Find python tkinter codes named menu.py, problema_1.py, problema_2.py (calculus from user, hint and detail answer buttons) and respostamultipleimg.py (multiple choice with correction, scroll and images) to create your own menu with your own problems:
https://github.com/drfperez/selectivitat
Read code explanation in the same GitHub page under menupython.txt
Here’s a step-by-step guide to executing Python on Windows 11:
1. Download Python: Go to the official Python website (https://www.python.org/downloads/) and download the latest version of Python for Windows. Choose the installer that matches your system architecture (32-bit or 64-bit).
2. Run the Installer: Once the download is complete, run the installer. Make sure to check the box that says “Add Python to PATH” during the installation process. This step is crucial for being able to run Python from the command line.
3. Verify Installation: After installation, open the Command Prompt or PowerShell. To check if Python is installed and added to the PATH, type python –version and press Enter. This command should display the installed Python version.
4. Run Python Code: To execute Python code, open Command Prompt or PowerShell and type python followed by the Enter key. This will launch the Python interpreter, indicated by the >>> prompt. You can then start entering and executing Python commands line by line.
5. Exit Python: To exit the Python interpreter, type exit() and press Enter, or use the keyboard shortcut Ctrl + Z followed by Enter.
Following these steps should help you install Python on Windows 11 and execute Python code via the command line.
IDLE
To execute IDLE (Integrated Development and Learning Environment) on Windows 11 after installing Python:
Search for IDLE: You can search for IDLE by typing “IDLE” in the Windows search bar.
Run IDLE: Once you find it in the search results, click on it to open the IDLE Python IDE.
Alternatively, you can open IDLE by following these steps:
Press the Windows key + R to open the Run dialog box.
Type idle and press Enter. This should launch the IDLE Python IDE.
After opening IDLE, you can start writing and running your Python code within the IDLE editor.
Using IDLE
Using IDLE (Integrated Development and Learning Environment) for Python involves a few basic steps:
Open IDLE: You can open IDLE by searching for it in the Windows search bar or by pressing Windows key + R to open the Run dialog, then typing idle and pressing Enter.
IDLE Interface: Once opened, IDLE will display a Python shell window, which is an interactive interpreter prompt (marked by >>>). You can type Python code directly into this prompt and press Enter to execute it line by line.
Creating and Running Scripts:
To create a new script, click on “File” in the menu bar and select “New File” or use the shortcut Ctrl + N.
Write your Python code in the newly opened editor window.
To execute the code, click on “Run” in the menu bar and select “Run Module” or use the shortcut F5. This will execute the entire script in the Python shell window.
Saving and Opening Files:
To save a file, click on “File” in the menu bar and select “Save” or use the shortcut Ctrl + S.
To open an existing file, click on “File” and select “Open” or use the shortcut Ctrl + O.
Features:
IDLE offers features like syntax highlighting, auto-indentation, code completion, and debugging tools to help with Python development.
Closing IDLE:
To exit IDLE, simply close the Python shell window and/or any script editor windows that you have open.
IDLE provides a simple environment for both beginners and experienced developers to write and execute Python code, offering an interactive shell as well as a script editor for creating larger Python programs.
Install libraries in idle
In IDLE, you can install Python libraries using the Python package manager called pip. To install libraries in IDLE:
Open IDLE: Launch IDLE by searching for it in the Windows search bar or using the Windows key + R shortcut and typing idle.
Access the Python Shell: In IDLE, you’ll see the Python shell window, indicated by the >>> prompt.
Install Libraries using pip: To install a Python library, type !pip install <library_name> directly into the Python shell and press Enter. For instance, to install the tkinter library, type !pip install tkinter and press Enter.
Example:
!pip install tkinter
Confirmation: Once you press Enter, pip will start downloading and installing the specified library. It will display messages indicating the progress and successful installation.
Remember, this method installs libraries globally, meaning they’ll be accessible across all your Python projects. If you’re working on a specific project, it’s advisable to use a virtual environment to manage dependencies separately.
