### Install EUMDAC from Source

Source: https://github.com/eumetlab/data-services/eumdac/blob/public/README.md

Clone the EUMDAC repository and install it locally using pip.

```bash
git clone https://gitlab.eumetsat.int/eumetlab/data-services/eumdac.git
cd eumdac
pip install .
```

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

### Install EUMDAC with PIP

Source: https://github.com/eumetlab/data-services/eumdac/blob/public/README.md

Use this command to install the EUMDAC Python package from PyPI.

```bash
pip install eumdac
```

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

### Manage filters, ROIs, and quicklooks

Source: https://context7.com/eumetlab/data-services/llms.txt

Perform management operations (list, get details, save, update, delete) on filters, regions of interest (ROIs), and quicklooks. The same command structure applies to all resource types.

```bash
eumdac tailor filters
```

```bash
eumdac tailor rois
```

```bash
eumdac tailor quicklooks
```

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

### Install EUMDAC with Conda

Source: https://github.com/eumetlab/data-services/eumdac/blob/public/README.md

Install EUMDAC on an Anaconda Python distribution using the provided conda command.

```bash
conda install -c eumetsat-forge eumdac
```

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

### Get job log

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve the log file for a specific customization job. The log contains detailed information about the processing steps and any errors encountered.

```python
print(f"Log:\n{customisation.logfile}")
```

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

### Get a specific customization by ID

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve details of a specific customization job using its unique ID.

```python
customisation = datatailor.get_customisation('abc123-def456')
```

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

### Get details of a specific chain

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve detailed information about a specific data processing chain using its ID. This is useful for understanding chain configurations.

```bash
eumdac tailor chains --id my-chain-id
```

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

### Getting Collection Information

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieves metadata about data collections, including search options, date ranges, and descriptions.

```APIDOC
## Getting Collection Information

### Description
The `Collection` class provides metadata about data collections including available search options, date ranges, and detailed descriptions.

### Method
`datastore.get_collection(collection_id)`

### Endpoint
N/A (Method call on DataStore object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

# Get a specific collection by ID
collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')

# Access collection properties
print(f"Title: {collection.title}")
print(f"Abstract: {collection.abstract}")

# Get full metadata
metadata = collection.metadata
print(f"Date range: {metadata['properties'].get('date')}")
print(f"License: {metadata['properties'].get('rights')}")

# List available search options for the collection
for option_name, option_info in collection.search_options.items():
    print(f"{option_name}: {option_info['title']}")
    if option_info['options']:
        print(f"  Accepts: {option_info['options']}")
```

### Response
#### Success Response (200)
Returns a `Collection` object with metadata.

#### Response Example
```json
{
  "title": "High Rate SEVIRI Level 1.5 Image Data - MSG - 0 degree",
  "abstract": "This collection contains High Rate (HR) SEVIRI image data...",
  "metadata": {
    "properties": {
      "date": "2004-01-01T00:00:00Z/2024-12-31T23:59:59Z",
      "rights": "EUMETSAT data policy"
    }
  },
  "search_options": {
    "dtstart": {"title": "Start Time", ...},
    "dtend": {"title": "End Time", ...},
    "bbox": {"title": "Bounding Box", ...}
  }
}
```
```

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

### Get detailed job status

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve detailed status information for a specific customization job using the verbose flag. This provides more in-depth information about the job's state.

```bash
eumdac tailor status job-id-1 -v
```

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

### Get Collection Information and Metadata

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieves metadata for a specific data collection, including title, abstract, date range, license, and available search options. Use the collection ID to fetch details.

```python
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

# Get a specific collection by ID
collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')

# Access collection properties
print(f"Title: {collection.title}")
print(f"Abstract: {collection.abstract}")

# Get full metadata
metadata = collection.metadata
print(f"Date range: {metadata['properties'].get('date')}")
print(f"License: {metadata['properties'].get('rights')}")

# List available search options for the collection
for option_name, option_info in collection.search_options.items():
    print(f"{option_name}: {option_info['title']}")
    if option_info['options']:
        print(f"  Accepts: {option_info['options']}")
```

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

### Initializing the DataStore

Source: https://context7.com/eumetlab/data-services/llms.txt

Provides the main interface for accessing EUMETSAT's data collections, searching for products, and downloading satellite data.

