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Copy file name to clipboardExpand all lines: docs/python/environments.md
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@@ -18,7 +18,7 @@ Python environments are managed via the Python Environments extension. The exten
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The Python Environments view can be accessed from the Activity Bar and provides a unified interface for managing your Python projects and environments:
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![Python Environments view in VS Code (Screenshot placeholder)]()
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The view consists of two main sections:
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### Quick Create
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Quick create allows for a one-click environment creation flow, choosing the defaults for you. Quick create configures a virutal environment using the default environment manager and the latest Python version, and installing dependencies found in a `requirements.txt` or `pyproject.toml` file.
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Quick create allows for a one-click environment creation flow, choosing the defaults for you. Quick create configures a virtual environment using the default environment manager and the latest Python version, and installing dependencies found in a `requirements.txt` or `pyproject.toml` file.
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1. Open the Python Environments view from the Activity Bar
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2. Under "Environment Managers", find your preferred environment manager (e.g., venv)
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- The latest Python version
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- Workspace dependencies (if available)
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### Custom environment creation
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For more control over your environment settings, choose custom environment creation.
Copy file name to clipboardExpand all lines: docs/python/python-quick-start.md
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@@ -28,7 +28,9 @@ You can quickly create a scaffolded Python project for scripts or a Python packa
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2. Under "Python Projects", select **Create New**.
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2. In the "Python Projects" section, select **Add Python Project** and **Create New**.
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3. Choose from available project templates:
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-**Package**: A structured Python package with `__init__.py` and setup configurations.
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When you launch VS Code for the very first time, you will need to install the Python extension to get Python-specific features and UI. Let’s look at the UI after installing the Python extension:
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Copy file name to clipboardExpand all lines: docs/python/python-tutorial.md
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1. Open the Python Environments view from the Activity Bar on the left side of VS Code.
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2. Under "Environment Managers", select your preferred environment manager (such as venv).
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3. Select **Create Environment** or use the **Quick Create** option which automatically creates a new virtual environment using your default environment manager and the latest Python version.
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2. Under "Environment Managers", select the `+` next to your preferred environment manager (such as Venv).
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[TODO: Add screenshot of Python Environments Quick Create option in VS Code]
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3. Select the **Quick Create** option which automatically creates a new virtual environment using your default environment manager and the latest Python version.
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4. Follow the prompts to specify the Python version and environment name.
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4.After selecting the interpreter, a notification will show the progress of the environment creation and the environment folder (`/.venv`) will appear in your workspace.
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4.A notification will show the progress of the environment creation and the environment folder (`/.venv`) will appear in your workspace.
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5. Once created, your new environment will be available in the list and automatically selected for your workspace.
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> **Note**: For additional information about virtual environments, or if you run into an error in the environment creation process, see [Environments](/docs/python/environments.md#creating-environments).
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1. Open the **Python Environments** view from the Activity Bar.
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2. Locate your active environment under either "Python Projects" or "Environment Managers".
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2. Locate your active environment under "Environment Managers".
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3. Expand your environment and the **Packages** node to view packages currently available in your environment. Select the package icon on the environment.
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4. Select **Search common PyPI packages** and search for and select `numpy`.
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5. Once installed, the package will appear in your environment's package list.
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### Using the terminal to install packages
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Alternatively, you can install packages using the terminal:
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