Last Updated: 2020-06-17
- Udacity Python Course
- Audacity Developers
- Audacity Command Line Mode
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- Audacity Command Line
These commands were originally written for scripting Audacity, e.g via a Python script that uses mod-script-pipe. The commands though are also present in the menu, available from macros, and available from within Nyquist using (AUD-DO 'command') Scriptables II (unassigned) Like Scriptables I, but these ones are less commonly used from the menu. To change the Python interpreter, select the interpreter currently displayed in blue bar on the bottom of your VS Code window or open the Command Palette (Ctrl+Shift+P) and enter the command Python: Select Interpreter. This will display a list of the Python interpreters that you currently have installed. As far as I see Audacity plots the magnitude spectrum, i.e. The absolute value of the fourier transform of the first 2048 samples. You plot the maximum amplitude in all time chunks relating to each frequency bin of the short time fourier transform. Maybe this fits your needs. Noise reduction in python using ΒΆ This algorithm is based (but not completely reproducing) on the one outlined by Audacity for the noise reduction effect (Link to C code) The algorithm requires two inputs: A noise audio clip comtaining prototypical noise of the audio clip.
Cloud SQL is a fully-managed database service that makes it easy to set up, maintain, manage, and administer your relational databases on Google Cloud Platform.
Udacity Python Course
In this codelab, you'll write a Cloud Function in Python. The function:
- Connects to a Cloud SQL Database instance.
- Sends an insert statement to a table in the database.
- How to access the Cloud Functions web UI in the Google Cloud Console.
- How to create a Cloud Function.
- How to test a Cloud Function.
- How to connect to a Cloud SQL database instance (either MySQL or PostgreSQL) using Python.
- How to write to a Cloud SQL database using Python.
- A browser, such as Chrome or Firefox.
- A Google Cloud Platform project that contains your Cloud SQL instance.
- If you don't already have one, we have a tutorial for that. Do all the steps except for deleting the instance.
- Your instance contains a MySQL or PostgreSQL database with a table.
- Your instance connection name, the database and table names, the database user name and the user's password.
- You can find the connection_name in the Console UI. Navigate to your SQL instance's Overview page. The connection name is in the format: PROJECT_ID:REGION:INSTANCE_NAME
- The database names are your own. If you have not already created a Cloud SQL database, we have a tutorial for that. Here is an example of a simple database and table for MySQL:
- CREATE DATABASE library;
- USE library;
- CREATE TABLE books (title VARCHAR(100));
- INSERT into books (title) VALUES ('Cloud SQL for Winners');
- A Service account with the Cloud SQL Client role.
- In the Console UI, navigate to the IAM & Admins > IAM page.
- You can use the default Compute Engine service account. It has the suffix compute@developer.gserviceaccount.com.
- Select Edit using the pencil icon.
- Click ADD ANOTHER ROLE and add Cloud SQL > Client.
- Click SAVE.
The Cloud Function code for connecting to a Cloud SQL database is right here. Some of the variable values depend on whether your Cloud SQL database is MySQL or PostgreSQL, and depend on your own database information.
The Cloud Functions UI in the Cloud Console includes a text editor. You can copy/paste and edit the code there, or edit the code locally first, and then copy/paste it into the UI.
main.py
- In a browser, go to the Google Cloud Platform Console UI.
- Select Cloud Functions from the Navigation menu.
- Click CREATE FUNCTION on the button bar.
- Enter a name for the function.
- Select the HTTP trigger. (Make a note of the URL displayed beneath the trigger item. It will be in this format: https://REGION-PROJECT_ID.cloudfunctions.net/FUNCTION_NAME)
- Select Inline editor for the source code option.
- Select Python 3.7 for the runtime option.
- In the source code editor windows, delete the existing content for both requirements.txt and main.py, and replace them with your edited versions of the code above.
- Enter insert as the name of the Function to execute.
- In the Advanced options, select a Service account that has the Cloud SQL Client role.
- Click Create and wait for the spinner to stop. A green check appears when the function is ready to use.
- In a browser, go to the Google Cloud Platform Console UI.
- Select Cloud Functions from the Navigation menu.
- Click on the name of the function you created earlier.
- Select the TESTING link in the middle of the page.
- Select TEST THE FUNCTION.
- The result should appear: ok (If the test fails, you'll see a stack trace to help with debugging.)
- In a browser, go to the URL that you saved earlier, when you created the function.
- The ok result should appear in the browser as well.
Congratulations, you've successfully built a Cloud Function that works with Cloud SQL.
Audacity Developers
Specifically, you've created a Cloud Function that connects and writes to a Cloud SQL database instance.