246 lines
8.9 KiB
Python
246 lines
8.9 KiB
Python
# Copyright 2023 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Common fixtures."""
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import collections
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import contextlib
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import glob
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import os
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import shutil
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import tempfile
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from pathlib import Path
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import pytest
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import tftest
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import yaml
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PlanSummary = collections.namedtuple('PlanSummary', 'values counts outputs')
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@contextlib.contextmanager
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def _prepare_root_module(path):
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"""Context manager to prepare a terraform module to be tested.
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If the TFTEST_COPY environment variable is set, `path` is copied to
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a temporary directory and a few terraform files (e.g.
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terraform.tfvars) are deleted to ensure a clean test environment.
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Otherwise, `path` is simply returned untouched.
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"""
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if os.environ.get('TFTEST_COPY'):
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# if the TFTEST_COPY is set, create temp dir and copy the root
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# module there
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with tempfile.TemporaryDirectory(dir=path.parent) as tmp_path:
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tmp_path = Path(tmp_path)
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# if we're copying the module, we might as well ignore files and
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# directories that are automatically read by terraform. Useful
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# to avoid surprises if, for example, you have an active fast
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# deployment with links to configs)
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ignore_patterns = shutil.ignore_patterns('*.auto.tfvars',
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'*.auto.tfvars.json',
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'[0-9]-*-providers.tf',
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'terraform.tfstate*',
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'terraform.tfvars', '.terraform')
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shutil.copytree(path, tmp_path, dirs_exist_ok=True,
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ignore=ignore_patterns)
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yield tmp_path
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else:
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# if TFTEST_COPY is not set, just return the same path
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yield path
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def plan_summary(module_path, basedir, tf_var_files=None, extra_files=None,
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**tf_vars):
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"""
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Run a Terraform plan on the module located at `module_path`.
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- module_path: terraform root module to run. Can be an absolute
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path or relative to the root of the repository
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- basedir: directory root to use for relative paths in
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tf_var_files.
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- tf_var_files: set of terraform variable files (tfvars) to pass
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in to terraform
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Returns a PlanSummary object containing 3 attributes:
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- values: dictionary where the keys are terraform plan addresses
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and values are the JSON representation (converted to python
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types) of the attribute values of the resource.
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- counts: dictionary where the keys are the terraform resource
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types and the values are the number of times that type appears
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in the plan
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- outputs: dictionary of the modules outputs that can be
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determined at plan type.
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Consult [1] for mode details on the structure of values and outputs
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[1] https://developer.hashicorp.com/terraform/internals/json-format
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"""
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# make the module_path relative to the root of the repo while still
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# supporting absolute paths
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module_path = Path(__file__).parents[1] / module_path
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with _prepare_root_module(module_path) as test_path:
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binary = os.environ.get('TERRAFORM', 'terraform')
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tf = tftest.TerraformTest(test_path, binary=binary)
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extra_files = [(module_path / filename).resolve()
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for x in extra_files or []
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for filename in glob.glob(x, root_dir=module_path)]
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tf.setup(extra_files=extra_files, upgrade=True)
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tf_var_files = [(basedir / x).resolve() for x in tf_var_files or []]
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plan = tf.plan(output=True, tf_var_file=tf_var_files, tf_vars=tf_vars)
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# compute resource type counts and address->values map
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values = {}
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counts = collections.defaultdict(int)
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counts['modules'] = counts['resources'] = 0
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q = collections.deque([plan.root_module])
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while q:
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e = q.popleft()
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if 'type' in e:
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counts[e['type']] += 1
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if 'values' in e:
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values[e['address']] = e['values']
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for x in e.get('resources', []):
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counts['resources'] += 1
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q.append(x)
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for x in e.get('child_modules', []):
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counts['modules'] += 1
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q.append(x)
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# extract planned outputs
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outputs = plan.get('planned_values', {}).get('outputs', {})
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return PlanSummary(values, dict(counts), outputs)
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@pytest.fixture(name='plan_summary')
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def plan_summary_fixture(request):
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"""Return a function to generate a PlanSummary.
