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AEPP Command Line Interface (CLI)

The AEPP Command Line Interface (CLI) is a powerful tool that allows developers to interact with the Adobe Experience Platform directly from their terminal. This guide provides an overview of the CLI commands and how to use them effectively.

Table of content

Menu

Installation

This package can be accessible directly after installing the AEPP SDK. To install the SDK, follow the instructions in the Getting Started Guide.
I provide a guide to get started with the CLI, see the getting started with the CLI section.

Initializing the CLI

To start using the CLI, you need to initialize it in your terminal. You can do this by running the following command:

python -m aepp.cli

At the start of your instantiation, you can provide optional parameters that would be used to directly connect to your Adobe Experience Platform instance. These parameters include:

  • --client-id or -cid : Your Adobe I/O Client ID
  • --secret or -s : Your Adobe I/O Client Secret
  • --org-id or -o : Your Adobe I/O Organization ID
  • --sandbox or -sx : Your Adobe I/O Sandbox name
  • --scopes or -sc : Your Adobe I/O Scopes (comma-separated if multiple)
  • --region or -r : The region of your Adobe Experience Platform instance (default is 'nld2'). Available regions are: "va7", "aus5", "can2", "ind2".
  • --config-file or -cf : Path to a JSON configuration file containing connection parameters.
  • --command or -cmd : Run a single CLI command non-interactively and exit immediately after. The value is a string containing the command name followed by its arguments, using the same syntax as the interactive prompt. This is useful for scripting or automation workflows.

Non-interactive mode examples

The -cmd flag lets you connect to AEP and execute one command in a single call, without entering the interactive shell. The command string follows the exact same syntax as the interactive prompt.

# List all schemas in the prod sandbox, filtered by "client"
python -m aepp.cli -cf config_api.json -sx prod -cmd "get_schemas -f client"

# Export all datasets to CSV from the dev sandbox
python -m aepp.cli -cf config_api.json -sx dev -cmd "get_datasets"

# List all audiences filtered by name and save them
python -m aepp.cli -cf config_api.json -sx prod -cmd "get_audiences -f loyalty"

# Get all identities from a specific region
python -m aepp.cli -cf config_api.json -sx prod -cmd "get_identities -r va7"

# Export a specific schema as a CSV file
python -m aepp.cli -cf config_api.json -sx prod -cmd "get_schema_csv _tenant.schemas.abc123"

Note: Any command available in the interactive shell can be used with -cmd. The arguments accepted by each command are the same as described in the Available Commands section below.

Available Commands

The CLI provides a variety of commands to manage and interact with Adobe Experience Platform resources. Below is a list of available commands:

Configs

create_config_file

Generate a JSON configuration file with your connection parameters for future use.
Arguments:

  • -fn, --file_name : File name for your config file (default: "aepp_config.json")

config

In case you did not provide the connection parameters at the start of the CLI, you can use this command to set up your connection configuration. Parameters:

  • --client-id or -cid : Your Adobe I/O Client ID
  • --secret or -s : Your Adobe I/O Client Secret
  • --org-id or -o : Your Adobe I/O Organization ID
  • --sandbox or -sx : Your Adobe I/O Sandbox name
  • --scopes or -sc : Your Adobe I/O Scopes (comma-separated if multiple)
  • --region or -r : The region of your Adobe Experience Platform instance (default is 'nld2'). Available regions are: "va7", "aus5", "can2", "ind2".
  • --config-file or -cf : Path to a JSON configuration file containing connection parameters.

change_sandbox

Switch the active sandbox session after initial configuration.
Arguments:

  • sandbox : The name of the sandbox to switch to.

The command first tries to validate the sandbox name against the list returned by the Sandboxes API. If that API is not accessible with your current credentials (e.g. your service account lacks the "Manage Sandboxes" permission), a yellow warning is shown and the switch proceeds unvalidated instead of being blocked.

get_sandboxes

List all sandboxes available in the current organization.

create_sandbox

Create a new sandbox in the current organization.
Arguments:

  • -n, --name : Name for the new sandbox. It must be unique and not contain spaces (use - instead of space).
  • -t, --type : Type for the new sandbox. Possible values: [development, production].
  • -tl, --title : Title for the new sandbox.

