feat: add environment variable loading in S3Client initialization #45
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WalkthroughThe update to the S3 client implementation adds explicit loading of environment variables from a Changes
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Actionable comments posted: 1
🧹 Nitpick comments (3)
hivemind_etl/storage/s3_client.py (3)
16-19: Consider making .env file loading optional.The current implementation raises an error if the
.envfile can't be loaded, which might be problematic in environments where configuration is provided through system environment variables rather than a.envfile (like in production deployments with containerization).Since there's already robust checking for required environment variables later in the constructor (lines 28-46), consider making the
.envfile loading optional.- loaded = load_dotenv() - if not loaded: - raise ValueError("Failed to load environment variables") + # Load environment variables from .env file if present + load_dotenv()
16-19: Consider providing configuration options for dotenv.The
load_dotenv()function supports various configuration options like specifying a custom path to the.envfile or controlling whether existing environment variables should be overridden. Consider adding flexibility by allowing these options to be configured.- loaded = load_dotenv() - if not loaded: - raise ValueError("Failed to load environment variables") + # Allow customizing the .env file location via environment variable + dotenv_path = os.getenv("DOTENV_PATH", ".env") + loaded = load_dotenv(dotenv_path=dotenv_path, override=False) + if not loaded and os.getenv("REQUIRE_DOTENV", "false").lower() == "true": + raise ValueError(f"Failed to load environment variables from {dotenv_path}")
16-46: Consider updating documentation for environment setup.Now that the class explicitly loads environment variables from a
.envfile, it would be helpful to update any documentation to inform users about this behavior and the expected format of the.envfile. This is particularly important for new developers joining the project.Consider adding a docstring to the
__init__method explaining the environment setup requirements:def __init__(self): + """ + Initialize the S3 client by loading environment variables and configuring the connection. + + Environment variables are loaded from a .env file in the project root. + Required environment variables: + - AWS_ENDPOINT_URL: The S3 endpoint URL + - AWS_ACCESS_KEY_ID: AWS access key + - AWS_SECRET_ACCESS_KEY: AWS secret key + - AWS_S3_BUCKET: S3 bucket name + - AWS_REGION: AWS region + - AWS_SECURE: Whether to use HTTPS (defaults to "true") + + Raises: + ValueError: If environment variables cannot be loaded or required variables are missing + """ loaded = load_dotenv()
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hivemind_etl/storage/s3_client.py(1 hunks)
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🔇 Additional comments (1)
hivemind_etl/storage/s3_client.py (1)
11-11:Details
✅ Verification successful
Ensure python-dotenv is added to project dependencies.
The code now imports the
load_dotenvfunction from thedotenvpackage, so make sure this dependency is included in your project's requirements file (e.g.,requirements.txtorsetup.py).
🏁 Script executed:
#!/bin/bash # Check if python-dotenv is in requirements files if [ -f requirements.txt ]; then echo "Checking requirements.txt for python-dotenv..." grep -i "python-dotenv\|dotenv" requirements.txt fi if [ -f setup.py ]; then echo "Checking setup.py for python-dotenv..." grep -i "python-dotenv\|dotenv" setup.py fi if [ -f pyproject.toml ]; then echo "Checking pyproject.toml for python-dotenv..." grep -i "python-dotenv\|dotenv" pyproject.toml fiLength of output: 262
No action needed:
python-dotenvis already declared in requirements.txt
Thepython-dotenv>=1.0.0, <2.0.0entry confirms theload_dotenvimport is supported.
| loaded = load_dotenv() | ||
| if not loaded: | ||
| raise ValueError("Failed to load environment variables") | ||
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💡 Verification agent
🧩 Analysis chain
Consider impact on testing environments.
This change could affect unit tests that rely on mocked environment variables. Ensure that your testing setup properly handles the .env file loading, either by providing a test .env file or by mocking the load_dotenv function.
🏁 Script executed:
#!/bin/bash
# Check for test files that might be affected
echo "Checking for tests that use S3Client:"
fd -e py "test.*\.py" | xargs grep -l "S3Client"
echo "Checking for test environment setup:"
fd -e py "test.*\.py" | xargs grep -l "dotenv\|getenv\|environ"Length of output: 334
Ensure tests handle the new .env loading check
The added guard in hivemind_etl/storage/s3_client.py will raise a ValueError if load_dotenv() returns False, which can break existing unit tests that set environment variables via mocks rather than an actual .env file. Please update your testing setup to account for this:
• Tests referencing environment setup (may be affected):
test_run_workflow.pytests/unit/test_website_etl.py
• Consider one of the following fixes:
- Mock
load_dotenv()in these tests so it always returnsTrue. - Provide a lightweight test
.envfixture loaded before S3Client is instantiated. - Refactor
S3Clientto accept an injectable “dotenv loader” or to skip the check under a test flag.
🤖 Prompt for AI Agents
In hivemind_etl/storage/s3_client.py around lines 16 to 19, the code now raises
a ValueError if load_dotenv() returns False, which can break unit tests that
mock environment variables without an actual .env file. To fix this, update the
affected tests (e.g., test_run_workflow.py and tests/unit/test_website_etl.py)
by either mocking load_dotenv() to always return True, providing a minimal test
.env file loaded before S3Client instantiation, or refactoring S3Client to
accept a configurable dotenv loader or skip the check during testing.
Summary by CodeRabbit
.envfile are loaded before use, with clear error messaging if loading fails.