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In the returned function `basedir` becomes optional and it defaults
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to the directory of the calling test
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"""
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def inner(module_path, basedir=None, tf_var_files=None, extra_files=None,
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**tf_vars):
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if basedir is None:
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basedir = Path(request.fspath).parent
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return plan_summary(module_path=module_path, basedir=basedir,
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tf_var_files=tf_var_files, extra_files=extra_files,
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**tf_vars)
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return inner
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def plan_validator(module_path, inventory_paths, basedir, tf_var_files=None,
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extra_files=None, **tf_vars):
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summary = plan_summary(module_path=module_path, tf_var_files=tf_var_files,
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extra_files=extra_files, basedir=basedir, **tf_vars)
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# allow single single string for inventory_paths
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if not isinstance(inventory_paths, list):
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inventory_paths = [inventory_paths]
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for path in inventory_paths:
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# allow tfvars and inventory to be relative to the caller
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path = basedir / path
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try:
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inventory = yaml.safe_load(path.read_text())
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except (IOError, OSError, yaml.YAMLError) as e:
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raise Exception(f'cannot read test inventory {path}: {e}')
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# don't fail if the inventory is empty
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inventory = inventory or {}
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# If you add additional asserts to this function:
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# - put the values coming from the plan on the left side of
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# any comparison operators
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# - put the values coming from user's inventory the right
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# side of any comparison operators.
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# - include a descriptive error message to the assert
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# for values:
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# - verify each address in the user's inventory exists in the plan
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# - for those address that exist on both the user's inventory and
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# the plan output, ensure the set of keys on the inventory are a
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# subset of the keys in the plan, and compare their values by
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# equality
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if 'values' in inventory:
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expected_values = inventory['values']
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for address, expected_value in expected_values.items():
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assert address in summary.values, \
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f'{address} is not a valid address in the plan'
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for k, v in expected_value.items():
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assert k in summary.values[address], \
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f'{k} not found at {address}'
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plan_value = summary.values[address][k]
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assert plan_value == v, \
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f'{k} at {address} failed. Got `{plan_value}`, expected `{v}`'
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if 'counts' in inventory:
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expected_counts = inventory['counts']
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for type_, expected_count in expected_counts.items():
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assert type_ in summary.counts, \
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f'module does not create any resources of type `{type_}`'
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plan_count = summary.counts[type_]
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assert plan_count == expected_count, \
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f'count of {type_} resources failed. Got {plan_count}, expected {expected_count}'
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if 'outputs' in inventory:
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expected_outputs = inventory['outputs']
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for output_name, expected_output in expected_outputs.items():
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assert output_name in summary.outputs, \
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f'module does not output `{output_name}`'
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output = summary.outputs[output_name]
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# assert 'value' in output, \
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# f'output `{output_name}` does not have a value (is it sensitive or dynamic?)'
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plan_output = output.get('value', '__missing__')
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assert plan_output == expected_output, \
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f'output {output_name} failed. Got `{plan_output}`, expected `{expected_output}`'
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return summary
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@pytest.fixture(name='plan_validator')
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def plan_validator_fixture(request):
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"""Return a function to build a PlanSummary and compare it to a YAML inventory.
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In the returned function `basedir` becomes optional and it defaults
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to the directory of the calling test'
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"""
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def inner(module_path, inventory_paths, basedir=None, tf_var_files=None,
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**tf_vars):
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if basedir is None:
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basedir = Path(request.fspath).parent
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return plan_validator(module_path=module_path,
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inventory_paths=inventory_paths, basedir=basedir,
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tf_var_files=tf_var_files, **tf_vars)
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return inner
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# @pytest.fixture
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# def repo_root():
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# 'Return a pathlib.Path to the root of the repository'
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# return Path(__file__).parents[1]
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