pycarlo

library0.15.248pypypi✓ verified 24d ago

Pycarlo is Monte Carlo's Python SDK, providing programmatic access to the Monte Carlo data observability platform's APIs. It enables users to execute queries and mutations against the Monte Carlo API and leverage higher-level features for common data operations. The library is actively maintained and frequently updated, with a current version of 0.12.292 and requires Python 3.9 or greater.

devops data

pip install -U pycarlo

package ↗homepage ↗

INSTALL

IMPORT

SIG · PYCARLO

pycarlo

devopspythonv0.15.248

Install

4.0s avg

Import

6979ms

Disk

51MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.15.248 · 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 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 7.080s · 44.3MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 4.0s · import 6.878s · 63MB

51MB installed

● package 51MB

Code

Verified usage

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

Client

✓ from pycarlo.core import Client

Query

✓ from pycarlo.core import Query

Mutation

✓ from pycarlo.core import Mutation

Session

✓ from pycarlo.core import Session

CircuitBreakerService

✓ from pycarlo.features.circuit_breakers import CircuitBreakerService

This quickstart demonstrates how to initialize the Pycarlo client and execute a basic query to retrieve the current user's email. Authentication is handled via environment variables (MCD_ID, MCD_TOKEN), a Monte Carlo CLI-configured profile (~/.mcd/profiles.ini), or by explicitly passing credentials to the Session. It's recommended to use environment variables or CLI profiles for security in production environments.

import os from pycarlo.core import Client, Query, Session # Configure session using environment variables or a named profile # For production, it's recommended to set MCD_ID and MCD_TOKEN environment variables. # Alternatively, you can configure via the Monte Carlo CLI: `montecarlo configure` # If using a named profile, ensure ~/.mcd/profiles.ini is set up. mcd_id = os.environ.get('MCD_ID', 'your_mcd_id_here') mcd_token = os.environ.get('MCD_TOKEN', 'your_mcd_token_here') # Instantiate a client. By default, it uses the 'default' profile or environment variables. # You can also pass credentials explicitly or specify a profile: # client = Client(Session(mcd_id=mcd_id, mcd_token=mcd_token)) client = Client() # Create a query object query = Query() query.get_user.email() # Execute the query try: response = client(query) user_email = response.get_user.email print(f"Current user email: {user_email}") except Exception as e: print(f"An error occurred: {e}")

Debug

Known issues

gotchaAPI Key Configuration: Pycarlo requires an API Key ID (MCD_ID) and API Secret (MCD_TOKEN) for authentication. These are typically sourced from environment variables or a configuration file (~/.mcd/profiles.ini) created by the Monte Carlo CLI (`montecarlo configure`). Incorrect or missing credentials will prevent the SDK from functioning.

fix

Ensure `MCD_ID` and `MCD_TOKEN` environment variables are set, or run `montecarlo configure` via the CLI to set up a default profile. For explicit control, pass `mcd_id` and `mcd_token` to `pycarlo.core.Session`.

affects: All

gotchaEnum Backward Compatibility: Unlike `sgqlc`'s default behavior, Pycarlo is designed to be backward compatible with new enum values introduced in the Monte Carlo API. If the API returns an enum value not present in your SDK version, it will be returned as a string with a warning, instead of raising an error. While this prevents breakage, it means your local SDK might not fully reflect the latest API schema.

fix

Keep your Pycarlo SDK updated to the latest version to avoid warnings and ensure full feature and schema support. `pip install -U pycarlo`.

affects: All

gotchaSeparation of Core and Features: Pycarlo is divided into `core` for direct API queries/mutations and `features` for higher-level convenience functions (e.g., circuit breakers, dbt, pii filtering). Ensure you import from the correct submodule (e.g., `from pycarlo.core import Client` vs. `from pycarlo.features.circuit_breakers import CircuitBreakerService`).

fix

Refer to the documentation for specific imports. Most basic operations start with `pycarlo.core`.

affects: All

Upgrade

Version history

0.15.248latest on PyPI · released Aug 28, 2026

Audit

Dependencies

No dependency data recorded yet.

Agent activity

13 hits · last 30 days

node

Resources

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

homepagehttps://www.montecarlodata.com/ ↗