AVD transforms

Developer Guide

Documents the transform implementations. To view artifacts as an operator, see Viewing Artifacts.

Four Python transforms turn the data produced by the two-phase pipeline into user-facing artifacts. All four are registered in .infrahub.yml.

Generated Pydantic models

The *_query.py files referenced below are generated from their matching .gql and the checked-in schema.graphql via infrahubctl graphql generate-return-types. Do not hand-edit them. See Transforms → Query Classes for the regeneration command.

Transform	Target group	Content type	Wraps
avd_eos_config	avd_devices	text/plain	pyavd.get_device_config()
avd_device_doc	avd_devices	text/markdown	PyAVD device documentation
avd_fabric_doc	fabrics	text/markdown	pyavd.get_fabric_documentation()
avd_anta_catalog	avd_devices	application/yaml	pyavd.get_device_test_catalog()

avd_eos_config

Class: AvdEosConfigTransform Source: transforms/avd_eos_config.py Query: transforms/avd_device_config.gql Pydantic model: transforms/avd_device_config_query.py

Renders a single device's Arista EOS CLI configuration.

Flow:

1. Query resolves the target device and navigates to AvdArtifact.structured_config_file.
2. Transform fetches the structured-config JSON from the AvdStructuredConfigFile (a CoreFileObject).
3. Calls pyavd.get_device_config(structured_config).
4. Returns the EOS CLI text.

If structured_config_file is missing or empty, the transform returns a user-readable "No structured config available" message rather than crashing — see Debugging the Pipeline for the diagnostic flow.

avd_device_doc

Class: AvdDeviceDocTransform Source: transforms/avd_device_doc.py Query: transforms/avd_device_config.gql (reused) Pydantic model: transforms/avd_device_config_query.py

Renders per-device markdown documentation.

Flow:

1. Same query as avd_eos_config — resolves device and its structured config.
2. Calls the PyAVD device documentation function on the structured config.
3. Returns markdown.

avd_fabric_doc

Class: AvdFabricDocTransform Source: transforms/avd_fabric_doc.py Query: transforms/avd_fabric_devices.gql Pydantic model: transforms/avd_fabric_devices_query.py

Renders fabric-wide markdown documentation covering the full topology.

Flow:

1. Query resolves the fabric and walks to every device in its pods and racks.
2. Transform fetches hostvars and structured config files for all devices.
3. Calls pyavd.get_avd_facts(all_hostvars) to build the shared facts.
4. Calls pyavd.get_fabric_documentation(avd_facts, structured_configs, fabric_name).
5. Returns markdown.

Fabric documentation requires hostvars to be present for every device in the fabric. If any device has no hostvars, the transform fails the artifact generation with a message naming the missing devices.

avd_anta_catalog

Class: AvdAntaCatalogTransform Source: transforms/avd_anta_catalog.py Query: transforms/avd_anta_catalog.gql Pydantic model: transforms/avd_anta_catalog_query.py

Renders a per-device ANTA test catalog as YAML.

Flow:

1. Query resolves the target device and every device in the graph, so siblings can be filtered by fabric in the transform. The device's fabric is pod.parent, a discriminated union — only a NetworkFabric parent has the name and anta_enabled fields the gating needs.
2. If the fabric has anta_enabled unset or false, return a marker comment and stop.
3. Download each same-fabric device's structured config, passing it through pyavd.validate_structured_config().
4. Build one AVDFabricData from all of them — catalog generation is fabric-wide, unlike EOS config rendering.
5. Call pyavd.get_device_test_catalog(hostname, target_structured_config, fabric_data) and dump it as YAML.

Every "cannot render" path returns a comment rather than raising, so the artifact always renders and states the reason:

# ANTA disabled for fabric Fabric-L3LS-Multi-Domain
# No structured config for leaf-infrahub-dc1-1
# ANTA catalog: no fabric for leaf-infrahub-dc1-1

Registration in .infrahub.yml

python_transforms:
  - name: avd_eos_config
    class_name: AvdEosConfigTransform
    file_path: "./transforms/avd_eos_config.py"
  - name: avd_fabric_doc
    class_name: AvdFabricDocTransform
    file_path: "./transforms/avd_fabric_doc.py"
  - name: avd_device_doc
    class_name: AvdDeviceDocTransform
    file_path: "./transforms/avd_device_doc.py"
  - name: avd_anta_catalog
    class_name: AvdAntaCatalogTransform
    file_path: "./transforms/avd_anta_catalog.py"

artifact_definitions:
  - name: avd_eos_configuration
    targets: avd_devices
    transformation: avd_eos_config
  - name: avd_fabric_documentation
    targets: fabrics
    transformation: avd_fabric_doc
  - name: avd_device_documentation
    targets: avd_devices
    transformation: avd_device_doc
  - name: avd_anta_catalog
    targets: avd_devices
    transformation: avd_anta_catalog
    content_type: application/yaml

Other transforms

The repository also ships transforms outside the AVD pipeline — the cabling-plan CSV, computed interface descriptions, the ContainerLab topology, and the CloudVision webhook payload. They are documented in Transforms.

Adding a new transform

See Extending the Pipeline → Adding a new transform output.