```APIDOC
## Initializing the DataStore

### Description
The `DataStore` class provides the main interface for accessing EUMETSAT's data collections, searching for products, and downloading satellite data.

### Method
Initialization of `DataStore` object.

### Endpoint
N/A (Class initialization)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from eumdac import AccessToken, DataStore

# Setup authentication
credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)

# Initialize DataStore with authenticated token
datastore = DataStore(token)

# List all available collections
for collection in datastore.collections:
    print(f"{collection} - {collection.title}")
```

### Response
#### Success Response (200)
N/A (Class initialization, returns DataStore object)

#### Response Example
```json
{
  "message": "DataStore initialized successfully.",
  "collections_available": [
    "EO:EUM:DAT:MSG:HRSEVIRI",
    "EO:EUM:DAT:MSG:MSG15-RSS",
    "EO:EUM:DAT:0080"
  ]
}
```
```

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

### Initialize DataStore for Data Access

Source: https://context7.com/eumetlab/data-services/llms.txt

Provides the main interface for accessing EUMETSAT's data collections, searching for products, and downloading satellite data. Requires an authenticated token.

```python
from eumdac import AccessToken, DataStore

# Setup authentication
credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)

# Initialize DataStore with authenticated token
datastore = DataStore(token)

# List all available collections
for collection in datastore.collections:
    print(f"{collection} - {collection.title}")

# Output example:
# EO:EUM:DAT:MSG:HRSEVIRI - High Rate SEVIRI Level 1.5 Image Data - MSG - 0 degree
# EO:EUM:DAT:MSG:MSG15-RSS - Rapid Scan High Rate SEVIRI Level 1.5 Image Data - MSG
# EO:EUM:DAT:0080 - MVIRI Level 1.5 Climate Data Record - MFG - 0 degree
```

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

### List all orders

Source: https://context7.com/eumetlab/data-services/llms.txt

List all download orders. This command provides a summary of all orders, including their status and associated data.

```bash
eumdac order list
```

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

### Submit job with chain from file

Source: https://context7.com/eumetlab/data-services/llms.txt

Submit a new customization job using a chain configuration defined in a YAML file. Ensure the YAML file path is correctly specified.

```bash
eumdac tailor post -c EO:EUM:DAT:MSG:HRSEVIRI \
    -p MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA \
    --chain ./my_chain.yaml
```

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

### List orders with verbose details

Source: https://context7.com/eumetlab/data-services/llms.txt

List all download orders with verbose details. The verbose flag provides more comprehensive information about each order.

```bash
eumdac order list -v
```

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

### Perform OpenSearch Query

Source: https://context7.com/eumetlab/data-services/llms.txt

Use OpenSearch queries for flexible product searches. The 'pi' parameter is required.

```python
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

# Perform an OpenSearch query (pi parameter is required)
query = "pi=EO:EUM:DAT:MSG:HRSEVIRI&dtstart=2024-01-01T00:00:00&dtend=2024-01-01T12:00:00"
results = datastore.opensearch(query)

print(f"Found {results.total_results} products")
for product in results:
    print(product)
```

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

### List all available chains

Source: https://context7.com/eumetlab/data-services/llms.txt

List all available data processing chains. This command helps in identifying existing chains for use or management.

```bash
eumdac tailor chains
```

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

### Download job outputs

Source: https://context7.com/eumetlab/data-services/llms.txt

Download the output files for a specific customization job. Specify the output directory using the --output-dir option.

```bash
eumdac tailor download job-id-1 --output-dir ./outputs
```

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

### Search for Chains by Product and Format

Source: https://context7.com/eumetlab/data-services/llms.txt

Utilize the Python API to find processing chains that match specific product and format criteria.

```python
matching_chains = datatailor.chains.search(product="HRSEVIRI", format="netcdf4")
```

