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Description:
azureagrifoodfarming 1.0.0b2
Azure FarmBeats client library for Python
FarmBeats is a B2B PaaS offering from Microsoft that makes it easy for AgriFood companies to build intelligent digital agriculture solutions on Azure. FarmBeats allows users to acquire, aggregate, and process agricultural data from various sources (farm equipment, weather, satellite) without the need to invest in deep data engineering resources. Customers can build SaaS solutions on top of FarmBeats and leverage first class support for model building to generate insights at scale.
Use FarmBeats client library for Python to do the following.
Create & update parties, farms, fields, seasonal fields and boundaries.
Ingest satellite and weather data for areas of interest.
Ingest farm operations data covering tilling, planting, harvesting and application of farm inputs.
Source code | Package (PyPi) | API reference documentation | Product documentation | Changelog
Getting started
Prerequisites
To use this package, you must have:
Azure subscription - Create a free account
Azure FarmBeats resource - Install FarmBeats
3.6 or later - Install Python
Install the package
Install the Azure FarmBeats client library for Python with pip:
pip install azure-agrifood-farming
Authenticate the client
To use an Azure Active Directory (AAD) token credential,
provide an instance of the desired credential type obtained from the
azure-identity library.
To authenticate with AAD, you must first pip install azure-identity and
enable AAD authentication on your FarmBeats resource. If you followed the installation docs when creating the FarmBeats
resource, this is already covered.
After setup, you can choose which type of credential from azure.identity to use.
As an example, DefaultAzureCredential
can be used to authenticate the client:
Set the values of the client ID, tenant ID, and client secret of the AAD application as environment variables:
AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET
Use the returned token credential to authenticate the client:
from azure.agrifood.farming import FarmBeatsClient
from azure.identity import DefaultAzureCredential
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
Key concepts
Basic understanding of below terms will help to get started with FarmBeats client library.
Farm Hierarchy
Farm hierarchy is a collection of below entities.
Party - is the custodian of all the agronomic data.
Farm - is a logical collection of fields and/or seasonal fields. They do not have any area associated with them.
Field - is a multi-polygon area. This is expected to be stable across seasons.
Seasonal field - is a multi-polygon area. To define a seasonal boundary we need the details of area (boundary), time (season) and crop. New seasonal fields are expected to be created for every growing season.
Boundary - is the actual multi-polygon area expressed as a geometry (in geojson). It is normally associated with a field or a seasonal field. Satellite, weather and farm operations data is linked to a boundary.
Cascade delete - Agronomic data is stored hierarchically with party as the root. The hierarchy includes Party -> Farms -> Fields -> Seasonal Fields -> Boundaries -> Associated data (satellite, weather, farm operations). Cascade delete refers to the process of deleting any node and its subtree.
Scenes
Scenes refers to images normally ingested using satellite APIs. This includes raw bands and derived bands (Ex: NDVI). Scenes may also include spatial outputs of an inference or AI/ML model (Ex: LAI).
Farm Operations
Fam operations includes details pertaining to tilling, planting, application of pesticides & nutrients, and harvesting. This can either be manually pushed into FarmBeats using APIs or the same information can be pulled from farm equipment service providers like John Deere.
Examples
Create a Party
Once you have authenticated and created the client object as shown in the Authenticate the client
section, you can create a party within the FarmBeats resource like this:
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
party_id = "party-1"
party = client.parties.create_or_update(
party_id=party_id,
party={
"name": party_name,
"description": party_description
}
)
Create a Farm
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
party_id = "party-1" # Using party from previous example
farm = client.farms.create_or_update(
party_id=party_id,
farm_id="farm-1",
farm={
"name": farm_name,
"description": farm_description
}
)
Create a Season
Creating a Season object, spanning from April to August of 2021.
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
season_id = "contoso-season"
season_name = "contoso-season-name"
season_description = "contoso-season-description"
year = "2021"
start_date_time = "2021-01-01T20:08:10.137Z"
end_date_time = "2021-06-06T20:08:10.137Z"
season = client.seasons.create_or_update(
season_id=season_id,
season={
"name": season_name,
"year": year,
"startDateTime": start_date_time,
"endDateTime": end_date_time,
"description": season_description
}
)
Create a Boundary
Creating a Boundary for the Seasonal Field created in the preceding example.
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
party_id = "party-1"
boundary_id = "boundary-1"
boundary = client.boundaries.create_or_update(
party_id=party_id,
boundary_id=boundary_id,
boundary={
"geometry": {
"type": "Polygon",
"coordinates":
[
[
[73.70457172393799, 20.545385304358106],
[73.70457172393799, 20.545385304358106],
[73.70448589324951, 20.542411534243367],
[73.70877742767334, 20.541688176010233],
[73.71023654937744, 20.545083911372505],
[73.70663166046143, 20.546992723579137],
[73.70457172393799, 20.545385304358106],
]
]
},
"status": "<string>",
"name": "<string>",
"description": "<string>"
}
)
Ingest Satellite Imagery
Triggering a Satellite Data Ingestion job for the boundary created above,
to ingest Leaf Area Index data for the month of January 2020.