Schema Methods

get_schemas

List all schemas in the current sandbox.
Arguments:

  • -sv, --save : Save the list of schemas to a CSV file.
  • -f, --filter: filter the schema returned based on title and on lower case and partial match of that string

get_classes

List all classes in the current sandbox.
Arguments:

  • -sv, --save : Save the list of classes to a CSV file.
  • -f, --filter: filter the classes returned based on title and on lower case and partial match of that string

get_ups_schemas

List all schemas enabled for Unified Profile in the current sandbox.
Arguments:

  • -sv, --save : Save the list of enabled schemas to a CSV file.

get_profile_schemas

Get schemas specifically filtered for the Profile class (https://ns.adobe.com/xdm/context/profile).\

get_event_schemas

Get schemas specifically filtered for the Experience Event class (https://ns.adobe.com/xdm/context/experienceevent).\ Arguments:

  • -sv, --save : Save the list of event schemas to a CSV file.

get_schema_xdm

Get the raw JSON (XDM) definition of a specific schema.
Arguments:

  • schema : The Schema Title, $id, or alt:Id.
  • -f, --full : Boolean. Get full schema details (default: False, possible values: True, False).

get_schema_csv

Get the structure of a specific schema exported as a CSV file.
Arguments:

  • schema : The Schema $id or alt:Id.
  • -f, --full : Boolean. Get full schema details (default: False, possible values: True, False).

get_schema_json

Get the JSON representation of a specific schema manager object.
Arguments:

  • schema : The Schema $id or alt:Id.

enable_schema_for_ups

Enable a specific schema for the Unified Profile Service.
Arguments:

  • schema_id : The Schema ID to enable.

get_union_profile_json

Export the current Profile Union Schema to a JSON file.

get_union_profile_csv

Export the current Profile Union Schema to a CSV file.
Arguments:

  • -f, --full : Boolean. Get full schema information (default: False, possible values: True, False).

get_union_event_json

Export the current Experience Event Union Schema to a JSON file.

get_union_event_csv

Export the current Experience Event Union Schema to a CSV file.
Arguments:

  • -f, --full : Boolean. Get full schema information (default: False, possible values: True, False).

get_fieldgroups

List all field groups in the current sandbox.
Arguments:

  • -ootb, --ootb : Boolean. Include out-of-the-box field groups (default: False, possible values: True, False).
  • -f, --filter : Filter the field groups based on the string.
  • -sv, --save : Save the list of field groups to a CSV file.

get_ups_fieldgroups

List all field groups enabled for Profile in the current sandbox.
Arguments:

  • -sv, --save : Save the list of enabled field groups to a CSV file.

get_fieldgroup_json

Get the JSON definition of a specific field group.
Arguments:

  • fieldgroup : Field Group Name, $id, or alt:Id.

get_fieldgroup_csv

Get the structure of a specific field group exported as a CSV file.
Arguments:

  • fieldgroup : Field Group Name, $id, or alt:Id.
  • -f, --full : Boolean. Get full field group details (default: False, possible values: True, False).

get_fieldgroup_xdm

Get the XDM definition of a specific field group exported as a JSON file.
Arguments:

  • fieldgroup : Field Group Name, $id, or alt:Id.

delete_fieldgroup

Delete a field group from the current sandbox.
Arguments:

  • fieldgroup : Field Group Name, $id, or alt:Id to delete.

upload_fieldgroup_definition_csv

Create or Update a field group using a CSV definition file.
Arguments:

  • csv_path : Path to the CSV file.
  • -ts, --test : Boolean. Test the upload locally without sending to AEP (default: False, possible values: True, False).

create_fieldgroup_definition_template

Create a CSV template for defining a field group.
Arguments:

  • -tl, --title : Name of the field group (default: "MyFieldGroup").
  • -d, --description : Description of the field group (default: "").
  • -fn, --file_name : Name of the output CSV file (default: None).

upload_fieldgroup_definition_xdm

Create or Update a field group using a JSON XDM file.
Arguments:

