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A suite of tools for interacting with Zegami through Python.

Project description

Zegami Python SDK



An SDK and general wrapper for the lower level Zegami API for Python. This package provides higher level collection interaction and data retrieval.

Getting started

Grab this repo, open the script, and load an instance of ZegamiClient into a variable.

from zegami_sdk.client import ZegamiClient

zc = ZegamiClient(username, login)


The client operates using a user token. By default, logging in once with a valid username/password will save the acquired token to your home directory as zegami.token. The next time you need to use ZegamiClient, you may call zc = ZegamiClient() with no arguments, and it will look for this stored token.

Example Usage

Get the metadata and images associated with every dog of the 'beagle' breed in a collection of dogs:

zc = ZegamiClient()


To see your available workspaces, use:


You can then ask for a workspace by name, by ID, or just from a list

all_workspaces = zc.workspaces
first_workspace = all_workspaces[0]



# Note the ID of a workspace
my_workspace = zc.get_workspace_by_id(id)



# Note the name of a collection
coll = my_workspace.get_collection_by_name(name_of_collection)

You can get the metadata in a collection as a Pandas DataFrame using:

rows = coll.rows

You can get the images of a collection using:

first_10_img_urls = coll.get_image_urls(list(range(10)))
imgs = coll.download_image_batch(first_10_img_urls)

If your collection supports the new multi-image-source functionality, you can see your available sources using:


For source 2's (3rd in 0-indexed-list) images, you would use:

first_10_source3_img_urls = novo_col.get_image_urls(list(range(10)), source=2)`

# To see the first of these:

In Development

This SDK is in active development, not all features are available yet. Creating/uploading to collections is not supported currently - check back soon!

Project details

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