For larger projects or managing dependencies more effectively, consider using a separate terminal or command prompt outside of IDLE to install libraries. This offers more visibility and control over the installation process.
Separate terminal
Separate terminal, I’m referring to using the system’s command prompt or terminal outside of IDLE.
Here are the steps to use a separate terminal to install Python libraries:
Open Command Prompt or Terminal:
On Windows, you can open the Command Prompt by searching for “Command Prompt” in the Windows search bar or by pressing Windows key + R and typing cmd.
On macOS or Linux, you can open the Terminal by searching for it in the applications or using the keyboard shortcut Ctrl + Alt + T or Cmd + Space and typing “Terminal”.
Navigate to Your Python Environment (Optional):
If you’re using a virtual environment for your project, navigate to your project’s directory using the cd command. For instance, if your project is in C:\Projects\my_project, type cd C:\Projects\my_project in the Command Prompt.
Install Libraries using pip:
Type pip install <library_name> in the Command Prompt and press Enter. For example, to install the tkinter library, type pip install tkinter and press Enter.
Example:
pip install tkinter
Confirmation: Pip will download and install the specified library, displaying progress and installation messages in the terminal. Once completed, the library will be available for use in your Python projects.
Using the command prompt or terminal provides a more comprehensive view of the installation process, especially when working with multiple libraries or larger projects. It’s a good practice to utilize separate terminals for managing dependencies and libraries in Python projects.
Step-by-step instructions to set up Visual Studio Code as a Python editor:
1. Download and Install Visual Studio Code (VS Code):
2. Go to the official Visual Studio Code website (https://code.visualstudio.com/).
Download the installer for Windows.
Run the installer and follow the installation instructions.
3. Install the Python Extension: Open Visual Studio Code after installation. Go to the Extensions view by clicking on the square icon on the left sidebar or using the shortcut Ctrl + Shift + X.
Search for “Python” in the Extensions Marketplace.
Select the official Python extension published by Microsoft and click “Install”.
Install Python:
If you haven’t installed Python yet, download it from the official website (https://www.python.org/downloads/) and follow the installation instructions. Ensure to check the box that says “Add Python to PATH” during installation.
Set Python Interpreter in VS Code:
4. Open your Python file or create a new one in Visual Studio Code.
At the bottom-left corner, click on the Python interpreter version.
If Python was installed correctly and added to PATH, it should automatically detect the Python interpreter. If not, you’ll need to select the interpreter from the list (e.g., python.exe or python3.exe).
Writing and Running Python Code:
5. Start writing your Python code in the VS Code editor.
To run your code, use the shortcut Ctrl + Shift + P to open the command palette, then type and select “Python: Run Python File in Terminal”.
Alternatively, you can run the code by right-clicking in the editor and selecting “Run Python File in Terminal”.
These steps should help you set up Visual Studio Code as your Python editor and run Python code within the VS Code environment.
Create virtual environment
To create a virtual environment in Python, you can use the venv module, which comes built-in with Python (versions 3.3 and later). Here are the steps:
Using Command Prompt or Terminal:
Open Command Prompt or Terminal:
Open the Command Prompt on Windows or Terminal on macOS/Linux.
Navigate to the Directory (Optional):
Use the cd command to navigate to the directory where you want to create the virtual environment. For example, cd project_directory.
Create a Virtual Environment:
Type the following command and replace myenv with the desired name for your virtual environment:
For Windows: python -m venv myenv
For macOS/Linux: python3 -m venv myenv
Activate the Virtual Environment:
Activating the virtual environment isolates your Python environment.
For Windows: myenv\Scripts\activate
For macOS/Linux: source myenv/bin/activate
Install Libraries in the Virtual Environment:
Once the virtual environment is activated, any libraries you install using pip will be isolated within this environment.