  • xdm_path : Path to the JSON file.
  • -ts, --test : Boolean. Test the upload locally without sending to AEP (default: False, possible values: True, False).

upload_fieldgroup_definition_xlsx

Create or Update a field group using an Excel XLSX file.
Arguments:

  • xlsx_path : Path to the XLSX file.
  • -sh, --sheet : Name of the sheet in the XLSX file to use (default: "Sheet1").
  • -ts, --test : Boolean. Test the upload locally without sending to AEP (default: False, possible values: True, False).

get_descriptors

List all descriptors in the current sandbox.
Arguments:

  • -sv, --save : Save the list of descriptors to a CSV file.

get_descriptor

Display the JSON definition of a specific descriptor in the current sandbox.
Arguments:

  • descriptor_id : Required descriptor ID (@id).
  • -sv, --save : Also save the definition to descriptor_<descriptor_id>.json.

get_datatypes

List all data types in the current sandbox.\

get_datatype_csv

Export a specific Data Type structure to a CSV file.
Arguments:

  • datatype : Data Type Name, $id, or alt:Id.
  • -f, --full : Boolean. Get full details (default: False, possible values: True, False).

get_datatype_json

Export a specific Data Type definition to a JSON file.
Arguments:

  • datatype : Data Type Name, $id, or alt:Id.

get_datatype_xdm

Export a specific Data Type XDM definition to a JSON file.
Arguments:

  • datatype : Data Type Name, $id, or alt:Id.

create_b2b_artifacts

Create the B2B identities and schema and relationship for the current sandbox.
combination of createB2BIdentities in the identity module and createB2Bschemas in schema module.

Dataset Methods

get_datasets

List all datasets in the current sandbox.
Also save the result in a CSV file.\

  • -f, --filter: filter the dataset returned based name and on lower case and partial match of that string

get_dataset

Display a single dataset's JSON definition and save it to dataset_<dataset_id>.json.
Arguments:

  • dataset : Required Dataset ID or exact, case-sensitive Dataset Name. Quote names containing spaces.

Example:

prod> get_dataset "Customer events"

get_datasets_infos

List all datasets with detailed storage and row count statistics.

do_get_datasets_tableNames

Get the table names associated with dataset names and ID. Arguments:

  • -f, --filter: filter the dataset returned based name and on lower case and partial match of that string

get_observable_schema_json

Retrieve the observable schema JSON for a specific dataset.
Arguments:

  • dataset : The Dataset ID or Name.

get_observable_schema_csv

Retrieve the observable schema CSV for a specific dataset.
Arguments:

  • dataset : The Dataset ID or Name.

get_snapshot_datasets

Get the list of snapshot datasets in the current sandbox.\

get_dataset_expiration

Get the TTL (Time To Live) / rowExpiration setting for a dataset. ONLY WORKS ON Experience Event Datasets.
Arguments:

  • dataset : The Dataset ID or Name.

set_dataset_expiration

Set the TTL (Time To Live) / rowExpiration setting for a dataset. ONLY WORKS ON Experience Event Datasets.
Arguments:

  • dataset : The Dataset ID or Name.
  • -t, --ttl : TTL value in days.

createDataset

Create a new dataset.
Arguments:

  • dataset_name : The name for the new dataset.
  • schema_id : The Schema ID to associate with the dataset.

enable_dataset_for_ups

Enable a specific dataset for the Unified Profile Service.
Arguments:

  • dataset : The Dataset ID or Name.

Audience Methods

get_audiences

List all audiences in the current sandbox. If the getAudiences method fails, it will fallback to getSegments method, which might not include external audiences.
The result will be saved in a CSV with more information than what is being displayed in the terminal. Arguments:

  • -f, --filter: filter the audience returned based name and on lower case and partial match of that string

The results displayed in the Terminal will have the following columns:

  • ID : Audience ID
  • Name : Audience Name
  • Evaluation : Evaluation Method, Batch, Streaming or Edge
  • Total Profiles : The total profile of that audience if available
  • In Flow : If the audience has been shared (True or False)
  • Active in Flow : If the audience expiration date for actively being shared is below today (True or False)

create_audiences_job

Create a job for audience segmentation. Only 50 jobs available per year for production sandboxes. Arguments:

  • audience_ids : list of audience IDs such as "audienceId1" "audienceId2" "audienceId3"

flexible_audience_evaluation

Trigger an on-demand evaluation job for one or more specific audiences, outside of the regular batch schedule. This is useful when you need to refresh audience membership immediately without waiting for the next scheduled batch run.
Arguments:

  • audience_ids : One or more audience IDs to evaluate. Pass them space-separated, e.g. "audienceId1" "audienceId2".