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

### List all customization jobs

Source: https://context7.com/eumetlab/data-services/llms.txt

List all submitted customization jobs. This command provides a summary of all jobs, regardless of their status.

```bash
eumdac tailor list
```

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

### Submit a new customization job

Source: https://context7.com/eumetlab/data-services/llms.txt

Submit a new customization job with a specified product and chain configuration. The chain can be defined inline as a JSON string.

```bash
eumdac tailor post -c EO:EUM:DAT:MSG:HRSEVIRI \
    -p MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA \
    --chain '{"product": "HRSEVIRI", "format": "netcdf4"}'
```

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

### Initialize AccessToken for Authentication

Source: https://context7.com/eumetlab/data-services/llms.txt

Handles OAuth2 authentication with EUMETSAT APIs. Initialize with consumer key and secret. Tokens have a default 24-hour validity but can be customized. The token string value triggers automatic refresh if expired.

```python
from eumdac import AccessToken

# Initialize with your consumer key and secret from EUMETSAT
consumer_key = 'your-consumer-key'
consumer_secret = 'your-consumer-secret'
credentials = (consumer_key, consumer_secret)

# Create token with default 24-hour validity
token = AccessToken(credentials)

# Create token with custom validity period (in seconds)
token = AccessToken(credentials, validity=3600)  # 1 hour validity

# Get the token string value (triggers automatic refresh if expired)
token_value = str(token)

# Check token expiration time
print(f"Token expires at: {token.expiration}")
```

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

### Create a processing chain

Source: https://context7.com/eumetlab/data-services/llms.txt

Define a processing chain for customizing data products. This includes specifying the product, format, projection, region of interest, and compression.

```python
chain = Chain(
    product="HRSEVIRI",
    format="netcdf4",
    projection="geographic",
    roi=roi,
    filter=filter_bands,
    compression={"algorithm": "internal"}
)
```

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

### Resume/restart a failed order

Source: https://context7.com/eumetlab/data-services/llms.txt

Resume or restart a download order that has failed. This command attempts to continue the download from where it left off or restart the process.

```bash
eumdac order restart order-id
```

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

### Download outputs when job is DONE

Source: https://context7.com/eumetlab/data-services/llms.txt

Download the output files of a completed customization job. The code iterates through the output names, streams the content, and saves it to a specified directory.

```python
if customisation.status == 'DONE':
    output_dir = Path("./tailor_outputs")
    output_dir.mkdir(exist_ok=True)

    for output_name in customisation.outputs:
        output_path = output_dir / Path(output_name).name
        with customisation.stream_output(output_name) as stream:
            with output_path.open('wb') as f:
                f.write(stream.read())
        print(f"Downloaded: {output_path}")
```

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

### Create chain from dictionary

Source: https://context7.com/eumetlab/data-services/llms.txt

An alternative method to create a processing chain by providing configuration as a dictionary.

```python
chain_dict = {
    "product": "HRSEVIRI",
    "format": "geotiff",
    "projection": "geographic",
    "roi": {"NSWE": "60.0,40.0,-10.0,30.0"}
}
chain = Chain(**chain_dict)
```

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

### Download Products and Entries

Source: https://context7.com/eumetlab/data-services/llms.txt

Download entire satellite data products or specific files (entries) within a product using a stream for memory-efficient handling of large files. Requires specifying output directory.

```python
from pathlib import Path
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')
results = collection.search(
    dtstart="2024-01-15T10:00:00",
    dtend="2024-01-15T10:30:00"
)

output_dir = Path("./downloads")
output_dir.mkdir(exist_ok=True)

for product in results:
    # Download the full product
    with product.open() as stream:
        filename = stream.name
        output_path = output_dir / filename
        with output_path.open('wb') as f:
            # Read and write in chunks for memory efficiency
            while True:
                chunk = stream.read(1024 * 1024)  # 1 MB chunks
                if not chunk:
                    break
                f.write(chunk)
        print(f"Downloaded: {output_path}")

    # Download a specific entry (file within the product)
    for entry in product.entries:
        if entry.endswith('.nat'):  # Example: download only .nat files
            with product.open(entry=entry) as stream:
                entry_path = output_dir / stream.name
                with entry_path.open('wb') as f:
                    f.write(stream.read())
                print(f"Downloaded entry: {entry_path}")
            break
```

