Merge pull request #9 from JustinFrizzell/config-file-names

Config file names

README.md

@@ -11,13 +11,13 @@
 <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
 </p>
 
-**SQLconnect** is a Python package designed to simplify the process of connecting to SQL databases. It uses a `connections.yaml` file for database configuration and a `.env` file for secure credentials management. SQLconnect supports executing SQL from `.sql` files or Python strings, and retrieving data into pandas DataFrames. This package is particularly useful for data analysts and developers who need a straightforward way to interact with SQL databases.
+**SQLconnect** is a Python package designed to simplify the process of connecting to SQL databases. It uses a `sqlconnect.yaml` file for database configuration and a `sqlconnect.env` file for secure credentials management. SQLconnect supports executing SQL from `.sql` files or Python strings, and retrieving data into pandas DataFrames. This package is particularly useful for data analysts and developers who need a straightforward way to interact with SQL databases.
 
 ## Features
 
-- Allows easy configuration and management of database connections using a `connections.yaml` file.
+- Allows easy configuration and management of database connections using a `sqlconnect.yaml` file.
 
-- Supports the use of a `.env` file for secure storage of database credentials, enhancing security.
+- Supports the use of a `sqlconnect.env` file for secure storage of database credentials, enhancing security.
 
 - Leverages SQLAlchemy for database connections, providing a robust and flexible framework for SQL operations.
 
@@ -35,7 +35,7 @@ pip install sqlconnect
 
 ## Configuration
 
-To use SQLconnect, create a `connections.yaml` file in the root of your project (or in your home directory) with the following example structure:
+To use SQLconnect, create a `sqlconnect.yaml` file in the root of your project (or in your home directory) with the following example structure:
 
 ```yaml
 connections:
@@ -44,13 +44,13 @@ connections:
     odbc_driver: 'SQL+Server'
     server: 'prod-server.database.com'
     database: 'ProdDB'
-    username: '${DB_PROD_USERNAME}' # References DB_PROD_USERNAME in .env
-    password: '${DB_PROD_PASSWORD}' # References DB_PROD_PASSWORD in .env
+    username: '${DB_PROD_USERNAME}' # References DB_PROD_USERNAME in sqlconnect.env
+    password: '${DB_PROD_PASSWORD}' # References DB_PROD_PASSWORD in sqlconnect.env
     options:
       - 'Trusted_Connection=No'
 ```
 
-Also create a `.env` file in the root of your project (or in your home directory) with the following example structure:
+Also create a `sqlconnect.env` file in the root of your project (or in your home directory) with the following example structure:
 
 ```bash
 # This file should be kept secure and not checked into version control (add to .gitignore)
@@ -68,7 +68,7 @@ Here's a quick example to get you started:
 ```python
 import sqlconnect as sc
 
-# Set up a database connection, all configuration is handled with connections.yaml and .env
+# Set up a database connection, all configuration is handled with sqlconnect.yaml and sqlconnect.env
 connection = sc.Sqlconnector("Database_PROD")
 
 # Assign the results of a query to a pandas DataFrame

docs/index.rst

@@ -20,7 +20,7 @@
    </div>
    <div style="height: 20px;"></div> <!-- Spacer -->
 
-**SQLconnect** is a Python package designed to simplify the process of connecting to SQL databases. It uses a ``connections.yaml`` file for database configuration and a ``.env`` file for secure credentials management. SQLconnect supports executing SQL from ``.sql`` files or Python strings, and retrieving data into pandas DataFrames. This package is particularly useful for data analysts and developers who need a straightforward way to interact with SQL databases.
+**SQLconnect** is a Python package designed to simplify the process of connecting to SQL databases. It uses a ``sqlconnect.yaml`` file for database configuration and a ``sqlconnect.env`` file for secure credentials management. SQLconnect supports executing SQL from ``.sql`` files or Python strings, and retrieving data into pandas DataFrames. This package is particularly useful for data analysts and developers who need a straightforward way to interact with SQL databases.
 
 Contents
 ========

docs/tutorial.md

@@ -2,7 +2,7 @@
 
 ## Configuration
 
-To use SQLconnect, create a `connections.yaml` file in the root of your project (or in your home directory) with the following example structure:
+To use SQLconnect, create a `sqlconnect.yaml` file in the root of your project (or in your home directory) with the following example structure:
 
 ```yaml
 connections:
@@ -11,13 +11,13 @@ connections:
     odbc_driver: 'SQL+Server'
     server: 'prod-server.database.com'
     database: 'ProdDB'
-    username: '${DB_PROD_USERNAME}' # References DB_PROD_USERNAME in .env
-    password: '${DB_PROD_PASSWORD}' # References DB_PROD_PASSWORD in .env
+    username: '${DB_PROD_USERNAME}' # References DB_PROD_USERNAME in sqlconnect.env
+    password: '${DB_PROD_PASSWORD}' # References DB_PROD_PASSWORD in sqlconnect.env
     options:
       - 'Trusted_Connection=No'
 ```
 
-Also create a `.env` file in the root of your project (or in your home directory) with the following example structure:
+Also create a `sqlconnect.env` file in the root of your project (or in your home directory) with the following example structure:
 
 ```bash
 # This file should be kept secure and not checked into version control (add to .gitignore)
@@ -35,7 +35,7 @@ Here's a quick example to get you started:
 ```python
 import sqlconnect as sc
 
-# Set up a database connection, all configuration is handled with connections.yaml and .env
+# Set up a database connection, all configuration is handled with sqlconnect.yaml and sqlconnect.env
 connection = sc.Sqlconnector("Database_PROD")
 
