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Arcpy Metadata Editor (arcpy_metadata)

Whether you create it or not, metadata is a critical part of GIS analysis. ArcGIS includes a built-in GUI metadata editor, but has scant access to metadata properties from Python. The arcpy_metadata package provides this access, allowing large Python packages that generate their own geospatial outputs in ArcGIS to properly document the data.

Getting arcpy_metadata

arcpy_metadata is pure Python and its only dependency is arcpy (installed with ArcGIS). It's available on the Python Package Index so you can get arcpy_metadata via pip (pip install arcpy_metadata).

If you don't have or don't know how to use pip, you can install arcpy_metadata by cloning/downloading this repository and running setup.py install in the root folder

Using arcpy_metadata

Creating the Metadata Editor

Edit existing metadata for Shapefiles, Rasters, FeatureClasses, RasterDatasets, MosaicDatasets or Layers

import arcpy_metadata as md
metadata = md.MetadataEditor(path_to_some_feature_class)  # currently supports Shapefiles, FeatureClasses, RasterDatasets and Layers

Edit or create an XML file directly

import arcpy_metadata as md
metadata = md.MetadataEditor(metadata_file="path/to/metadata_file.xml")  # currently supports Shapefiles, FeatureClasses, RasterDatasets and Layers

Choose your log level

metadata = md.MetadataEditor(path_to_some_feature_class, loglevel="DEBUG")  # use any of CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET, dafault is INFO

Get text items (returns string)

title = metadata.title
abstract = metadata.abstract

Change text items

metadata.title = "The new title"
metadata.abstract = "This is the abstract"

Get list items (returns list)

tags = metadata.tags
for tag in tags:
    print tag

Change list items

metadata.tags = ["tag1", "tag2"]
metadata.tags[1] = "another tag"
metadata.tags.append("new tag")
metadata.tags.insert(0, "first tag")
metadata.tags.remove("tag1")
metadata.tags.pop()

Get numeric items (return int or float)

min_scale = metadata.min_scale
max_scale = metadata.max_scale

Change numeric items

metadata.min_scale = 500000
metadata.max_scale = 500

Get date items (returns date object)

last_update = metadata.last_update
last_update_year = metadata.last_update.year

Change date items (excepts datetime objects and formated string (yyyymmdd, yyyy-mm-ddThh:mm:ss)

from datetime import date
today = date.today()
metadata.last_update = today
metadata.last_update = "20160221"

Get contact items (returns contact object)

contact = metadata.point_of_contact
contact_name = metadata.point_of_contact.contact_name
contact_email = metadata.point_of_contact.email

Change contact items (all contact items are string)

metadata.point_of_contact.contact_name = "First and Last Name"
metadata.point_of_contact.email = "email@address.com"

Edited nested lists

# make sure you have the right number of elements
# add new ones
while metadata.online_resource < 3:
    metadata.online_resource.new()
# or delete spare once
while metadata.online_resource > 3:
	metadata.online_resource.pop()
	
metadata.online_resource[0].name = "First download link"
metadata.online_resource[0].link = "http://somelink"
metadata.online_resource[0].function = "download"
metadata.online_resource[1].name = "Second download link"
metadata.online_resource[1].link = "http://someotherlink"
metadata.online_resource[1].function = "download"
metadata.online_resource[2].name = "Third download link"
metadata.online_resource[2].link = "http://yetanotherdownloadlink"
metadata.online_resource[2].function = "download"

Remove all items from the geoprocessing history

metadata.rm_gp_history()

Saving the changes back to the file

metadata.save() # save the metadata back to file.
metadata.cleanup() # remove all temporary files.

or

metadata.finish()  # save() and cleanup() as one call

If you want to enable automatic updates of your metadata (feature classes only) call.

metadata.finish(True) 

Supported items

Contact items

Online Resource Items

Don't see the item you need? Read more about how to extend arcpy_metadata to work with other metadata elements it doesn't yet handle in CONTRIBUTING.md.

Python and ArcGIS Support

arcpy_metadata runs on Python 2 and 3, which means it can, at a basic level, be used both with ArcMap and ArcGIS Pro. ArcGIS Pro doesn't yet have some of the metadata export functions that arcpy_metadata relies on though, so, as of version 0.5, you must specify a path to a metadata XML file, or use a dataset that already has its metadata in an accessible XML format (e.g. Shapefile), in order to use arcpy_metadata in ArcGIS Pro. All features work in ArcMap/Python 2.

Under the hood

arcpy_metadata uses the strategy of exporting the metadata from the layer, then edits the xml export based on your method calls. When you're done, use finish() to save your data back to the source.

Known limitations

Does not yet support all metadata items.

arcpy_metadata only works with 32-bit Python. We use arcpy.XSLTransform_conversion() to extract metadata from geodatabases. 64bit arcpy python bindings for background processing do not support tools inside the metadata conversion toolset.

How to contribute

Contributions are well come! Please fork and submit pull requests. If you are missing a particular metadata attribute, you can easiy add them here. Don't forget to also add them to the test cases to make sure everything works as expected

Acknowledgements

arcpy_metadata was initially a project of the UC Davis Center for Watershed Sciences and has received significant contributions from the World Resources Institute. It was created as part of a larger project funded by the California Department of Fish and Wildlife Biogeographic Data Branch and further developed for Global Forest Watch. We thank our funders for their support and their commitment to high quality geospatial data.