Deactivate the Virtual Environment (when finished):
To deactivate the virtual environment and return to the global Python environment, simply type deactivate and press Enter in the Command Prompt or Terminal.
Using virtual environments is a best practice in Python development, as it allows you to isolate project dependencies and avoid conflicts between different projects’ libraries and versions.
You can create and manage virtual environments within Visual Studio Code (VS Code) or Mu editor using the integrated terminal.
Visual Studio Code (VS Code):
1. Open VS Code.
Open Integrated Terminal:
Press Ctrl + to open the integrated terminal within VS Code.
2. Navigate to Your Project Directory:
Use the cd command to navigate to your project directory where you want to create the virtual environment.
3. Create a Virtual Environment:
Use the following command to create a virtual environment named myenv (replace myenv with your preferred name):
python -m venv myenv
Activate the Virtual Environment:
For Windows:
myenv\Scripts\activate
For macOS/Linux:
source myenv/bin/activate
4. Install Libraries and Run Code:
Once activated, any libraries you install using pip will be specific to this virtual environment. You can run your Python code in this activated environment.
Mu Editor:
In Mu editor, the virtual environment setup might need to be done through an external terminal or command prompt.
1. Open Mu Editor.
Open External Terminal:
Mu might not have an integrated terminal for this purpose. Open the terminal or command prompt outside of Mu.
2. Navigate to Your Project Directory.
3. Create a Virtual Environment:
Use the python -m venv myenv command to create a virtual environment as explained above.
Activate the Virtual Environment:
Use the activation commands mentioned earlier for Windows or macOS/Linux.
4. Install Libraries and Run Code:
5. Once activated, install libraries using pip and execute your Python code within this activated environment.
Both VS Code and Mu allow you to access and use virtual environments through the integrated or external terminal, providing a way to manage project-specific dependencies and environments easily.
About pip
You can check if pip is installed by opening Command Prompt and typing pip –version. If it’s installed, it will display the version number; if not, it’ll show an error.
If pip isn’t installed, you can download get-pip.py from the official site (https://bootstrap.pypa.io/get-pip.py), then run it using Python by executing python get-pip.py in Command Prompt. This should install pip for you.
You can upgrade pip by running python -m pip install –upgrade pip in Command Prompt. This command will upgrade pip to the latest version available.
Command line commands
Here’s a summary of some useful command line codes:
General Command Line Codes:
ls – List files and directories in the current location.
cd – Change directory.
mkdir – Create a new directory.
rm – Remove files or directories.
cp – Copy files or directories.
mv – Move or rename files or directories.
pwd – Print the current working directory.
cat – Display contents of a file.
grep – Search for specific patterns in files.
chmod – Change file permissions.
Executing a Python File:
To execute a Python file in the command line:
Navigate to the directory containing the Python file using cd.
Use python filename.py or python3 filename.py (depending on the Python version) to execute the file.
These commands should help you navigate and perform various tasks in the command line, as well as execute Python scripts easily.
List files and directories: Use ls to see what’s in the current directory.
Change directory: Apply cd directory_name to move into a specific directory. For example, cd Documents moves you into the “Documents” directory.
Go up one directory: Utilize cd .. to move up one level in the directory structure.
Absolute path: Use an absolute path (e.g., cd /path/to/directory) to directly navigate to a specific location from anywhere in the system.
Print the current working directory: Use pwd to display the current directory path.
Combining these commands allows you to move around and access different directories within the command line interface.
import cv2
# Load the pre-trained Haar cascade for face detection
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + ‘haarcascade_frontalface_default.xml’)
# Read an image from file or capture it from a camera
image = cv2.imread(‘path/to/your/image.jpg’)
# Convert the image to grayscale for face detection
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Detect faces in the image
faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
# Draw rectangles around the detected faces
for (x, y, w, h) in faces:
cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)
# Display the result
cv2.imshow(‘Detected Faces’, image)
cv2.waitKey(0)
cv2.destroyAllWindows()