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

### Submit multiple products for customization

Source: https://context7.com/eumetlab/data-services/llms.txt

Submit multiple products for customization in a single request. This is more efficient for batch processing.

```python
products = list(results)[:5]  # First 5 products
customisations = datatailor.new_customisations(products, chain)
for c in customisations:
    print(f"Job {c}: {c.status}")
```

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

### Initialize DataTailor Service

Source: https://context7.com/eumetlab/data-services/llms.txt

Initialize the DataTailor service to access EUMETSAT's Data Tailor for customizing and processing satellite data products. Provides access to service info, user details, and workspace quota.

```python
from eumdac import AccessToken, DataTailor

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)

# Initialize DataTailor
datatailor = DataTailor(token)

# Get service information
print(f"Data Tailor Info: {datatailor.info}")
print(f"User Info: {datatailor.user_info}")

# Check workspace quota
quota = datatailor.quota
print(f"Workspace usage: {quota}")
```

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

### Set EUMDAC Credentials

Source: https://context7.com/eumetlab/data-services/llms.txt

Configure your EUMDAC API credentials using the CLI. This command prompts for your consumer key and secret.

```bash
eumdac set-credentials your-consumer-key your-consumer-secret
```

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

### List all existing customizations

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve a list of all existing customization jobs managed by the Data Tailor service. Displays job ID and status.

```python
import time
from pathlib import Path
from eumdac import AccessToken, DataTailor

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datatailor = DataTailor(token)

# List all existing customizations
for customisation in datatailor.customisations:
    print(f"Job {customisation}: {customisation.status} - {customisation.product_type}")
```

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

### View job log

Source: https://context7.com/eumetlab/data-services/llms.txt

View the log output for a specific customization job. This is helpful for debugging or understanding job execution details.

```bash
eumdac tailor log job-id-1
```

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

### Access Product Details

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve comprehensive metadata for a specific satellite data product, including sensing times, instrument information, and file entries. Supports LEO and MTG product specific properties.

```python
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

# Get a specific product directly
product = datastore.get_product(
    'EO:EUM:DAT:MSG:HRSEVIRI',
    'MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA'
)

# Access product metadata
print(f"Product ID: {product}")
print(f"Satellite: {product.satellite}")
print(f"Instrument: {product.instrument}")
print(f"Product Type: {product.product_type}")
print(f"Sensing Start: {product.sensing_start}")
print(f"Sensing End: {product.sensing_end}")
print(f"Publication Time: {product.ingested}")
print(f"Size: {product.size} KB")
print(f"MD5 Checksum: {product.md5}")
print(f"Orbit Type: {product.orbit_type}")

# For LEO products, additional properties are available
if product.orbit_is_LEO:
    print(f"Orbit Number: {product.orbit_number}")
    print(f"Orbit Direction: {product.orbit_direction}")
    print(f"Relative Orbit: {product.relative_orbit}")
    print(f"Cycle Number: {product.cycle_number}")
    print(f"Timeliness: {product.timeliness}")

# For MTG products
if product.is_mtg:
    print(f"Region Coverage: {product.region_coverage}")
    print(f"Sub-Region: {product.subregion_identifier}")
    print(f"Repeat Cycle: {product.repeat_cycle}")

# List files inside the product (SIP entries)
print("Product entries:")
for entry in product.entries:
    print(f"  - {entry}")

# Get product download URL
print(f"Download URL: {product.url}")
```

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

### Download EUMDAC Products

Source: https://context7.com/eumetlab/data-services/llms.txt

Download products based on search criteria, specific product IDs, or entries. Supports integrity checks, parallel downloads, and output directory structuring.

```bash
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --output-dir ./downloads
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    -p MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA \
    --output-dir ./downloads
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --output-dir ./downloads \
    --integrity
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --entry "*.nat" \
    --output-dir ./downloads
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --output-dir ./downloads \
    --download-threads 5
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --output-dir ./downloads \
    --dirs
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-16 \
    --output-dir ./downloads \
    --yes
eumdac download -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T10:00:00 --end 2024-01-15T10:30:00 \
    --output-dir ./downloads \
    --chain '{"product": "HRSEVIRI", "format": "netcdf4"}'
eumdac download-cart ./my_cart.xml --output-dir ./downloads
```