This is a Long Running Operation (also called a 'Job'), and returns
a Poller object. Calling the .result() method on the poller object
waits for the operation to terminate, and returns the final status.
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
from isodate.tzinfo import Utc
from datetime import datetime
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
party_id = "party-1"
boundary_id = "westlake-boundary-1"
start_date_time = "2021-01-01T20:08:10.137Z"
end_date_time = "2021-06-06T20:08:10.137Z"
# Queue the job
satellite_job_poller = client.scenes.begin_create_satellite_data_ingestion_job(
job_id=job_id,
job={
"boundaryId": boundary_id,
"endDateTime": end_date_time,
"partyId": party_id,
"startDateTime": start_date_time,
"provider": "Microsoft",
"source": "Sentinel_2_L2A",
"data": {
"imageNames": [
"NDVI"
],
"imageFormats": [
"TIF"
],
"imageResolution": [10]
},
"name": "<string>",
"description": "<string>"
}
)
# Wait for the job to terminate
satellite_job = satellite_job_poller.result()
job_status = satellite_job_poller.status()
Get Ingested Satellite Scenes
Querying for the scenes created by the job in the previous example.
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
from datetime import datetime
credential = DefaultAzureCredential()
client = FarmBeatsClient(endpoint="https://<my-account-name>.farmbeats.azure.net", credential=credential)
party_id = "party-1"
boundary_id = "boundary-1"
scenes = client.scenes.list(
party_id=party_id,
boundary_id=boundary_id,
start_date_time=start_date_time,
end_date_time=end_date_time,
provider="Microsoft",
source="Sentinel_2_L2A"
)
for scene in scenes:
bands = [image_file["name"] for image_file in scene["imageFiles"]]
bands_str = ", ".join(bands)
print(f"Scene has the bands {bands_str}")
Troubleshooting
General
The FarmBeats client will raise exceptions defined in [Azure Core][azure_core] if you call .raise_for_status() on your responses.
Logging
This library uses the standard
logging library for logging.
Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO
level.
Detailed DEBUG level logging, including request/response bodies and unredacted
headers, can be enabled on a client with the logging_enable keyword argument:
import sys
import logging
from azure.identity import DefaultAzureCredential
from azure.agrifood.farming import FarmBeatsClient
# Create a logger for the 'azure' SDK
logger = logging.getLogger('azure')
logger.setLevel(logging.DEBUG)
# Configure a console output
handler = logging.StreamHandler(stream=sys.stdout)
logger.addHandler(handler)
endpoint = "https://<my-account-name>.farmbeats.azure.net"
credential = DefaultAzureCredential()
# This client will log detailed information about its HTTP sessions, at DEBUG level
client = FarmBeatsClient(endpoint=endpoint, credential=credential, logging_enable=True)
Similarly, logging_enable can enable detailed logging for a single call,
even when it isn't enabled for the client:
client.crops.get(crop_id="crop_id", logging_enable=True)
Next steps
Additional documentation
For more extensive documentation on the FarmBeats, see the FarmBeats documentation on docs.microsoft.com.
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
Release History
1.0.0b2 (2023-02-23)
Features Added
Adding clients for Sensor Integration which includes crud operations on DeviceDataModels, Devices, SensorDataModels, Sensors, SensorMappings, SensorPartnerIntegration and get Sensor events.
Adding new APIs for STAC search and get feature
Adding breedingMethods and Measurements as part of Crop Entity
Adding geographicIdentifier as part of Season Entity
Adding trait, relativeMeasurements and treatments as part of CropVariety Entity
Adding type, crs, centroid and bbox(bounding box of the geometry) as part of Boundary Entity
Adding Source field in Farmer, Farm, Field, Seasonal Field, Boundary, Crop, Crop variety, Season and Attachment
CreatedBy and ModifiedBy in all entities
Measure renamed to measurements in Prescription & Crop
Acreage renamed to area in Boundary
Get Feature and Search Feature APIs for Sentinel 2 L2A and Sentinel 2 L1C STAC collections
Adding Weather Data APIs to fetch IBM weather data
Breaking Changes
Removing primaryBoundaryId & boundaryIds from Field and Seasonal Field
Removing isPrimary flag from Boundary
Removing avgYields from Seasonal Field
Renaming Farmer to Party
Renaming CropVariety to CropProduct
Updated dependency from azure-core<2.0.0,>=1.2.2 to azure-core<2.0.0,>=1.24.0
Other Changes
Python 2.7 is no longer supported. Please use Python version 3.6 or later.
1.0.0b1 (2021-05-25)
This is the initial release of the Azure AgriFood Farming library.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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