dda-python-terraform/test/test_terraform.py
Freddy Tan 2ff59f3630 1. add test cases, try tdd
2. refactor to more generic method instead of aws method
3. ready for release to pypi
2016-11-18 15:35:14 +08:00

83 lines
2.5 KiB
Python

from python_terraform import Terraform
import pytest
import os
import logging
import re
logging.basicConfig(level=logging.DEBUG)
ACCESS_KEY = os.environ['PACKER_access_key']
SECRET_KEY = os.environ['PACKER_secret_key']
STRING_CASES = [
[
lambda x: x.generate_cmd_string('apply', 'the_folder',
no_color='',
var={'a': 'b', 'c': 'd'}),
"terraform apply -var='a=b' -var='c=d' -no-color the_folder"
],
[
lambda x: x.generate_cmd_string('push', 'path',
var={'a': 'b'}, vcs=True,
token='token',
atlas_address='url'),
"terraform push -var='a=b' -vcs=true -token=token -atlas-address=url path"
],
]
CMD_CASES = [
['method', 'expected_output'],
[
[
lambda x: x.cmd('plan', 'aws_tf', no_color='', var={'access_key': ACCESS_KEY, 'secret_key': SECRET_KEY}) ,
'Plan: 1 to add, 0 to change, 0 to destroy'
]
]
]
class TestTerraform:
def teardown_method(self, method):
""" teardown any state that was previously setup with a setup_method
call.
"""
def purge(dir, pattern):
for f in os.listdir(dir):
if re.search(pattern, f):
if os.path.isfile(f):
os.remove(os.path.join(dir, f))
purge('.', '.tfstate')
@pytest.mark.parametrize([
"method", "expected"
], STRING_CASES)
def test_generate_cmd_string(self, method, expected):
tf = Terraform()
result = method(tf)
strs = expected.split()
for s in strs:
assert s in result
@pytest.mark.parametrize(*CMD_CASES)
def test_cmd(self, method, expected_output):
tf = Terraform()
ret, out, err = method(tf)
assert expected_output in out
assert ret == 0
def test_state_data(self):
tf = Terraform(working_dir='test_tfstate_file')
tf.read_state_file()
assert tf.tfstate.modules[0]['path'] == ['root']
def test_apply(self):
tf = Terraform(working_dir='apply_tf', variables={'test_var': 'test'})
tf.apply(var={'test_var': 'test2'})
def test_get_output(self):
tf = Terraform(working_dir='apply_tf', variables={'test_var': 'test'})
tf.apply()
assert tf.output('test_output') == 'test'