Tableau Dashboard Profiler is your secret agent for analyzing Tableau workbook files. It dives into your .twbx files and retrieves field-level details, helping you understand the structure and content of your dashboards.

Before you start, make sure you've installed the necessary Python packages. You can do this by running the following command in your terminal:

pip install -r requirements.txt

Follow these steps to analyze your Tableau workbooks:

1. Import the DashboardAnalyzer class from tableau_dashboard_profiler.py.
2. Initialize a DashboardAnalyzer instance with the path to the directory or file containing your .twbx Tableau workbooks.
3. Call the analyze method on the DashboardAnalyzer instance.
4. Optionally, provide an output path and a create_dir flag. The script will save the output CSV files in this directory. If the directory doesn't exist, setting create_dir to True will create it.
5. If you set return_concat to True when calling analyze, the method will return a DataFrame with the analysis results.

Here's an example:

from tableau_dashboard_profiler import DashboardAnalyzer

input_path = r'/path/to/your/workbooks'
output_path = r'/path/to/output/directory'

# Initialize the analyzer
analyzer = DashboardAnalyzer(input_path, output_path, create_dir=True)

# Analyze the workbooks and get a DataFrame of the results
df = analyzer.analyze(return_concat=True)

# See what the analyzer found
if df is not None:
    print(df)

The analyze method saves a CSV file for each analyzed .twbx workbook in the specified output directory. Each CSV file contains the following columns:

• 'Dashboard Name'
• 'Worksheet Name'
• 'Field Name'
• 'Field Calculation'
• 'Field Type'
• 'Field Role'
• 'Field Aggregation'

If return_concat is set to True, the analyze method also returns a DataFrame that contains all the results combined.

Happy Profiling! 🕵️‍♀️🔍📊