Example:

# Evaluate a single audience
flexible_audience_evaluation "a1b2c3d4-0000-0000-0000-111111111111"

# Evaluate multiple audiences at once
flexible_audience_evaluation "a1b2c3d4-0000-0000-0000-111111111111" "e5f6a7b8-0000-0000-0000-222222222222"

# Non-interactive mode
python -m aepp.cli -cf config_api.json -sx prod -cmd "flexible_audience_evaluation \"a1b2c3d4-0000-0000-0000-111111111111\""

get_batch_evaluation

Retrieve the current batch segmentation job definition for the sandbox, including its cron schedule and status.
No arguments.

update_batch_evaluation_time

Update the cron schedule that controls when the daily batch segmentation job runs for the current sandbox. The schedule uses the standard six-field cron format: seconds minutes hours day-of-month month day-of-week.
Arguments:

  • schedule : The cron expression to apply. Example: "0 0 1 * * ?" runs the job daily at 01:00 UTC.

Example:

# Run batch segmentation daily at 01:00 UTC
update_batch_evaluation_time "0 0 1 * * ?"

# Run batch segmentation daily at 03:30 UTC
update_batch_evaluation_time "0 30 3 * * ?"

# Non-interactive mode
python -m aepp.cli -cf config_api.json -sx prod -cmd "update_batch_evaluation_time \"0 0 1 * * ?\""
extract_audience_paths

Get the list of paths used in audience definitions.
Arguments:

  • audience : Audience ID or audience name to get paths for.
  • -r, --recursive : Boolean. Get paths recursively from segment references. Default False. Possible values: True, False.
extract_audience_ref

Get the list of audience references used in audience definitions.
Arguments:

  • audience : Audience ID or audience name to get references for.

Flow Service

create_dataset_http_source

Create an HTTP streaming endpoint for a specific dataset.
Arguments:

  • dataset : Name or ID of the Dataset.

get_DLZ_credential

Get Data Lake Zone credentials for the current sandbox.
Arguments:

  • type : (Optional) Credential type: 'user_drop_zone' (default) or 'dlz_destination'.

get_flows

List flows in the sandbox. Supports filtering by source/destination and time. Default last 24h.
Arguments:

  • -i, --internal_flows : Include internal flows (default: False).
  • -t, --type : Filter by flow type (source, destination, internal, all).
  • -adv, --advanced : Fetch run metrics (success/fail rates) (default: False).
  • -ao, --active_only : List only flows active in the time period (default: True).
  • -mn, --minutes : Lookback window in minutes (default: 0).
  • -H, --hours : Lookback window in hours (default: 0).
  • -d, --days : Lookback window in days (default: 0).

get_flow_errors

Export failed run details for a specific flow to a JSON file Default is last 24h.
Arguments:

  • flow_id : The Flow ID.
  • -mn, --minutes : Lookback window in minutes.
  • -H, --hours : Lookback window in hours.
  • -d, --days : Lookback window in days (default: 0).

