.md

recursive-include xpublish_edr *.py
```

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

### Development Dependencies: requirements-dev.txt

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Lists the development dependencies required for the xpublish-edr project. This file includes tools for testing, linting, formatting, documentation, and packaging.

```text
black
check-manifest
doctr
flake8
flake8-builtins
flake8-comprehensions
flake8-mutable
flake8-print
isort
nbsphinx
pre-commit
pylint
pytest
pytest-cov
pytest-flake8
pytest-xdist
setuptools_scm
sphinx
twine
wheel
```

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

### PEP 518 Build System Requirements (TOML)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

Specifies the build system requirements for a Python package using PEP 518. This TOML file declares dependencies needed for building the package and the build backend to be used, typically `setuptools.build_meta`.

```toml
[build-system]
requires = ["setuptools>=42", "wheel", "setuptools_scm[toml]>=3.4", "cython", "numpy"]
build-backend = "setuptools.build_meta"
```

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

### Pre-commit Configuration: .isort.cfg

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Configuration file for the 'isort' tool, specifying third-party libraries that should be recognized and grouped separately during import sorting.

```ini
[settings]
known_third_party = numpy,pytest,requests,setuptools

```

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

### Dependency Management with requirements.txt

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/docs/source/how2package4ioos.md

The requirements.txt file lists the Python and non-Python dependencies required for the project. It supports both pip and conda dependencies, with conda dependencies indicated by a '#conda:' prefix. A separate requirements-dev.txt file is recommended for development-specific dependencies.

```default
numpy
requests
#conda: libnetcdf
#conda: libgdal
```

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

### GitHub Actions: Pre-commit Workflow

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Defines a GitHub Actions workflow to run pre-commit hooks on pull requests and pushes to the master branch. It checks out code, sets up Python, caches pre-commit dependencies, and executes the pre-commit action.

```yaml
name: pre-commit

on:
  pull_request:
  push:
    branches: [master]

jobs:
  pre-commit:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v1
    - uses: actions/setup-python@v1
    - name: set PY
      run: echo "::set-env name=PY::$(python --version --version | sha256sum | cut -d' ' -f1)"
    - uses: actions/cache@v1
      with:
        path: ~/.cache/pre-commit
        key: pre-commit|${{ env.PY }}|${{ hashFiles('.pre-commit-config.yaml') }}
    - uses: pre-commit/action@v1.0.0

```

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

### Travis CI Build Matrix Configuration (YAML)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Defines the build matrix for Travis CI, specifying different Python versions and job types (e.g., python-3.6, python-3.8, coding_standards, tarball, docs) to be tested. It uses environment variables to control the build process.

```yaml
language: minimal

sudo: false

env:
  global:
    - secure: "TOKEN"

matrix:
  fast_finish: true
  include:
    - name: "python-3.6"
      env: PY=3.6
    - name: "python-3.8"
      env: PY=3.8
    - name: "coding_standards"
      env: PY=3
    - name: "tarball"
      env: PY=3
    - name: "docs"
      env: PY=3

```

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

### Travis CI Test Execution Script (YAML)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Defines the `script` section for Travis CI builds. It executes tests using pytest for Python-specific jobs, including code coverage analysis. For 'tarball' jobs, it focuses on building wheels, checking manifest, and validating the distribution with twine.

```yaml
script:
  - if [[ $TRAVIS_JOB_NAME == python-* ]]; then
      cp -r tests/ /tmp ;
      pushd /tmp && pytest -n 2 -rxs --cov=ioos_pkg_skeleton tests && popd ;
    fi

  - if [[ $TRAVIS_JOB_NAME == 'tarball' ]]; then
      pip wheel . -w dist --no-deps ;
      check-manifest --verbose ;
      twine check dist/* ;
    fi

```

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

### Travis CI: Test Coding Standards

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Configures Travis CI to run pytest with the flake8 marker when the job name is 'coding_standards'. This is intended for basic code style checks.

```yaml
script:
  - if [[ $TRAVIS_JOB_NAME == 'coding_standards' ]]; then
      pytest --flake8 -m flake8 ;
    fi
```

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

### Custom Format Registration (Python)

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Illustrates how to extend xpublish-edr with custom output formats by defining a formatter function in a Python package and registering it via `pyproject.toml` entry points.

```python
# In your custom package, create a formatter function
# mypackage/formats.py
import xarray as xr

def to_custom_format(ds: xr.Dataset) -> dict:
    """Export dataset in custom JSON format"""
    return {
        "data": ds.to_dict(),
        "metadata": {
            "variables": list(ds.data_vars),
            "dims": dict(ds.dims)
        }
    }

# Register via pyproject.toml entry points
# [project.entry-points.xpublish_edr_position_formats]
# custom = "mypackage.formats:to_custom_format"

# Now available via API:
# curl "http://localhost:9000/datasets/air/edr/position?coords=POINT(204%2044)&f=custom"
```

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

### MANIFEST.in File for Package Inclusion (Text)

Source: https://github.com/xpublish-community/xpublish-edr/blob/main/notebooks/IOOS-Python-Package-Skeleton.ipynb

Specifies additional files to include in the Python package distribution beyond the source code. This includes text files, licenses, and recursively includes all Python files within a specific directory.

```text
include *.txt
include LICENSE # Please consider the Windows users and use .txt
include README.md

recursive-include ioos_pkg_skeleton *.py

```

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

### Plugin Registration

Source: https://context7.com/xpublish-community/xpublish-edr/llms.txt

Register the CfEdrPlugin with xpublish to enable EDR endpoints. This involves loading a dataset and initializing the xpublish.Rest server with the plugin.

```APIDOC
## Plugin Registration

Register the CfEdrPlugin with xpublish to enable EDR endpoints.

```python
import xpublish
import xarray as xr
from xpublish_edr import CfEdrPlugin

# Load your CF-compliant dataset
ds = xr.tutorial.open_dataset("air_temperature")

# Create REST API with EDR plugin
rest = xpublish.Rest(
    {"air": ds},
    plugins={"edr": CfEdrPlugin()}
)

# Start the server
rest.serve()
```
```