Before deploying an application in a DevOps workflow, you must ensure that all required environment variables are set. Missing or incorrect environment variables can cause deployments to fail or behave unpredictably. This challenge will give you hands-on experience simulating such a pre-deployment check using Python. You will create a script that checks if each variable in a required set is present in the environment (for this exercise, you will use a hardcoded dictionary to represent environment variables) and reports whether each one is set or missing. This type of validation is a fundamental step in automating deployment pipelines and maintaining reliable infrastructure.


import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def test_prints_message_for_each_variable(self):
        import user_code
        importlib.reload(user_code)
        required = ["VAR1", "VAR2", "VAR3"]
        env = {"VAR1": "foo", "VAR3": "bar"}
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.check_env_vars(required, env)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "var1 is set" in output and "var2 is missing" in output and "var3 is set" in output,
            "Function prints correct status for all required variables.",
            f"Output did not contain expected messages: {output}",
        )

    def test_prints_set_for_present_variable(self):
        import user_code
        importlib.reload(user_code)
        required = ["EXISTING_VAR"]
        env = {"EXISTING_VAR": "exists"}
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.check_env_vars(required, env)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "existing_var is set" in output,
            "Function prints 'set' for present variable.",
            f"Expected 'is set' message for present variable, got: {output}",
        )

    def test_prints_missing_for_absent_variable(self):
        import user_code
        importlib.reload(user_code)
        required = ["MISSING_VAR"]
        env = {"OTHER_VAR": "something"}
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.check_env_vars(required, env)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "missing_var is missing" in output,
            "Function prints 'missing' for absent variable.",
            f"Expected 'is missing' message for absent variable, got: {output}",
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    changed = False
    # Collect all assignment nodes to modify
    assign_nodes = [
        (i, node)
        for i, node in enumerate(tree.body)
        if isinstance(node, ast.Assign)
        and any(isinstance(target, ast.Name) and target.id == var_name for target in node.targets)
    ]

    # If nothing to change, return unmodified code
    if not assign_nodes:
        return code

    # Perform replacements for all matching assignments (from last to first to not break line offsets)
    for i, node in reversed(assign_nodes):
        start_line = node.lineno - 1
        line = lines[start_line]
        indent = ' ' * (len(line) - len(line.lstrip()))
        lines[start_line] = f"{indent}{var_name} = {value}"
        next_line = len(lines)
        for next_node in tree.body[i+1:]:
            if hasattr(next_node, 'lineno'):
                next_line = next_node.lineno - 1
                break
        if next_line > start_line + 1:
            lines[start_line+1:next_line] = []
        changed = True

    return '\\n'.join(lines) if changed else code

if __name__ == "__main__":
    unittest.main()


test_main.py

Learn how Python empowers DevOps workflows, automates repetitive tasks, and streamlines infrastructure management. This course introduces practical Python techniques and libraries for DevOps beginners, focusing on automation, monitoring, and data-driven decision-making.

Explore how Python can automate repetitive DevOps tasks, from simple scripting to basic process management.

Learn how Python can be used to monitor system health and analyze logs, providing valuable insights for DevOps teams.

Apply Python's data analysis and visualization capabilities to make informed decisions in DevOps environments.

Challenge: Environment Variable Checker

Løsning

Challenge: Environment Variable Checker

Løsning