Examples#

This directory contains examples of how to use the SDA library.

Data Loading#

``load_single_file_io.py`` - Load a single test file with sda.io.load.loadany(). The same data can be visualized with the fplot command (e.g. fplot path/to/file.txt or drag-and-drop in the fplot GUI).
``load_tests.py`` - Simple example of loading specific tests locally
``load_test_cloud.py`` - Example of loading a single test data file directly from the Cloud (SharePoint)
``load_tests_cloud.py`` - Example of discovering and loading multiple tests from the Cloud (SharePoint)

Utilities#

``list_all_experiment_files.py`` - Discover and print information about all available data files on this machine

Performance Analysis#

``database_report_analysis.py`` - Comprehensive test data analysis script: - Analyzes ALL available test data on the machine - STT template tracking and compliance metrics - Visual quality thermometer with progress bars - Performance metrics (parsing speed, file sizes) - Enhanced Excel reports with native tables

python examples/database_report_analysis.py

CLI Usage#

The sda command-line tool can inspect column names across test files without loading any data using show-columns.

# List all unique column names across every test file (sorted, no duplicates)
sda show-columns *

# Columns from a single test
sda show-columns T297

# Columns from all T2xx tests (union, deduplicated)
sda show-columns T2*

# Find the exact column name(s) containing "torche" — useful to build a filter afterwards
sda show-columns * --columns torche
# e.g. outputs: "torche"  → then narrow down rows with:
# sda print T083 --filter 'torche="T8-Face"'

# Search for the word "lensing" through all column names across all tests
sda show-columns * | grep -i lensing