Radish Logic

How to connect Google Nest to Windows 11 as Speaker

I recently found out that I could connect my Google Nest mini to Windows as a speaker. So in this tutorial, I will guide you on how to connect your Google Nest to your Windows 11 laptop/desktop as a speaker.

The steps also include how to solve the issue of Windows 11 not showing Google Nest as a speaker even though it is already added as a Bluetooth device.

I used a Google Nest Mini to connect to Windows 11 below. The instructions should be the same regardless of your Google Nest speaker model.

How to list files in an S3 bucket folder using boto3 and Python

If you want to list the files/objects inside a specific folder within an S3 bucket then you will need to use the list_objects_v2 method with the Prefix parameter in boto3.

Below are 3 examples codes on how to list the objects in an S3 bucket folder.

What the code does is that it gets all the files/objects inside the S3 bucket named radishlogic-bucket within the folder named s3_folder/ and adds their keys inside a Python list (s3_object_key_list). It then prints each of the object keys in the list and also prints the number of files in the folder.

How to list all objects in an S3 Bucket using boto3 and Python

If you need to list all files/objects inside an AWS S3 Bucket then you will need to use the list_objects_v2 method in boto3.

Below are 3 example codes of how to list all files in a target S3 Bucket.

You can use any of the 3 options since it does the same thing.

It will get all of the files inside the S3 Bucket radishlogic-bucket using Python boto3, put it inside a Python list, then print each object key. It will print the files inside folder recursively, regardless if they are inside a folder or not.

At the end, it will also print the number of items inside the S3 Bucket.

How to delete a file in AWS S3 using boto3 and Python

To delete a file inside an AWS S3 Bucket using Python then you will need to use the delete_object function of boto3.

Below are 3 examples to delete an S3 file.

You can use any of the 3 options since it does the same thing. It will delete the file in S3 with the key of s3_folder/file.txt inside the S3 bucket named radishlogic-bucket using Python boto3.

How to read a file in S3 and store it in a String using Python and boto3

If you want to get a file from an S3 Bucket and then put it in a Python string, try the examples below.

boto3, the AWS SDK for Python, offers two distinct methods for accessing files or objects in Amazon S3: client method and the resource method.

Option 1 uses the boto3.client('s3') method, while options 2 and 3 use the boto3.resource('s3') method.

All 3 options do the exact same thing so get the one that you feel comfortable with or the one that will fit your use case.

How to write Python string to a file in S3 Bucket using boto3

To write a file from a Python string directly to an S3 bucket we need to use the boto3 package.

There are 2 ways to write a file in S3 using boto3. The first is via the boto3 client, and the second is via the boto3 resource. Both of these methods will be shown below.

S3 objects and keys

If you are new to AWS S3, you might be confused with some of the terms. So we’ll define some of them here. If you already know what objects and keys are then you can skip this section.

S3 objects are the same as files. When we run the method put_object what it means is that we are putting a file into S3.

S3 keys are the same as the filename with its full path. So if we want to create an object in S3 with the name of filename.txt within the foobar folder then the key is foobar/filename.txt.

Now that we have clarified some of the AWS S3 terms, follow the details below to start writing Python strings directly to objects in S3.

How to generate S3 presigned URL using boto3 and Python

If you want to give your users temporary access to a private S3 file without giving them access to the AWS console, you will need to generate an S3 presigned URL of your target file.

To generate and test the S3 presigned URL, you can try the code below.

How to read a JSON file in S3 and store it in a Dictionary using boto3 and Python

If you want to get a JSON file from an S3 Bucket and load it into a Python Dictionary then you can use the example codes below.

There are 4 scenarios for the examples scripts below.

AWS boto3 provides 2 ways to access S3 files, the boto3.client('s3') and boto3.resource('s3'). For each of the example scenarios above, a code will be provided for the two methods.

Since both methods will function the same, you can choose whichever method you like.

How to write a Dictionary to JSON file in S3 Bucket using boto3 and Python

If you want to write a python dictionary to a JSON file in S3 then you can use the code examples below.

There are two code examples doing the same thing below because boto3 provides a client method and a resource method to edit and access AWS S3.

Writing Python Dictionary to an S3 Object using boto3 Client

import boto3
import json
from datetime import date

data_dict = {
    'Name': 'Daikon Retek',
    'Birthdate': date(2000, 4, 7),
    'Subjects': ['Math', 'Science', 'History']
}

# Convert Dictionary to JSON String
data_string = json.dumps(data_dict, indent=2, default=str)


# Upload JSON String to an S3 Object
client = boto3.client('s3')

client.put_object(
    Bucket='radishlogic-bucket', 
    Key='s3_folder/client_data.json',
    Body=data_string
)

How to download files from S3 Bucket using boto3 and Python

If you want to download a file from an AWS S3 Bucket using Python, then you can use the sample codes below.

The codes below use AWS SDK for Python named boto3.

boto3 provides three methods to download a file.

download_file()
download_fileobj() – with multipart upload
get_object()

Then for each method, you can use the client class or the resource class of boto3.

Both of the classes will be used for each of the methods above.

Note: All examples will work with any Python3 environment running in Windows, MacOS or Linux operating systems.