Open and Read Tableau .hyper Extract Files

What is a .hyper file and where does it come from

Tableau introduced the .hyper extract format in 2018 (Tableau 10.5) to replace legacy .tde (Tableau Data Extract) files, and dropped .tde support after Tableau Desktop 2024.2 (versions 2024.3 and later support .hyper only, as of October 2026). A .hyper file is a compressed local database file that stores snapshots of tables, column types, and pre-materialized calculations so workbooks can run offline without a paid Tableau Creator seat ($75 per user/month, billed annually) or a local Tableau Desktop Free Edition install.

You will usually encounter a .hyper file in one of two ways:

1. Bundled inside a .twbx file: Inside the ZIP archive of a .twbx packaged workbook, under Data/ or Data/Extracts/*.hyper.
2. Downloaded as a standalone .hyper or .tdsx file: Exported from Tableau Server, Tableau Cloud, or Tableau Prep, where a .tdsx packaged data source is a ZIP archive containing the .tds definition and local .hyper extract files.

Method 1: Open a packaged .twbx workbook in your browser with xmetric

If your .hyper extract lives inside a .twbx workbook, you can look at the workbook's schema and calculation layer immediately in your browser:

1. Drop the .twbx file into the box at the top of this page.
2. xmetric's workbook inspector reads the .twbx locally in your browser and lists every data source, sheet, dashboard, calculated field, and formula (including broken or unused calculations), and lets you save the packaged data files.
3. Open the same .twbx in the xmetric app to drag dimensions and measures from the packaged extract onto Rows and Columns. Not every dashboard will look identical to Tableau.
4. Test Level of Detail (FIXED, INCLUDE, EXCLUDE) expressions and table calculations on sample data in the formula playground.
5. Your workbook and packaged files stay on your device; nothing is uploaded unless you save a workbook online.

Translating extract-level calculations to SQL

Many .twbx workbooks include calculated fields layered on top of the .hyper extract columns. The inspector shows the Tableau formula; here it is next to the equivalent SQL query:

// Tableau Formula on Extract: Repeat Customer Flag
IIF({ FIXED [Customer ID] : COUNTD([Order ID]) } > 1, "Repeat", "One-Time")

Equivalent SQL query on the extract table:

SELECT
  customer_id,
  order_id,
  CASE
    WHEN COUNT(DISTINCT order_id) OVER (PARTITION BY customer_id) > 1
    THEN 'Repeat'
    ELSE 'One-Time'
  END AS repeat_customer_flag
FROM "Extract"."Extract";

Method 2: Convert a standalone .hyper file to CSV with Python

If you have a bare .hyper file outside of a .twbx workbook (or if you unzipped a .twbx or .tdsx archive), you can list its schemas, tables, and rows using Salesforce's official tableauhyperapi Python package on Windows, macOS, or Linux:

pip install tableauhyperapi

Run this script to inspect every table inside "Extract" and export it to a standard CSV file:

import csv
from tableauhyperapi import HyperProcess, Telemetry, Connection

hyper_path = "Data/Extracts/sales_extract.hyper"

with HyperProcess(telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU) as hyper:
    with Connection(endpoint=hyper.endpoint, database=hyper_path) as connection:
        for schema in connection.catalog.get_schema_names():
            for table in connection.catalog.get_table_names(schema):
                table_def = connection.catalog.get_table_definition(table)
                columns = [col.name.unescaped for col in table_def.columns]
                print(f"Found table {table} with columns: {columns}")

                out_csv = f"{table.name.unescaped}.csv"
                with open(out_csv, "w", newline="", encoding="utf-8") as f:
                    writer = csv.writer(f)
                    writer.writerow(columns)
                    with connection.execute_query(f"SELECT * FROM {table}") as result:
                        writer.writerows(result)

Once exported to CSV, import the file in the xmetric app to pivot and chart it on shelves in your browser without uploading your data. The app also opens Excel and Parquet files.