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

### Use context manager for automatic cleanup

Source: https://context7.com/eumetlab/data-services/llms.txt

Submit a customization job using a context manager. The job is automatically deleted upon exiting the context, ensuring cleanup.

```python
with datatailor.new_customisation(product, chain) as customisation:
    while customisation.status in ['QUEUED', 'RUNNING']:
        time.sleep(10)
    # Download outputs...
# Job is automatically deleted when exiting the context
```

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

### List archived or failed orders

Source: https://context7.com/eumetlab/data-services/llms.txt

List download orders that have been archived or have failed. These flags help in identifying orders that may require attention or review.

```bash
eumdac order list --archived
```

```bash
eumdac order list --failed
```

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

### Create a band filter for selecting specific channels

Source: https://context7.com/eumetlab/data-services/llms.txt

Define a filter to select specific bands from a product. This is useful for creating custom processing chains.

```python
filter_bands = Filter(
    name="visible_bands",
    product="HRSEVIRI",
    bands=[
        {"id": "VIS006", "number": 1, "name": "VIS 0.6"},
        {"id": "VIS008", "number": 2, "name": "VIS 0.8"},
        {"id": "IR_016", "number": 3, "name": "IR 1.6"}
    ]
)
```

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

### Submit a single customization job

Source: https://context7.com/eumetlab/data-services/llms.txt

Submit a single data customization job to the Data Tailor service. Requires authentication credentials and a product to process.

```python
from eumdac import AccessToken, DataStore, DataTailor
from eumdac.tailor_models import Chain

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)
datatailor = DataTailor(token)

# Get a product to customize
collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')
results = collection.search(dtstart="2024-01-15T12:00:00", dtend="2024-01-15T12:30:00")
product = results.first()

# Define processing chain
chain = Chain(
    product="HRSEVIRI",
    format="netcdf4",
    projection="geographic"
)

# Submit a single customization job
customisation = datatailor.new_customisation(product, chain)
print(f"Customisation ID: {customisation}")
print(f"Status: {customisation.status}")
```

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

### Check status of the latest order

Source: https://context7.com/eumetlab/data-services/llms.txt

Check the status of the most recently placed download order. This is a convenient way to monitor the latest download activity.

```bash
eumdac order status latest
```

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

### Create a filter

Source: https://context7.com/eumetlab/data-services/llms.txt

Create a new data filter configuration from a YAML file. This allows for defining specific criteria for data selection.

```bash
eumdac tailor filters --save ./filter.yaml
```

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

### Create a new ROI

Source: https://context7.com/eumetlab/data-services/llms.txt

Create a new region of interest (ROI) by providing its configuration as a JSON string. The NSWE (North, South, West, East) coordinates define the geographical boundaries.

```bash
eumdac tailor rois --save '{"id": "europe", "name": "Europe", "NSWE": "72,34,-25,45"}'
```

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

### Check status of a specific order

Source: https://context7.com/eumetlab/data-services/llms.txt

Check the status of a specific download order by providing its order ID. This is useful for monitoring download progress.

```bash
eumdac order status order-id
```

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

### Delete all orders

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete all download orders. Use the --all flag to confirm the deletion of all order records.

```bash
eumdac order delete --all
```

