Skip to main content

Utility functions to work with Terraform Cloud and manage Terraform state.

Project description

tf_utils.py

A Python utility module for advanced management and automation of Terraform Cloud workspaces and state files.

Features

  • State File Filtering:
    Clean and filter Terraform state files by resource/module prefixes.

  • Terraform Cloud API Automation:

    • Download/upload state files.
    • Lock/unlock workspaces.
    • Trigger, monitor, and manage runs (cancel, discard, apply).
    • Manage workspace variables.
    • Retrieve run outputs and plan summaries.
  • Logging:
    Consistent, timestamped logging for all operations.

  • SSL Verification: SSL verification is skipped if there is any certificate errors.

Usage

1. Setup

Install dependencies:

pip3 install requests
pip3 install python-utilities-tfc

Import the module in your Python script:

from python_utilities_tfc import tf_utils
export TERRAFORM_CLOUD_TOKEN="your-token"
export TERRAFORM_ORG_NAME="your-org-name"

2. Example Operations

Auto-Apply-Workspace

import os
import logging

from tf_utils import (
    setup_logging,
    trigger_run,
    monitor_run,
    get_plan_summary,
    apply_run,
    get_workspace_id
)

def main():
    setup_logging()

    workspace_name = os.getenv("TARGET_WORKSPACE_NAME", "Virtual-Machines-Management")

    # Read safe prefixes from environment or fallback to "null_resource"
    safe_prefixes = os.getenv("SAFE_PREFIXES", "null_resource").split(",")

    try:
        # Step 1: Get Workspace ID
        workspace_id = get_workspace_id(workspace_name)

        # Step 2: Trigger Plan-only Run
        logging.info(f"🚀 Triggering a plan-only run on workspace: {workspace_name}")
        run_id = trigger_run(workspace_id, auto_apply=False)

        if not run_id:
            logging.error("❌ Failed to trigger run. No run ID returned.")
            return

        # Step 3: Monitor the Plan
        logging.info(f"🔎 Monitoring plan run {run_id}...")
        monitor_run(run_id)

        # Step 4: Summarize the Plan
        plan_result = get_plan_summary(run_id)

        if not plan_result:
            logging.warning("⚠️ No plan summary available. Cannot decide to auto-apply.")
            return

        summary = plan_result.get("summary", {})
        resource_changes = plan_result.get("resource_changes", [])

        adds = summary.get("add", 0)
        changes = summary.get("change", 0)
        destroys = summary.get("destroy", 0)
        has_changes = summary.get("has-changes", True)

        # Step 5: Log resource changes
        if resource_changes:
            logging.info("🛠️ The following resources will be created/updated/deleted:")
            for res in resource_changes:
                logging.info(f"- {res['address']} ({', '.join(res['actions'])})")
        else:
            logging.info("✅ No actionable resource changes (only 'no-op').")

        # Step 6: Evaluate changes
        unsafe_changes = []
        for res in resource_changes:
            actions = res.get("actions", res.get("change", {}).get("actions", []))
            address = res["address"]

            for action in actions:
                if action == "create":
                    continue  # always allowed
                elif action in ["delete", "update"]:
                    if not any(address.startswith(prefix) for prefix in safe_prefixes):
                        unsafe_changes.append({
                            "address": address,
                            "actions": actions
                        })
                else:
                    # Any unknown action -> treat as unsafe
                    unsafe_changes.append({
                        "address": address,
                        "actions": actions
                    })

        # Step 7: Auto-Apply if Safe
        logging.info(f"🛠 Plan Summary: {adds} to add, {changes} to change, {destroys} to destroy.")

        if has_changes:
            if not unsafe_changes:
                logging.info("✅ Only safe changes detected. Proceeding to auto-apply...")
                apply_run(run_id)

                # Step 8: Monitor the Apply
                logging.info(f"🔎 Monitoring apply for run {run_id}...")
                monitor_run(run_id)
                logging.info("✅ Apply completed successfully.")
            else:
                logging.warning("⚠️ Unsafe resource changes detected. Manual review required:")
                for unsafe in unsafe_changes:
                    logging.warning(f"- {unsafe['address']} ({', '.join(unsafe['actions'])})")
                logging.warning("🚫 Skipping auto-apply due to unsafe changes.")
        else:
            logging.info("✅ No changes detected. No need to apply.")

    except Exception as e:
        logging.error(f"❌ Error occurred: {e}")

if __name__ == "__main__":
    main()

Clean a State File

tf_utils.clean_state_file_by_prefixes(
    input_path="input.tfstate",
    output_path="cleaned.tfstate",
    keep_prefixes=["module1"],
    remove_prefixes=["module2"]
)

Download Workspace State

tf_utils.download_workspace_state(
    workspace_name="my-workspace",
)

Trigger and Monitor a Run

run_id = tf_utils.trigger_run(
    workspace_id="ws-xxxx",
    auto_apply=True
)
tf_utils.monitor_run(
    run_id=run_id
)

Get Run Outputs

outputs = tf_utils.get_run_outputs(
    run_id="run-xxxx"
)
print(outputs)

Functions Overview

  • setup_logging(): Configure logging.
  • clean_state_file_by_prefixes(): Filter resources in a state file.
  • download_workspace_state(): Download the latest state from Terraform Cloud.
  • push_state_to_terraform_cloud(): Upload a state file to Terraform Cloud.
  • lock_workspace(), unlock_workspace(): Lock/unlock a workspace.
  • trigger_run(), monitor_run(), cancel_run(), discard_run(), apply_run(): Manage runs.
  • get_run_outputs(), get_plan_summary(): Retrieve outputs and plan details.
  • get_variable_id(), update_variable(): Manage workspace variables.

Requirements

  • Python 3.11+
  • requests library

Notes

  • All API operations require a valid Terraform Cloud API token.
  • Use caution when discarding or canceling runs, as this may affect your infrastructure state.

License

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

python-utilities-tfc-1.6.0.tar.gz (10.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

python_utilities_tfc-1.6.0-py3-none-any.whl (10.5 kB view details)

Uploaded Python 3

File details

Details for the file python-utilities-tfc-1.6.0.tar.gz.

File metadata

  • Download URL: python-utilities-tfc-1.6.0.tar.gz
  • Upload date:
  • Size: 10.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.5

File hashes

Hashes for python-utilities-tfc-1.6.0.tar.gz
Algorithm Hash digest
SHA256 99d4a86750df03bf04537bf93208cefc2785f6b44906d431913f1b9c5bc1cbdc
MD5 9d1083d9663d8167115f813739094ce2
BLAKE2b-256 f356cfe6c6f17e03a24f2a6207e9ee6d9e73a238975e8febff16d66d3c52e4e1

See more details on using hashes here.

File details

Details for the file python_utilities_tfc-1.6.0-py3-none-any.whl.

File metadata

File hashes

Hashes for python_utilities_tfc-1.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 805ee0f16b4d3d254b70e1e8d825da29dab95641c672ac8cd4da53ed9abf79b9
MD5 191c284baf4156827498aab72feee696
BLAKE2b-256 688b08b041254185f5dc1c44b3784e1b7276367dd8c9afe8e0dff30ffc25eef8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page