TabalystTOOLAvailable
Tabalyst Inspect
Finds which array, sheet or table of a JSON, JSONL or Excel file holds the records, and writes an editable file.
Tabalyst Tools
Small tools around the report.
Tabalyst Report is built on a shared engine. Tabalyst Inspect, Tabalyst Scan and Tabalyst Sample expose parts of it as commands of their own, for when you need to control how a file is read, keep a full description of its fields or work on a smaller file.
Three tools, three jobs
TOOLAvailable
Tabalyst Scan
Describes every field of a CSV, JSON, JSONL or Excel file in one JSON document. The engine behind the report.
TOOLAvailable
Tabalyst Sample
Draws a smaller CSV: first, last, random or stratified rows, reproducible with a seed.
How they fit together
Inspect, Scan and Tabalyst Report chain: each one can use the answer of the previous one. None of them is required, because the report inspects and scans a file by itself. Sample works on its own, on CSV files.
- 1 · Install
pip install tabalyst# One package: the tools share it with Tabalyst Report
- 2 · Choose the collection
tabalyst inspect orders.json# Writes orders.json-inspect.json, which you can edit
- 3 · Describe every field
tabalyst scan orders.json -o orders.scan.json# Applies the Inspect file, writes the scan document
- 4 · Build the report
tabalyst report --scan orders.scan.json# Without reading the source again
- 5 · Work on less data
tabalyst sample customers.csv --sample-method random --rows 1000 --seed 42# customers.sample.csv, the source is never modified
import tabalyst # Where are the records? Writes the Inspect file and returns itinspection = tabalyst.inspect("orders.json") # The full description of every field, one scan document per sourcescans = tabalyst.generate_scans(["orders.json"], output_dir="scans") # A reproducible sample of a CSV filesample = tabalyst.sample_csv( "customers.csv", method="random", rows=1000, seed=42,)
Next step
Where to go next
The tools are documented command by command. Every command and option is in the CLI reference.
DOCS
CLI reference
Every command, option and exit code.
DOCS
Python API reference
The public functions and their results.