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

### Authentication with AccessToken

Source: https://context7.com/eumetlab/data-services/llms.txt

Handles OAuth2 authentication with EUMETSAT APIs, including token generation and automatic renewal.

```APIDOC
## Authentication with AccessToken

### Description
The `AccessToken` class handles OAuth2 authentication with EUMETSAT APIs, managing token generation and automatic renewal when tokens expire.

### Method
Initialization of `AccessToken` object.

### Endpoint
N/A (Class initialization)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from eumdac import AccessToken

# Initialize with your consumer key and secret from EUMETSAT
consumer_key = 'your-consumer-key'
consumer_secret = 'your-consumer-secret'
credentials = (consumer_key, consumer_secret)

# Create token with default 24-hour validity
token = AccessToken(credentials)

# Create token with custom validity period (in seconds)
token = AccessToken(credentials, validity=3600)  # 1 hour validity

# Get the token string value (triggers automatic refresh if expired)
token_value = str(token)

# Check token expiration time
print(f"Token expires at: {token.expiration}")
```

### Response
#### Success Response (200)
N/A (Class initialization, returns token object)

#### Response Example
```json
{
  "token_value": "<your_access_token>",
  "expiration": "<token_expiration_datetime>"
}
```
```

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

### Monitor job progress

Source: https://context7.com/eumetlab/data-services/llms.txt

Continuously monitor the progress of a customization job. The loop checks the status and progress percentage, pausing for 10 seconds between checks.

```python
while customisation.status in ['QUEUED', 'RUNNING']:
    print(f"Status: {customisation.status}, Progress: {customisation.progress}%")
    time.sleep(10)

print(f"Final status: {customisation.status}")
print(f"Duration: {customisation.duration} seconds")
print(f"Processing steps: {customisation.processing_steps}")
```

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

### Create and save a new filter

Source: https://context7.com/eumetlab/data-services/llms.txt

Create a new filter object and save it to the Data Tailor service. Filters are used to select specific bands or channels for processing.

```python
new_filter = Filter(
    id="my_rgb_bands",
    name="RGB Bands",
    product="HRSEVIRI",
    bands=[{"id": "VIS006"}, {"id": "VIS008"}, {"id": "IR_016"}]
)
datatailor.filters.create(new_filter)
```

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

### Housekeep orders

Source: https://context7.com/eumetlab/data-services/llms.txt

Perform housekeep operations on download orders, which typically involves archiving old orders or cleaning up completed downloads. This helps manage storage.

```bash
eumdac order housekeep
```

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

### Describe EUMDAC Collections

Source: https://context7.com/eumetlab/data-services/llms.txt

List available data collections or retrieve detailed information about a specific collection or product using the CLI. Filtering by keyword is supported.

```bash
eumdac describe
eumdac describe --filter "SEVIRI"
eumdac describe --filter "*MSG*"
eumdac describe -c EO:EUM:DAT:MSG:HRSEVIRI
eumdac describe -c EO:EUM:DAT:MSG:HRSEVIRI -p MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA
eumdac describe -c EO:EUM:DAT:MSG:HRSEVIRI -p MSG4-SEVI-MSG15-0100-NA-20240115120000.000000000Z-NA -v
```

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

### Searching for Products

Source: https://context7.com/eumetlab/data-services/llms.txt

Finds products matching specific criteria within a collection, such as date ranges and geographic bounds.

```APIDOC
## Searching for Products

### Description
Use the `search()` method on collections to find products matching specific criteria such as date ranges, geographic bounds, and satellite parameters.

### Method
`collection.search(dtstart, dtend, bbox, sat, ...)`

### Endpoint
N/A (Method call on Collection object)

### Parameters
#### Path Parameters
None

#### Query Parameters
- **dtstart** (datetime) - Required - The start date/time for the search.
- **dtend** (datetime) - Required - The end date/time for the search.
- **bbox** (string) - Optional - Bounding box in the format "west,south,east,north".
- **sat** (string) - Optional - Specific satellite identifier (e.g., "MSG4").