 # Assign the results of a query to a pandas DataFrame

setup.py

@@ -3,7 +3,7 @@
 
 setuptools.setup(
     name="sqlconnect",
-    version="0.2.0",
+    version="0.2.1",
     author="Justin Frizzell",
     description="Package to simplify connections to SQL databases.",
     long_description=Path("README.md").read_text(encoding="utf-8"),
@@ -12,7 +12,6 @@
     project_urls={
         "Documentation": "https://sqlconnect.readthedocs.io/en/latest/",
         "Source": "https://github.com/JustinFrizzell/sqlconnect",
-        # You can add other links here if necessary
     },
     packages=setuptools.find_packages(),
     install_requires=["pandas", "sqlalchemy", "pyyaml", "pyodbc", "python-dotenv"],

sqlconnect/config.py

@@ -18,7 +18,7 @@
     - os: Used for environment variable management.
     - pathlib: For file path manipulations.
     - yaml: Required for parsing YAML configuration files.
-    - dotenv: Used for loading environment variables from '.env' files.
+    - dotenv: Used for loading environment variables from 'sqlconnect.env' files.
 
 Example Usage:
     # Used within Sqlconnector class
@@ -29,7 +29,7 @@
     - Configuration files should define connection parameters like 'sqlalchemy_driver', 'odbc_driver', 
       'server', 'database', and optionally 'username', 'password'.
     - Usernames and passwords should be referenced as environment variables in the format '${ENV_VAR}'.
-    - Attempts to load '.env' files from the current directory or the user's home directory for environment 
+    - Attempts to load 'sqlconnect.env' files from the current directory or the user's home directory for environment 
       variables.
 """
 import os
@@ -52,7 +52,7 @@ def get_connection_config(connection_name: str, config_path: str = None) -> dict
         The name of the connection for which the configuration is to be retrieved.
     config_path : str, optional
         The path to the configuration file. If not provided, the function searches
-        in 'connections.yaml' or 'connections.yml' in the current directory, and
+        in 'sqlconnect.yaml' or 'sqlconnect.yml' in the current directory, and
         then in the user's home directory.
 
     Returns
@@ -83,10 +83,10 @@ def get_connection_config(connection_name: str, config_path: str = None) -> dict
         [Path(config_path)]
         if config_path
         else [
-            Path("connections.yaml"),
-            Path("connections.yml"),
-            Path.home() / "connections.yaml",
-            Path.home() / "connections.yml",
+            Path("sqlconnect.yaml"),
+            Path("sqlconnect.yml"),
+            Path.home() / "sqlconnect.yaml",
+            Path.home() / "sqlconnect.yml",
         ]
     )
 
@@ -114,8 +114,8 @@ def get_connection_config(connection_name: str, config_path: str = None) -> dict
             return connection_config
 
     raise FileNotFoundError(
-        f"Config file not found in {Path('connections.yaml').absolute()} "
-        f"or {Path.home() / 'connections.yaml'}"
+        f"Config file not found in {Path('sqlconnect.yaml').absolute()} "
+        f"or {Path.home() / 'sqlconnect.yaml'}"
     )
 
 
@@ -145,8 +145,8 @@ def get_db_url(connection_config: dict) -> str:
     ------
     EnvironmentError
         If 'username' and/or 'password' are specified as environment variables in the configuration
-        and these variables are not found in either the current directory's '.env' file or the
-        user's home directory '.env' file.
+        and these variables are not found in either the current directory's 'sqlconnect.env' file or the
+        user's home directory 'sqlconnect.env' file.
 
     Examples
     --------
@@ -163,7 +163,7 @@ def get_db_url(connection_config: dict) -> str:
 
     Notes
     -----
-    The function checks for '.env' files in the current directory and the user's home directory
+    The function checks for 'sqlconnect.env' files in the current directory and the user's home directory
     for environment variables if 'username' and 'password' are provided as environment variable keys.
     It uses `os.getenv` to retrieve these environment variables.
     """
@@ -177,10 +177,10 @@ def get_db_url(connection_config: dict) -> str:
     # Check for username and password
     auth_details = ""
     if "username" in connection_config and "password" in connection_config:
-        if Path(".env").exists():
-            load_dotenv(Path(".env"))
+        if Path("sqlconnect.env").exists():
+            load_dotenv(Path("sqlconnect.env"))
         else:
-            home_env_path = Path.home() / ".env"
+            home_env_path = Path.home() / "sqlconnect.env"
             if home_env_path.exists():
                 load_dotenv(home_env_path)
 
@@ -192,7 +192,7 @@ def get_db_url(connection_config: dict) -> str:
         if username is None or password is None:
             raise EnvironmentError(
                 f"Environment variables '{env_username_key}' and/or '{env_password_key}' not "
-                f"found in {Path('.env').absolute()} or {Path.home() / '.env'}"
+                f"found in {Path('sqlconnect.env').absolute()} or {Path.home() / 'sqlconnect.env'}"
             )
 
         auth_details = f"{username}:{password}@"

sqlconnect/connector.py

@@ -16,7 +16,7 @@
 Example:
     >>> import sqlconnect as sc
     >>> 
-    >>> # Set up a database connection. All configuration is handled with connections.yaml and .env
+    >>> # Set up a database connection. All configuration is handled with sqlconnect.yaml and sqlconnect.env
     >>> connection = sc.Sqlconnector("Database_PROD")
     >>> 
     >>> # Assign the results of a query to a pandas DataFrame

tests/test_sqlconnect_config.py

@@ -30,7 +30,7 @@
 @pytest.fixture
 def mock_config_file_yaml(tmp_path):
     # Create a temporary YAML config file for testing
-    config_file = tmp_path / "connections.yaml"
+    config_file = tmp_path / "sqlconnect.yaml"
     yaml_content = yaml.dump(TEST_CONFIG_DICT)
     config_file.write_text(yaml_content)