Hi @boubcher, you can read the schema definition of any dataset with the Schema (Any Format) reader. Each schema feature output from the reader will have a list attribute called "attribute{}" which contains the definition of all user attributes of a feature class. The list is a structured one consisting of these three members.

• attribute{}.name: Attribute name
• attribute{}.fme_data_type: FME generic data type
• attribute{}.native_data_type: Native data type of the attribute (format specific)

You can use the ListExploder to decompose the list into individual elements, and then write them into an Excel spreadsheet.

Thanks Takashi

 

I came across the problem, but in my case I did not have access to the source_datasets, so I could not run the workspace, but I wanted to extract every user attribute. So what i did was to make a script to extract the data from the .fmw file and it goes as follows:

import xml.etree.cElementTree as ET
workspace = r'C:\Enter\Your\Workspace\Here.fmw'

with open(workspace) as f:
    lines = w]
    line = f.readline()
    while True:
        if not line:
            break
        if line.startswith('#!'):
            lines.append(line)
        elif line.startswith('#'):
            pass
        else:
            break
        line = f.readline()
    with open('fmw2xml.xml','w') as fw:
        fw.write(''.join(lines).replace('#! ',''))

xml =  ET.parse('fmw2xml.xml')
for feature_type in xml.iter('FEATURE_TYPE'):
    with open(f'{feature_type.attribÂ"NODE_NAME"]}.csv', 'w+') as csv:
        _header = False
        for child in feature_type.iter('FEAT_ATTRIBUTE'):
            if not _header:
                csv.write(';'.join(child.attrib.keys())+'\n')
                _header = True
            csv.write(';'.join(child.attrib.values())+'\n')

Now what this does it creates a csv file for every reader in your workspace, and inside each csv is the user attributes. code tested in py 3.6 , for 2.7 f strings must be converted to supported string format.

What about on a DB connection?