Latest Contributions by AllenDailey1

I figured out a way to do it!  I wanted to share my solution here, in case it can help anyone else in the future.  I wrote a Python script that used the Metadata class to access the xml file, and I read through the xml to determine what wording was used to indicate the metadata standard ("ArcGISProfile").  I did some string manipulation to grab the metadata standard (as well as the date the metadata was last updated), and I wrote all the feature class names and their metadata standard, date, and other metadata elements to a csv file, for easy sorting and examination.  Here is the script; the part that gets the metadata standard is lines 41-55:   """ Writes enterprise databases' feature classes' metadata elements, including metadata standard, to a csv file for use in determining which feature classes' metadata needs to be updated or put into a different standard. Python 3 / ArcGIS Pro Allen Dailey 1/25/24 """ import arcpy from arcpy import metadata as md import csv # Desired file name for csv file. File can already exist, or not. If exists, will overwrite. filename = r"\\path\to\csv_file.csv" # Column names to use in csv file columns = ["Database", "Dataset", "FeatureClass", "DateUpdated", "Standard", "Title", "Tags", "Summary", "Description", "UseLimitations", "Credits"] # List of enterprise database sde connections. Metadata elements will be obtained for each fc in each db. db_sde_list = [r"List\of\my\ArcGISPro\database\sde\connections.sde"] def get_metadata(db, dataset, fc_list, csv_writer): """ Gets metadata elements for each feature class in a list and writes the metadata elements to a csv. :param db: String, name of database, gotten from sde file path string :param dataset: Name of dataset within the db, gotten from arcpy.ListDatasets() :param fc_list: List, feature classes, generated by arcpy.ListFeatureClasses() :param csv_writer: CSV writer :return: None """ # For each feature class that has been passed into this function: for fc in fc_list: # Instantiate it as a metadata object m = md.Metadata(fc) # Get each of the usual metadata elements from the feature class's metadata tt = m.title tg = m.tags s = m.summary d = m.description u = m.accessConstraints c = m.credits # Get the metadata standard from the xml file. First, access the xml. x = m.xml # Break the xml into a list of parts, in order to find the part that says the metadata standard chunklist = x.split(">") # Standard and date = empty string, to avoid error in case the next block doesn't work out in a particular case. standard = "" date = "" # Go through each item in the list of parts of the xml file to find the standard for i in range(len(chunklist)): # "ArcGISProfile" is the field name for the metadata standard if "ArcGISProfile" in chunklist[i]: # The standard comes right after "ArcGISProfile." standard = chunklist[i + 1].split("<")[0] # Exit the loop to keep the correct content for the "standard" variable. break # Go through the xml to get the date metadata was last updated for i in range(len(chunklist)): if "mdDateSt" in chunklist[i]: date = chunklist[i+1].split("<")[0] break # List containing all the data to be written to a row of the csv file row = [db, dataset, fc, date, standard, tt, tg, s, d, u, c] # Write the row to the file csv_writer.writerow(row) # Establish the csv file and csv writer with open(filename, 'w', encoding="utf-8") as csvfile: writer = csv.writer(csvfile) # Write the column names to the csv file writer.writerow(columns) # For each database in the list, write its metadata elements to the csv file for db in db_sde_list: # Establish the database as the workspace in order to next access its datasets arcpy.env.workspace = db dbname = (db.split("\\")[-1]).split(".")[0] datasets = arcpy.ListDatasets() # If there are any standalone feature classes not inside datasets, get their names and their metadata try: lone_fcs = arcpy.ListFeatureClasses() get_metadata(dbname, "", lone_fcs, writer) except: print(f"Has no standalone fc's: {db}") for dataset in datasets: ds_fcs = arcpy.ListFeatureClasses(feature_dataset=dataset) get_metadata(dbname, dataset, ds_fcs, writer)     ... View more