#### Request Body
None

### Request Example
```python
from datetime import datetime
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')

# Search with date range
results = collection.search(
    dtstart=datetime(2024, 1, 1, 0, 0, 0),
    dtend=datetime(2024, 1, 1, 23, 59, 59)
)

# Get total count without iterating
print(f"Total products found: {results.total_results}")

# Iterate through results
for product in results:
    print(f"Product ID: {product}")
    print(f"  Sensing start: {product.sensing_start}")
    print(f"  Sensing end: {product.sensing_end}")
    print(f"  Size: {product.size} KB")
    break  # Just show first result

# Get only the first product
first_product = results.first()

# Search with additional parameters
results = collection.search(
    dtstart=datetime(2024, 1, 15),
    dtend=datetime(2024, 1, 16),
    bbox="-10,35,30,60",  # Bounding box: west,south,east,north
    sat="MSG4"  # Specific satellite
)
```

### Response
#### Success Response (200)
Returns a `ProductList` object containing matching products.

#### Response Example
```json
{
  "total_results": 150,
  "products": [
    {
      "id": "<product_id_1>",
      "sensing_start": "2024-01-01T00:00:00Z",
      "sensing_end": "2024-01-01T00:15:00Z",
      "size": 5000
    },
    ...
  ]
}
```
```

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

### Check workspace quota

Source: https://context7.com/eumetlab/data-services/llms.txt

Check the current workspace quota usage. Use the verbose flag for more detailed information.

```bash
eumdac tailor quota
```

```bash
eumdac tailor quota -v  # Verbose output
```

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

### Create Region of Interest and Chain

Source: https://context7.com/eumetlab/data-services/llms.txt

Use the Python API to define and create custom regions of interest and processing chains.

```python
roi = RegionOfInterest(
    id="mediterranean",
    name="Mediterranean Sea",
    NSWE="46.0,30.0,-6.0,37.0",
    description="Mediterranean region"
)
datatailor.rois.create(roi)

chain = Chain(
    id="my_processing_chain",
    product="HRSEVIRI",
    format="netcdf4",
    projection="geographic",
    description="Standard processing chain"
)
datatailor.chains.create(chain)
```

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

### Search EUMDAC Products by Date and Bounding Box

Source: https://context7.com/eumetlab/data-services/llms.txt

Find products within a specified date range and geographic area. Supports various date formats and bounding box specifications.

```bash
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15T00:00:00 \
    --end 2024-01-15T23:59:59
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --time-range 2024-01-15 2024-01-16
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-16 \
    --bbox "-10,35,30,60"
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-16 \
    --satellite MSG4
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-16 \
    --limit 10
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-16 \
    --sort start --asc
eumdac search -c EO:EUM:DAT:METOP:ASCSZF1B \
    --start 2024-01-15 --end 2024-01-16 \
    --acronym ASCSZF1B
eumdac search -c EO:EUM:DAT:MSG:HRSEVIRI \
    --start 2024-01-15 --end 2024-01-20 \
    --daily-window 10:00:00 14:00:00
```

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

### Save a new chain from YAML/JSON

Source: https://context7.com/eumetlab/data-services/llms.txt

Save a new data processing chain configuration from a YAML or JSON file. This allows for creating custom processing workflows.

```bash
eumdac tailor chains --save ./chain.yaml
```

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

### Delete a finished job (cleanup)

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete a completed customization job from the system to clean up resources. This action is irreversible.

```python
customisation.delete()
print("Job deleted")
```

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

### Check status of specific jobs

Source: https://context7.com/eumetlab/data-services/llms.txt

Check the status of one or more specific customization jobs by providing their job IDs. This is useful for monitoring progress.

```bash
eumdac tailor status job-id-1 job-id-2
```

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

### List all saved filters

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve a list of all filters saved on the Data Tailor service. This allows you to see available filters and their IDs.

```python
from eumdac import AccessToken, DataTailor
from eumdac.tailor_models import Chain, Filter, RegionOfInterest, Quicklook

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datatailor = DataTailor(token)

# Work with filters
# List all saved filters
filters = datatailor.filters.search()
for f in filters:
    print(f"Filter: {f.id}")
```

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

### Define Region of Interest for Data Tailor

Source: https://context7.com/eumetlab/data-services/llms.txt

Create a Region of Interest (ROI) object for use in Data Tailor processing chains. Requires a name, NSWE coordinates (North, South, West, East in decimal degrees), and an optional description.

