Quick Reference

Block types

Block	Purpose
Data Source	Load data into the pipeline
Python	Process data with Python
R	Process data with R
Output	Save a result into FlaskTrack

Data source types

Source	Use
Datalake Dataset	Existing FlaskTrack Data Studio dataset
Flight SQL	Custom read-only SQL query
Saved Report	Existing saved Data Studio report
FlaskTrack File	Existing organization file

Port types

Type	Use
Arrow Table	Tabular data
JSON	Structured values
File	File artifacts

Python helpers

import flasktrack as ft

Read:

ft.input_table("name")
ft.input_json("name")
ft.input_file("name")

Write:

ft.output_table("name", value)
ft.output_json("name", value)
ft.output_parquet("name", value)
ft.output_file("name", path, content_type="...")

Log:

ft.log("message")
ft.log("message", level="warning")

R helpers

source("/opt/flasktrack/flasktrack.R")

Read:

ft_input_table("name")
ft_input_json("name")
ft_input_file("name")

Write:

ft_output_table("name", value)
ft_output_json("name", value)
ft_output_parquet("name", value)
ft_output_file("name", path, "content/type")

Log:

ft_log("message")
ft_log("message", "warning")

Pipeline lifecycle

Create
  │
  ▼
Draft
  │
  ▼
Validate & Publish
  │
  ▼
Published
  │
  ▼
Run

To make later changes:

Published
   │
   ▼
New Draft
   │
   ▼
Edit
   │
   ▼
Publish New Version

Run lifecycle

Queued → Running → Succeeded
                 ├→ Failed
                 └→ Cancelled