pydo

library0.36.0pypypi✓ verified 88d ago

pydo is the official Python client library for interacting with the DigitalOcean API. It provides a programmatic interface to manage DigitalOcean resources such as Droplets, Kubernetes clusters, databases, and more. Currently at version 0.30.0, the library is frequently updated (often monthly minor releases) to reflect changes and additions to the DigitalOcean OpenAPI specification.

http-networking

pip install pydo

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · PYDO

pydo

http-networkingpythonv0.36.0

Install

4.9s avg

Import

698ms

Disk

110MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.36.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.718s · 109.3MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 4.9s · import 0.677s · 110MB

110MB installed

● package 110MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Client

✓ from pydo import Client

models

✓ from pydo import models

Import specific models like `models.Droplet` for type hinting or creating resources.

This quickstart demonstrates how to initialize the DigitalOcean client using an API token (preferably from an environment variable) and then fetch basic account information. It also includes commented-out examples for listing resources like Droplets, highlighting the common pattern for interacting with different services.

import os from pydo import Client from pydo.models import Account # Initialize a client with your DigitalOcean API token. # It's highly recommended to set DIGITALOCEAN_TOKEN as an environment variable. # Example: export DIGITALOCEAN_TOKEN="YOUR_DO_TOKEN" # For local testing without setting env var: DO_TOKEN = os.environ.get("DIGITALOCEAN_TOKEN", "YOUR_DO_TOKEN") if DO_TOKEN == "YOUR_DO_TOKEN": print("WARNING: Please set the DIGITALOCEAN_TOKEN environment variable for authentication.") print("Using a placeholder token for demonstration purposes. API calls will likely fail.") client = Client(token=DO_TOKEN) try: # Fetch current account information account: Account = client.account.get_account() print(f"Account Email: {account.email}") print(f"Droplet Limit: {account.droplet_limit}") print(f"Email Verified: {account.email_verified}") # Example: List up to 5 Droplets (adjust for pagination on large accounts) # droplets = client.droplets.list_droplets(per_page=5) # if droplets: # print(f"First Droplet Name: {droplets[0].name}") except Exception as e: print(f"An error occurred: {e}") if "Unauthorized" in str(e): print("Please ensure your DigitalOcean API token is valid and correctly set.")

Debug

Known issues

gotchaAlways store your DigitalOcean API token securely, preferably using environment variables (e.g., `DIGITALOCEAN_TOKEN`) rather than hardcoding it directly in your code. Hardcoded tokens pose a significant security risk.

fix

Use `os.environ.get('DIGITALOCEAN_TOKEN')` to retrieve the token.

affects: All versions

gotchaDigitalOcean API resources (like Droplets, Kubernetes clusters) often expose list operations that can return many items. While `pydo` aims to simplify this, be mindful of potential performance implications or memory usage when fetching very large lists, as some list methods may internally paginate to return a full collection.

fix

Consult the `pydo` documentation for specific list methods. For very large datasets, consider filtering requests or processing items in batches if direct iteration becomes inefficient.

affects: All versions

gotchaAs `pydo` is generated from the DigitalOcean OpenAPI specification, minor version updates (e.g., 0.29.0 to 0.30.0) can introduce changes to the underlying API models or available endpoints. This might mean new required fields for creating resources, removed fields from existing models, or changes in method signatures.

fix

Review the release notes for `pydo` and the DigitalOcean API documentation when upgrading to a new minor version, especially if you encounter `AttributeError` or unexpected API errors related to model structures.

affects: All minor versions (e.g., v0.x.y updates)

Errors

Common errors & fixes

pydo.exceptions.UnauthorizedException: You provided an invalid token.

The DigitalOcean API token used for client initialization is either missing, expired, or incorrect.

fix

Verify that the `DIGITALOCEAN_TOKEN` environment variable is correctly set with a valid, active API token, or that the token passed directly to `Client(token=...)` is correct.

AttributeError: 'DropletsService' object has no attribute 'list_all'

Attempting to call a non-existent method or a method with an incorrect name on a service object. For example, `client.droplets.list_all()` when the correct method is `client.droplets.list_droplets()`.

fix

Consult the `pydo` library documentation or use IDE auto-completion to find the correct method name for the desired operation (e.g., `client.droplets.list_droplets()` for listing Droplets).

pydo.exceptions.ResourceNotFoundException: The resource you requested could not be found.

The specific resource (e.g., Droplet, Volume) identified by its ID or name does not exist or is not accessible under your account.

fix

Double-check the ID or name of the resource you are trying to access. Ensure it exists in your DigitalOcean account and that your API token has the necessary permissions to access it.

Upgrade

Version history

0.36.0latest on PyPI · released Jun 9, 2026

Audit

Dependencies

No dependency data recorded yet.

Agent activity

9 hits · last 30 days

node

Resources

githubhttps://github.com/digitalocean/pydo ↗

packagehttps://pypi.org/project/pydo/ ↗

homepagehttps://www.digitalocean.com ↗

docshttps://pydo.readthedocs.io/ ↗