fabric-cli-pipeline

name	fabric-cli-pipeline
description	Fabric CLI data pipeline operations — list, create, run with parameters, monitor, schedule, cancel, export, and import DataPipeline items. Use when working with .DataPipeline items via the fab CLI.
allowed-tools	Bash(uv run *), Bash(fab *), Bash(cat *), Bash(grep *), Read, Write, Edit, Glob
user-invocable	false
metadata	{"author":"accelerate-data"}

Fabric CLI — Pipeline Operations

Complete reference for managing and executing data pipelines via fab CLI.

Execution Pattern

uv run --env-file .env fab <command>

List Pipelines

# All items in workspace (pipelines have .DataPipeline extension)
uv run --env-file .env fab ls ws1.Workspace

# Detailed listing
uv run --env-file .env fab ls ws1.Workspace -l

# Filter to pipelines only
uv run --env-file .env fab ls ws1.Workspace -q "[?contains(name, 'DataPipeline')]"

Check Existence

uv run --env-file .env fab exists ws1.Workspace/pip1.DataPipeline

Get Pipeline Details

uv run --env-file .env fab get ws1.Workspace/pip1.DataPipeline
uv run --env-file .env fab get ws1.Workspace/pip1.DataPipeline -v
uv run --env-file .env fab get ws1.Workspace/pip1.DataPipeline -q displayName

Create a Pipeline

uv run --env-file .env fab create ws1.Workspace/pip1.DataPipeline

Rename a Pipeline

uv run --env-file .env fab set ws1.Workspace/pip1.DataPipeline -q displayName -i "New Pipeline Name"

Delete a Pipeline

# With confirmation
uv run --env-file .env fab rm ws1.Workspace/pip1.DataPipeline

# Force
uv run --env-file .env fab rm ws1.Workspace/pip1.DataPipeline -f

Run a Pipeline

Synchronous (waits for completion)

# Basic run
uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline

# With timeout (seconds)
uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline --timeout 300

Asynchronous (fire and forget)

uv run --env-file .env fab job start ws1.Workspace/pip1.DataPipeline

With Parameters (-P)

Pass pipeline parameters using param_name:type=value format:

uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline -P string_param:string=hello,int_param:int=42

Supported parameter types: string, int, float, bool, object, array, secureString

Complex types (object, array):

# Object parameter
uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline -P 'obj_param:object={"key":{"nested_key":2}}'

# Array parameter
uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline -P 'array_param:array=[1,2,3]'

# Combined
uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline -P 'obj_param:object={"key":{"nested_key":2}},array_param:array=[1,2,3]'

With Raw JSON Input (-i)

For full control over the request body:

# Inline JSON
uv run --env-file .env fab job start ws1.Workspace/pip1.DataPipeline -i '{"parameters": {"string_param": "value"}}'

# From file
uv run --env-file .env fab job start ws1.Workspace/pip1.DataPipeline -i ./pipeline_params.json

Pipeline input JSON format:

{
  "parameters": {
    "string_param": "value",
    "int_param": 42,
    "obj_param": {"key": "value"},
    "array_param": [1, 2, 3]
  }
}

Monitor Pipeline Runs

List Runs

# All runs
uv run --env-file .env fab job run-list ws1.Workspace/pip1.DataPipeline

# Scheduled runs
uv run --env-file .env fab job run-list ws1.Workspace/pip1.DataPipeline --schedule

Check Run Status

uv run --env-file .env fab job run-status ws1.Workspace/pip1.DataPipeline --id <run_id>

Cancel a Run

uv run --env-file .env fab job run-cancel ws1.Workspace/pip1.DataPipeline --id <run_id>

Schedule Pipeline Runs

Create a Schedule

# Cron — every 30 minutes
uv run --env-file .env fab job run-sch ws1.Workspace/pip1.DataPipeline --type cron --interval 30

# Daily — at 06:00 and 18:00
uv run --env-file .env fab job run-sch ws1.Workspace/pip1.DataPipeline --type daily --interval 06:00,18:00

# Weekly — Monday, Wednesday, Friday at 08:00
uv run --env-file .env fab job run-sch ws1.Workspace/pip1.DataPipeline --type weekly --interval 08:00 --days Monday,Wednesday,Friday

