DigitalOcean PyDo Python Library Reference

Generated on 8 May 2026 from pydo version v0.34.0

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PyDo is the official Python client library for the DigitalOcean API. It provides a Python abstraction layer on top of the raw HTTP API, wrapping a generated client based on the DigitalOcean OpenAPI Specification.

Installation

Install pydo using pip:

Requires Python 3.7.2 or later.

Initialization

Create a client by passing your DigitalOcean API token:

import os
from pydo import Client

client = Client(token=os.environ.get("DIGITALOCEAN_TOKEN"))

The Client constructor accepts the following parameters:

Name Type Default Description
token string A valid API token, model access key, or agent access key. Required.
endpoint string https://api.digitalocean.com Base URL for API requests.
timeout integer 120 Request timeout in seconds.
inference_endpoint string https://inference.do-ai.run Serverless inference URL.
agent_endpoint string "" Agent inference endpoint URL. Required only for agent inference methods.

You can also customize retry behavior:

# Modify the total number of retries
client = Client(token=os.environ.get("DIGITALOCEAN_TOKEN"), retry_total=3)

For examples of advanced client configuration, including logging, custom user agents, and per-request timeouts, see the pydo examples directory.

Serverless inference methods can authenticate with either an API token or a model access key. Agent inference methods require an agent access key and a per-agent endpoint URL:

client = Client(
    token=os.environ.get("AGENT_ACCESS_KEY"),
    agent_endpoint="https://your_agent_url",
)

Usage

Call API methods through client.<resource>.<method>():

import os
from pydo import Client

client = Client(token=os.environ.get("DIGITALOCEAN_TOKEN"))

ssh_keys_resp = client.ssh_keys.list()
for k in ssh_keys_resp["ssh_keys"]:
    print(f"ID: {k['id']}, NAME: {k['name']}, FINGERPRINT: {k['fingerprint']}")

All methods raise HttpResponseError on failure. Each method page documents its specific return type.

Resources

pydo.account

Provides information about your current account.

pydo.actions

Actions are records of events that have occurred on the resources in your account.

pydo.addons

Add-ons are third-party applications that can be added to your DigitalOcean account.

pydo.agent_inference

DigitalOcean Gradient™ AI Agentic Cloud allows you to create multi-agent workflows to power your AI applications.

pydo.apps

App Platform is a Platform-as-a-Service (PaaS) offering from DigitalOcean that allows developers to publish code directly to DigitalOcean servers without worrying about the underlying infrastructure.

pydo.autoscalepools

Droplet autoscale pools manage automatic horizontal scaling for your applications based on resource usage (CPU, memory, or both) or a static configuration.

pydo.balance

The billing endpoints allow you to retrieve your account balance, invoices, billing history, and insights.

pydo.billing_history

The billing endpoints allow you to retrieve your account balance, invoices, billing history, and insights.

pydo.billing_insights

The billing endpoints allow you to retrieve your account balance, invoices, billing history, and insights.

pydo.byoip_prefixes

Bring your own IP (BYOIP) lets you provision your own IPv4 network prefixes to your account, then assign those IPs to your DigitalOcean resources.

pydo.cdn

Content hosted in DigitalOcean’s object storage solution, Spaces, can optionally be served by our globally distributed Content Delivery Network (CDN).

pydo.certificates

In order to perform SSL termination on load balancers, DigitalOcean offers two types of SSL certificate management.

pydo.databases

DigitalOcean’s managed database service simplifies the creation and management of highly available database clusters.

pydo.dedicated_inferences

Dedicated Inference delivers scalable production-grade LLM hosting on DigitalOcean.

pydo.domains

Domain resources are domain names that you have purchased from a domain name registrar that you are managing through the DigitalOcean DNS interface.

pydo.droplet_actions

Droplet actions are tasks that can be executed on a Droplet.

pydo.droplets

A Droplet is a DigitalOcean virtual machine.

pydo.firewalls

DigitalOcean Cloud Firewalls provide the ability to restrict network access to and from a Droplet allowing you to define which ports will accept inbound or outbound connections.

pydo.functions

Serverless functions are blocks of code that run on demand without the need to manage any infrastructure.

pydo.functions_access_key

Serverless functions are blocks of code that run on demand without the need to manage any infrastructure.

pydo.genai

The API lets you build GPU-powered AI agents with pre-built or custom foundation models, function and agent routes, and RAG pipelines with knowledge bases.

pydo.image_actions

Image actions are commands that can be given to a DigitalOcean image.

pydo.images

A DigitalOcean image can be used to create a Droplet and may come in a number of flavors.

pydo.inference

DigitalOcean Gradient™ AI Agentic Cloud allows access to serverless inference models.

pydo.invoices

The billing endpoints allow you to retrieve your account balance, invoices, billing history, and insights.

pydo.monitoring

The DigitalOcean Monitoring API makes it possible to programmatically retrieve metrics as well as configure alert policies based on these metrics.

pydo.nfs

NFS lets you create fully managed, POSIX-compliant network file storage that delivers secure, high-performance shared storage right inside your VPC.

pydo.one_clicks

1-Click applications are pre-built Droplet images or Kubernetes apps with software, features, and configuration details already set up for you.

pydo.partner_attachments

Partner Network Connect lets you establish high-bandwidth, low-latency network connections directly between DigitalOcean VPC networks and other public cloud providers or on-premises datacenters.

pydo.projects

Projects allow you to organize your resources into groups that fit the way you work.

pydo.regions

Provides information about DigitalOcean data center regions.

pydo.registries

DigitalOcean now supports up to nine additional registries (for a total maximum of 10) per team if your container registry uses the Professional subscription plan.

pydo.registry

DigitalOcean offers the ability for you to create a private container registry to store your Docker images for use with your Kubernetes clusters.

pydo.reserved_ips

As of 16 June 2022, we have renamed the [Floating IP](/reference/api/reference/floating-ips/ product to Reserved IPs.

pydo.reserved_ips_actions

As of 16 June 2022, we have renamed the [Floating IP](/reference/api/reference/floating-ips/ product to Reserved IPs.

pydo.reserved_ipv6

DigitalOcean Reserved IPv6s are publicly-accessible static IP addresses that can be mapped to one of your Droplets.

pydo.reserved_ipv6_actions

Reserved IPv6 actions requests are made on the actions endpoint of a specific reserved IPv6.

pydo.security

Security CSPM endpoints for scans, scan findings, and settings.

pydo.sizes

The sizes objects represent different packages of hardware resources that can be used for Droplets.

pydo.snapshots

Snapshots are saved instances of a Droplet or a block storage volume, which is reflected in the resource_type attribute.

pydo.spaces_key

Spaces keys authenticate requests to DigitalOcean Spaces Buckets.

pydo.ssh_keys

Manage SSH keys available on your account.

pydo.tags

A tag is a label that can be applied to a resource (currently Droplets, Images, Volumes, Volume Snapshots, and Database clusters) in order to better organize or facilitate the lookups and actions on it.

pydo.uptime

DigitalOcean Uptime Checks provide the ability to monitor your endpoints from around the world, and alert you when they’re slow, unavailable, or SSL certificates are expiring.

pydo.volume_actions

Block storage actions are commands that can be given to a DigitalOcean Block Storage Volume.

pydo.vpc_peerings

VPC Peerings join two VPC networks with a secure, private connection.

pydo.vpcnatgateways

VPC NAT Gateways allow resources in a private VPC to access the public internet without exposing them to incoming traffic.

pydo.vpcs

VPCs (virtual private clouds) allow you to create virtual networks containing resources that can communicate with each other in full isolation using private IP addresses.

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