• IBM Cloud Python SDK
  • Environment variables
  • Documentation
  • Supported features
  • Installation
  • Caching
    • Podman
    • Docker
  • Examples
    • List VPCs
    • Create a VPC instance
  • FAQ

ibmcloud-python-sdk aims to talk to IBM Cloud. To do this, it requires a configuration file. ibmcloud-python-sdk favours clouds.yaml file, but can also use environment variables (see below). An example:

---
clouds:
  default: demo-acc
  demo-acc:
    profile: demo
    description: Credentials from my IBM Cloud demo account
    key: XxX1234567890XxX
    region: us-south
    version: 2021-06-15
    generation: 2
    cis_username: [email protected]
    cis_apikey: abc123def456ghi789klm0n
  prod-acc:
    profile: prod
    description: Credentials from my IBM Cloud production account
    key: zZz1234567890zZz
    region: us-south
    version: 2021-06-15
    generation: 2
    cis_username: [email protected]
    cis_apikey: @@abc123def456ghi789klm0n@@

The clouds.yaml file will be searched at first into ~/.ibmcloud directory but this behavior could be overrided by an environment variable.

Documentation for the IBM Cloud Python SDK is available here.

IBM Cloud Python SDK leverages existing Python SDKs such as:

• SoftLayer
• IBM Cloud Object Storage

Only VPC Gen 2 is supported by this SDK.

Install from PyPi via pip:

python -m venv ~/virtualenvs/ibmcloud-python-sdk
source ~/virtualenvs/ibmcloud-python-sdk/bin/activate
pip install ibmcloud-python-sdk

Or you can install from source:

cd ~/Git
git clone https://github.com/goldyfruit/ibmcloud-python-sdk.git
python -m venv ~/virtualenvs/ibmcloud-python-sdk
source ~/virtualenvs/ibmcloud-python-sdk/bin/activate
cd ~/Git/ibmcloud-python-sdk
pip install .

We recommend to use Python virtual environment to install the SDK.

The SDK has caching capability (memcached only for now) to improve the HTTP requests speed. To enable this mechanisim please configure the SDK properly using ~/.ibmcloud/sdk.yaml file.

---
sdk:
  cache_ttl: 60
  memcached:
    - 127.0.0.1:11211

Muttiple cache servers could be configured as well.

---
sdk:
  cache_ttl: 60
  memcached:
    - 127.0.0.1:11211
    - 127.0.0.1:11212
    - 127.0.0.1:11213

An easy way to deploy memcached server is to use container.

podman run -dt -p 11211:11211 --name memcached -d memcached

sudo docker run -dt -p 11211:11211 --name memcached -d memcached

A list of examples on how to use this SDK can be found at here.

from ibmcloud_python_sdk.vpc import vpc as ic


vpc = ic.Vpc()
vpc.get_vpc("ibmcloud-vpc-baby")

from ibmcloud_python_sdk.vpc import vpc as icv
from ibmcloud_python_sdk.resource import resource_group as icr
import sys


# Variables
vpc_name = 'ibmcloud-vpc-baby'
resource_group_name = 'ibmcloud-resource-group-baby'

# Intentiate classes
vpc = icv.Vpc()
rg = icr.ResourceGroup()

# Retrieve resource group ID and check for error
resource_group_info = rg.get_resource_group(resource_group_name)
if 'errors' in resource_group_info:
    print(resource_group_info['errors'])
    sys.exit()

# Create the VPC based on variable and resource group ID
response = vpc.create_vpc(
            name=vpc_name,
            resource_group=resource_group_info['id'],
            address_prefix_management='auto',
            classic_access=True
        )

# Check for error during the VPC creation process
if 'errors' in response:
    print(response['errors'])
else:
    print(response)

• CRN or HREF could not be used as ID to retrieve resources
• PATCH method (update) is not yet supported which means a resource cannot be updated

See the bundled LICENSE file for more information.