# With date range
uv run --env-file .env fab job run-sch ws1.Workspace/pip1.DataPipeline --type daily --interval 06:00 --start 2026-04-01T06:00:00 --end 2026-07-01T00:00:00

Update a Schedule

# Disable
uv run --env-file .env fab job run-update ws1.Workspace/pip1.DataPipeline --id <schedule_id> --disable

# Enable
uv run --env-file .env fab job run-update ws1.Workspace/pip1.DataPipeline --id <schedule_id> --enable

Schedule Flags

Flag	Purpose	Example
--type	Schedule type	cron, daily, weekly
--interval	Frequency or time(s)	30 (minutes) or 06:00,18:00
--days	Days of week (weekly only)	Monday,Wednesday,Friday
--start	Start date (UTC)	2026-04-01T06:00:00
--end	End date (UTC)	2026-07-01T00:00:00
--enable	Enable schedule	—
--disable	Disable schedule	—
--id	Schedule ID (for update)	<guid>

Delete a Schedule

# With confirmation
uv run --env-file .env fab job run-rm ws1.Workspace/pip1.DataPipeline --id <schedule_id>

# Force delete
uv run --env-file .env fab job run-rm ws1.Workspace/pip1.DataPipeline --id <schedule_id> -f

Configure Timeout Behavior

By default, job run cancels the pipeline on timeout. To change:

uv run --env-file .env fab config set job_cancel_ontimeout false

Custom Polling Interval

uv run --env-file .env fab job run ws1.Workspace/pip1.DataPipeline --polling_interval 10

Export / Import

# Export pipeline definition
uv run --env-file .env fab export ws1.Workspace/pip1.DataPipeline -o /tmp/exports

# Export with force (skip sensitivity label, overwrite existing)
uv run --env-file .env fab export ws1.Workspace/pip1.DataPipeline -o /tmp/exports -f

# Import pipeline definition (creates or updates)
uv run --env-file .env fab import ws1.Workspace/pip1_imported.DataPipeline -i /tmp/exports/pip1.DataPipeline

# Import with force
uv run --env-file .env fab import ws1.Workspace/pip1.DataPipeline -i /tmp/exports/pip1.DataPipeline -f

Copy / Move

# Copy
uv run --env-file .env fab cp ws1.Workspace/pip1.DataPipeline ws2.Workspace/pip1_copy.DataPipeline

# Move
uv run --env-file .env fab mv ws1.Workspace/pip1.DataPipeline ws2.Workspace

Open in Browser

uv run --env-file .env fab open ws1.Workspace/pip1.DataPipeline

Parameter Type Reference

Type	Format	Example
string	name:string=value	env:string=prod
int	name:int=value	batch_size:int=1000
float	name:float=value	threshold:float=0.95
bool	name:bool=value	dry_run:bool=true
object	name:object={...}	config:object={"key":"val"}
array	name:array=[...]	ids:array=[1,2,3]
secureString	name:secureString=value	token:secureString=abc123

Pipeline Definition Structure

When exported, a pipeline definition contains:

• .platform file — metadata with type and displayName
• pipeline-content.json — activities array defining the pipeline steps

Important: The output directory (-o path) must already exist — fab export will not create it. Run mkdir -p /path first.

For notebook execution activities, use TridentNotebook type with notebookId and workspaceId in typeProperties.

Practical Tips

• run-status limitation: job run-status only returns pass/fail — no error details. Check Fabric UI or OneLake logs for failure debugging.
• Get pipeline ID: uv run --env-file .env fab get ws1.Workspace/pip1.DataPipeline -f -q "id"
• Create empty then import: Use fab mkdir to create, then fab import -f to overwrite with definition.

Common Issues

Issue	Fix
Parameters not applied	Use -P param:type=value format — type is required
Complex JSON escaping	Use -i ./file.json instead of inline JSON
Pipeline timeout	Increase --timeout or use async job start
Schedule not triggering	Check --enable flag and date range (--start/--end)
ERROR_WORKSPACE_NOT_FOUND	Verify workspace name and .Workspace extension
Cancel fails	Ensure you have the correct --id from job run-list