Deletion Methods

These commands wrap the deletion module to let you remove artifacts directly from the sandbox you are connected to.
Every command resolves the artifact by name or ID, prints a warning panel describing exactly what will be impacted (and, when --associated_artifacts is used, a Summary line totaling every artifact that will be deleted across the full cascade), and requires you to type the artifact's name back to confirm before anything is deleted. Pass -y true to skip the confirmation prompt (useful for scripting).
These operations are irreversible.

delete_dataset

Delete a dataset from the current sandbox.
Arguments:

  • dataset : Dataset name or ID to delete.
  • -a, --associated_artifacts : Boolean. Also delete the associated dataflows and schema (which itself cascades to that schema's field groups and data types). Default False.
  • -y, --yes : Boolean. Skip the confirmation prompt. Default False.

delete_schema

Delete a schema from the current sandbox.
Arguments:

  • schema : Schema title, $id, or alt:Id to delete.
  • -a, --associated_artifacts : Boolean. Also delete the field groups and data types used by this schema. Default False.
  • -y, --yes : Boolean. Skip the confirmation prompt. Default False.

delete_dataflow

Delete a dataflow from the current sandbox.
Arguments:

  • flow : Dataflow name or ID to delete.
  • -a, --associated_artifacts : Boolean. Also delete the associated source and target connections. Default False.
  • -y, --yes : Boolean. Skip the confirmation prompt. Default False.

delete_audience

Delete an audience/segment from the current sandbox.
If the audience is activated to any destination, it is first removed from those destination flows (shown in an "Impacted Destination Flows" table) before being deleted.
Arguments:

  • audience : Audience name or ID to delete.
  • -w, --waittime : Seconds to wait for destination flow updates to propagate before deleting. Default 30.
  • -y, --yes : Boolean. Skip the confirmation prompt. Default False.

Example:

# Delete a dataset only (leave its schema and dataflows untouched)
delete_dataset "my_dataset_name"

# Delete a dataset and cascade to its dataflows and schema
delete_dataset "my_dataset_name" -a true

# Delete a schema and its field groups/data types without being prompted
delete_schema "_tenant.schemas.abc123" -a true -y true

# Non-interactive mode
python -m aepp.cli -cf config_api.json -sx dev -cmd "delete_audience \"my_audience_name\" -y true"

Identities Methods

get_identities

List all identities in the current sandbox.
Arguments:

  • -r, --region : Region code (e.g., 'ndl2', 'va7', 'aus5'. Default: 'ndl2').
  • -co, --custom_only : Boolean. List only custom namespaces (default: False, possible values: True, False).

create_identity

Create a new identity namespace.
Arguments:

  • -c,--code : Code for the new identity namespace (e.g., crmId, uid)
  • -n,--name : Display name for the new identity namespace
  • -t,--type : Type for the new identity namespace. Possible Values: COOKIE, CROSS_DEVICE, DEVICE, EMAIL, MOBILE, NON_PEOPLE or PHONE
  • -d,--description : Description for the new identity namespace

Query Service Methods

All Query Service commands require an active sandbox connection. Run help <command> for a summary or <command> -h for its arguments.

get_queries

Retrieve up to 1000 queries from the last 24 hours (configurable), keep queries from the Query Service UI and Generic PostgreSQL clients, display the first 10, and export them to <sandbox>_queries.csv.
Arguments:

  • -ds, --dataset : Filter by Dataset ID.
  • -st, --state : Filter by API state: SUBMITTED, IN_PROGRESS, SUCCESS, FAILED, KILLED, or TIMEOUT (case-insensitive). Aliases running, completed, and failed are also accepted.
  • -mn, --minutes : Non-negative lookback window in minutes.
  • -H, --hours : Non-negative lookback window in hours.
  • -d, --days : Non-negative lookback window in days.

The three lookback options are added together. If all are zero or omitted, the lookback is 24 hours. Time filters use UTC.

get_query

Display a query's metadata, SQL and execution state as JSON. This does not execute the query or retrieve its result rows.
Arguments:

  • query_id : Required ID of the query to retrieve.

get_query_templates

List all query templates in the current sandbox, following pagination. Displays each template's ID, name and creation date.

get_query_template

Display a query template as JSON and save it to query_template_<template_id>.json.
Arguments:

  • template_id : Required ID of the query template to retrieve.

get_queries_scheduled

List all scheduled queries in the current sandbox, following pagination, and save their full definitions to queries_scheduled_<sandbox>.json.