```python
from eumdac.tailor_models import Chain, Filter, RegionOfInterest

# Create a Region of Interest (ROI)
roi = RegionOfInterest(
    name="Europe",
    NSWE="72.0,34.0,-25.0,45.0",  # North, South, West, East in decimal degrees
    description="European coverage area"
)

```

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

### Update an existing chain

Source: https://context7.com/eumetlab/data-services/llms.txt

Update an existing data processing chain using a YAML file. Ensure the file contains the correct chain ID for modification.

```bash
eumdac tailor chains --update ./chain.yaml
```

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

### Clear all jobs

Source: https://context7.com/eumetlab/data-services/llms.txt

Cancel all running jobs and delete all finished jobs. Use the --all flag to confirm clearing all jobs.

```bash
eumdac tailor clear --all
```

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

### Search for Products within a Collection

Source: https://context7.com/eumetlab/data-services/llms.txt

Searches for satellite data products within a collection using criteria like date ranges, bounding boxes, and specific satellite identifiers. Returns a results object that can be iterated or accessed for the first product.

```python
from datetime import datetime
from eumdac import AccessToken, DataStore

credentials = ('your-consumer-key', 'your-consumer-secret')
token = AccessToken(credentials)
datastore = DataStore(token)

collection = datastore.get_collection('EO:EUM:DAT:MSG:HRSEVIRI')

# Search with date range
results = collection.search(
    dtstart=datetime(2024, 1, 1, 0, 0, 0),
    dtend=datetime(2024, 1, 1, 23, 59, 59)
)

# Get total count without iterating
print(f"Total products found: {results.total_results}")

# Iterate through results
for product in results:
    print(f"Product ID: {product}")
    print(f"  Sensing start: {product.sensing_start}")
    print(f"  Sensing end: {product.sensing_end}")
    print(f"  Size: {product.size} KB")
    break  # Just show first result

# Get only the first product
first_product = results.first()

# Search with additional parameters
results = collection.search(
    dtstart=datetime(2024, 1, 15),
    dtend=datetime(2024, 1, 16),
    bbox="-10,35,30,60",  # Bounding box: west,south,east,north
    sat="MSG4"  # Specific satellite
)

```

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

### Generate EUMDAC Access Token

Source: https://context7.com/eumetlab/data-services/llms.txt

Obtain an authentication token for API access. Tokens can be generated with a specific validity period or forced to be new.

```bash
eumdac token
eumdac token --validity 3600
eumdac token --force
```

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

### Read a specific filter

Source: https://context7.com/eumetlab/data-services/llms.txt

Retrieve the details of a specific filter from the Data Tailor service using its ID.

```python
filter_data = datatailor.filters.read("my_rgb_bands")
```

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

### Delete an order

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete a specific download order by its ID. This action removes the order record and potentially associated temporary files.

```bash
eumdac order delete order-id
```

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

### Update a filter

Source: https://context7.com/eumetlab/data-services/llms.txt

Update an existing filter on the Data Tailor service. This allows modification of filter properties like its name or band configuration.

```python
filter_data.name = "Updated RGB Bands"
datatailor.filters.update(filter_data)
```

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

### Delete finished jobs

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete one or more finished customization jobs by providing their job IDs. This action removes completed jobs from the system.

```bash
eumdac tailor delete job-id-1 job-id-2
```

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

### Cancel a running job

Source: https://context7.com/eumetlab/data-services/llms.txt

Cancel a customization job that is currently queued or running. This action stops the processing and frees up resources.

```python
if customisation.status in ['QUEUED', 'RUNNING']:
    customisation.kill()
    print("Job cancelled")
```

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

### Cancel running jobs

Source: https://context7.com/eumetlab/data-services/llms.txt

Cancel one or more running customization jobs by providing their job IDs. This action stops ongoing processing.

```bash
eumdac tailor cancel job-id-1 job-id-2
```

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

### Delete a filter

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete a filter from the Data Tailor service using its ID. This action removes the filter permanently.

```python
datatailor.filters.delete("my_rgb_bands")
```

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

### Delete a chain

Source: https://context7.com/eumetlab/data-services/llms.txt

Delete a specific data processing chain by its ID. This action permanently removes the chain from the system.

```bash
eumdac tailor chains --delete my-chain-id
```

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