bynder-sdk 2.0.0

Bynder SDK can be used to speed up the integration of Bynder in Python

Bynder Python SDK

The main goal of this SDK is to speed up the integration of Bynder customers who use Python. Making it easier to connect to the Bynder API (https://bynder.docs.apiary.io) and execute requests on it.

Note: As of version 1.0.0 this SDK now uses OAuth 2.0. For the last version using OAuth 1.0a please refer to version 0.0.6.

Requirements and dependencies

The Python SDK requires the following in order to fully work:

• Python >= 3.5, older versions of Python won't work.

Pip should handle all the dependencies automatically.

Installation

This SDK depends on a few libraries in order to work, installing it with pip should take care of everything automatically.

Before you install the SDK we recommend you to setup a virtual environment:

virtualenv -p python3 venv  # create virtual environment
source venv/bin/activate    # activate virtual environment

After you have successfully setup a virtual environment you can install the SDK with pip. Run the following command while your virtual environment is active.

pip install bynder-sdk

Getting started

This is a simple example on how to retrieve data from the Bynder asset bank. For a more detailed example of implementation refer to the sample code.

First import the BynderClient:

from bynder_sdk import BynderClient

When using OAuth2, create an instance of the client and use the flow to receive a token:

bynder_client = BynderClient(
    domain='portal.getbynder.com',
    redirect_uri='https://...',
    client_id='',
    client_secret='',
    token_saver=token_saver
)

print(bynder_client.get_authorization_url())
code = input('Code: ')
bynder_client.fetch_token(code)

When using a permanent token, the client instance can be created like this:

bynder_client = BynderClient(
  domain='portal.getbynder.com',
  permanent_token=''
)

Finally call one of the API's endpoints through one of the clients:

asset_bank_client = bynder_client.asset_bank_client
media_list = asset_bank_client.media_list({
    'limit': 2,
    'type': 'image'
})

A full list of the currently available clients and methods in the SDK can be found below

Methods Available

These are the methods currently availble on the Bynder Python SDK, refer to the Bynder API Docs for more specific details on the calls.

BynderClient:

Get an instance of the Asset Bank Client or the Collection Client if already with access tokens set up. Also allows to generate and authenticate request tokens, which are necessary for the rest of the Asset Bank and Collection calls.

asset_bank_client
collection_client
pim_client
workflow_client
get_authorization_url()
fetch_token()
derivatives()

asset_bank_client:

All the Asset Bank related calls, provides information and access to Media management.

brands()
tags()
meta_properties()
media_list(query)
media_info(media_id, query)
media_download_url()
set_media_properties(media_id, query)
delete_media(media_id)
create_usage(itegration_id, asset_id, query)
usage(query)
delete_usage(integration_id, asset_id, query)
upload_file(file_path, brand_id, media_id, query)

With the upload_file method you can do two things. You can upload a new asset, or you can upload a new version of an exising asset. You can control this by sending a media_id or not.

collection_client:

All the collection related calls.

collections(query)
collection_info(collection_id)
create_collection(name, query)
delete_collection(collection_id)
collection_media_ids(collection_id)
add_media_to_collection(collection_id, media_ids)
remove_media_from_collection(collection_id, meedia_ids)
share_collection(collection_id, collection_option, recipients, query)

pim_client:

All the PIM related calls.

metaproperties()
metaproperty_info(metaproperty_id)
metaproperty_options(metaproperty_id)
edit_metaproperty_option(metaproperty_option_id, children)

workflow_client:

All the workflow related calls.

users()
campaigns(query)
campaign_info(campaign_id)
create_campaign(name, key, description, responsibleID, query)
delete_campaign(campaign_id)
edit_campaign(campaign_id, name, key, description, responsibleID, query)
metaproperties()
metaproperty_info(metaproperty_id)
groups()
group_info(group_id)
job_preset_info(job_preset_info)
jobs(campaign_id)
create_job(name, campaignID, accountableID, presetID, query)
job_info(job_id)
edit_job(job_id, name, campaignID, accauntableID, presetID, query)
delete_job(job_id)}

Tests

You can run the tests by using the command below. This will install the packages required and execute the tests for all the clients.

make test

Docker Setup Guide

The Docker setup allows you to run your Python scripts inside a Docker container, with dependencies installed and files synchronized. This guide aims to facilitate the development and testing of the SDK.

Requirements and dependencies

Ensure the following are installed on your machine:

• Docker
• docker-compose

Initial Setup

Create a secret.json file by following the example provided in the project. Fill in the necessary settings based on your requirements. If you have a permanent token, only the domain and permanent_token fields need to be specified:

{
   "domain": "example.bynder.com", # Without the http:// or https://
   "permanent_token": "7d09..........."
}

With docker and docker-compose installed, and your secret.json file ready, run the following command to initiate the container:

make run-docker

This command initializes a container with the bynder-python-sdk installed and ready for use.

Executing SDK Samples

You can utilize the Makefile commands on your console to run SDK sample scripts. The syntax is as follows:

make executeSdkSample sample-file-name=file.py

All sample files are located in the ./samples directory.

:warning: Caution: The sample scripts are provided as examples. It is crucial to review, add and/or modify the commands before execution. The container updates automatically with changes, ensuring a seamless development experience. Always exercise caution when executing scripts.

Stopping the Docker Container

When you're done with your development or testing, you can stop the Docker container using the following command:

make stop-docker