Displays the schedule ID, query name, start date, cron expression and activation state. The Enabled column shows True for ENABLED, False for DISABLED, and the state name for a transition such as REGISTERING.

create_query_scheduled

Create a scheduled query using either SQL or an existing query template. The query runs against <current_sandbox>:all, not a hard-coded production database.
Arguments:

  • -q, --query : SQL string. Required unless --template_id is provided.
  • -t, --template_id : Query template ID. Required unless --query is provided. The two options are mutually exclusive.
  • -sch, --schedule : Required five-field cron expression, such as "0 */2 * * *", or a shorthand: @once, @hourly, @daily, @weekly, @monthly, or @yearly.
  • -sd, --start_date : Required ISO 8601 start timestamp with a timezone, such as "2026-11-01T00:00:00Z".
  • -ed, --end_date : Optional ISO 8601 end timestamp with a timezone. Must be later than the start date.
  • -n, --name : Optional query name.
  • -d, --description : Optional query description.
  • -a, --arguments : Optional comma-separated SQL/template parameters in key1=value1,key2=value2 format. Values may contain =; commas separate parameters.

Dates are normalized to UTC before submission. Adjust the example dates before use. Adobe validates the cron expression; scheduled runs must not be more frequent than once per hour. For recurring schedules, omitting an end date depends on your organization's support for schedules without an end date.

Adobe accepts creation asynchronously and returns the schedule ID and initial state, normally REGISTERING. It automatically transitions to ENABLED after registration. There is no --enabled flag; use the commands below to change an existing schedule after registration.

Examples:

dev> create_query_scheduled -n "Daily accounts" -q "SELECT * FROM accounts" -sch "@daily" -sd "2026-11-01T00:00:00Z" -ed "2026-12-01T00:00:00Z"
dev> create_query_scheduled -n "Template run" -t template-id -a "table=accounts,minimum=10" -sch "0 */2 * * *" -sd "2026-11-01T00:00:00Z" -ed "2026-12-01T00:00:00Z"

enable_query_scheduled

Request enabling an existing query schedule.
Arguments:

  • schedule_id : Required schedule ID.

disable_query_scheduled

Request disabling an existing query schedule.
Arguments:

  • schedule_id : Required schedule ID.

Both commands report that Adobe accepted the request, not that the state change has finished. Use get_queries_scheduled to inspect the resulting state. Adobe can reject changes while a schedule is still registering or already in the requested state.

See the Query Service module documentation and Adobe's Schedules endpoint reference for API details.

query

Execute a raw SQL query against the Data Lake, save the results as CSV and display a sample.
Arguments:

  • sql_query : The SQL string to execute.
  • -fn : Optional output filename. The .csv extension is added if omitted. Defaults to query_result_<timestamp>.csv.

query_segment_population

Query the population of specific segment(s).
Arguments:

  • segment_id : Segment ID(s) to query population for. It can be multiple segment | audience IDs separated by spaces.
  • -ef, --extra_fields : Extra fields to include in the query, comma-separated.
  • -c, --count_only : If you want to get only the count of the segment population. (default: False). If set to True, the query will return only the count of profiles in the segment(s) instead of the full list.
  • -fn, --filename : If you want to save it to a specific filename.

Example:

prod> query_segment_population "segmentId1" "segmentId2" -ef "email,_tenant.fieldname" -fn "segment_population.csv"

Profile API

get_profile_attributes

Retrieve the profile attributes for a specific user, saving it in a JSON file.
Arguments:

  • -uid,--user_id : User ID of the user.
  • -ns,--namespace : Namespace of the user.

get_account_attributes

Retrieve the account attributes for a specific user, saving it in a JSON file.
Arguments:

  • -uid,--user_id : User ID of the user.
  • -ns,--namespace : Namespace of the user (default: b2b_account).

get_profile_events

Retrieve all UPS events for a specific user, saving it in a JSON file.
Arguments:

  • -uid,--user_id : User ID of the user.
  • -ns,--namespace : Namespace of the user.
  • -l, --limit : Number of events returned by the response (max 5000, default 1000)

The output in the terminal will give you an aggregated view of these different informations:

  • "eventTypes": the different types and their numbers
  • "primaryIdentities": the different primary identities used during the requests
  • "totalEvents": the total events attached to that profile
  • "firstEventTimestamp": The first event timestamp recorded of that profile
  • "lastEventTimestamp": The last event timestamp recorded of that profile

get_merge_policies

Retrieve all merge policies in the current sandbox.
Save the list of merge policies in a JSON file.

Hygiene API

get_hygiene_works

List all hygiene works in the current sandbox and save it in a JSON file.
Arguments:

  • -f, --filter: filter the works returned based name and on lower case and partial match of that string
  • -d, --days: filter the works by creation date based on a lookback window in days (default: 0, no filter)

get_hygiene_work

Get details of a specific hygiene work and save it in a JSON file.
Arguments:

  • workOrderId : The Hygiene Work ID.

Tools & Migration

extract_artifacts

Bulk extract sandbox components to a local folder.
Arguments:

  • -lf, --localfolder : Destination folder (default: ./extractions).
  • -f, --filters: filter the artifacts to extract based on name and on lower case and partial match of that string

extract_artifact

Extract a single specific artifact.
Arguments:

  • artifact : Name or ID of the artifact.
  • -at, --artifactType : Type (e.g., schema, dataset, etc.).
  • -lf, --localfolder : Destination folder.

sync

Synchronize or copy artifacts between sandboxes.
Arguments:

  • artifact : Name or ID of the component to sync.
  • -at, --artifactType : Type of component. Can be from this list: "schema","fieldgroup","datatype","descriptor","dataset","identity","mergepolicy","audience"
  • -t, --targets : list of target sandboxes.
  • -lf, --localfolder : Local staging folders.
  • -b, --baseSandbox : The source sandbox name.
  • -v, --verbose : Enable verbose logging (default: True).

Knowledge Graph

build_graph

Build a graph of all artifacts in the current sandbox and save it in memory for the session.
Arguments:

  • -hd, --has_data : Boolean. Retrieve information for all schemas and datasets. Default True.
  • -d, --detail : Boolean. Retrieve the path information for the schema and field groups. Default True.
  • -e, --enabled : Boolean. Build the knowledge graph based on enabled datasets only. Default False.
  • -ex, --export : Boolean. Export the graph to a turtle file (named <sandbox>.ttl) once built. Default False.
  • -v, --verbose : Boolean. If you want to see the progress of the graph building. Default False.

export_graph

Export the previously built graph (via build_graph) to a turtle file.
Arguments:

  • filename : Filename to export the graph to (e.g., graph.ttl).

load_graph

Load a graph from a turtle file into memory for the session.
Arguments:

  • filename : Filename to load the graph from (e.g., graph.ttl).

add_path_attributes

Add path attributes to the previously built graph. Requires a graph to have been built (build_graph) or loaded (load_graph) first.
Arguments:

  • -p, --path : Path to add the attributes to.
  • -a, --attributes : Attributes to add, in the form predicate1=value1 predicate2=value2 ....

add_schema_attributes

Add schema attributes to the previously built graph. Requires a graph to have been built (build_graph) or loaded (load_graph) first.
Arguments:

  • -s, --schema : Schema $id to add the attributes to.
  • -a, --attributes : Attributes to add, in the form predicate1=value1 predicate2=value2 ....

add_dataset_attributes

Add dataset attributes to the previously built graph. Requires a graph to have been built (build_graph) or loaded (load_graph) first.
Arguments:

  • -d, --dataset : Dataset ID to add the attributes to.
  • -a, --attributes : Attributes to add, in the form predicate1=value1 predicate2=value2 ....

Other methods

get_tags

Get the tag associated with your organization.

get_profile_attributes_lineage

Get usage details for all Profile paths.
No arguments.
This will take a long time.

get_event_attributes_lineage

Get the information details for all Experience Event paths.
No arguments. This will take a long time.

get_profile_attribute_lineage

Get usage details for a specific Profile path.
Arguments:

  • path : The Profile path to analyze.

get_event_attribute_lineage

Get usage details for a specific Experience Event path.
Arguments:

  • path : The Experience Event path to analyze.

exit

Exit the CLI.

help

Display help information about available commands.