Not able to access zip/exe from ADLSv2 into synapse

I have a zip file containing images uploaded to my storage account (ADLSv2)

storage acc: samplesa
container: samplecontainersa
data1: /folder1/sample1.exe
data2: /folder1/sample2.zip

I need to now read this zip, extract all sample images into a Pyspark dataframe in my synapse environment. Following is my code:

import zipfile
from pyspark.sql.functions import map_zip_with
zip_path = "abfss://samplecontainersa@samplesa.dfs.core.windows.net/folder1/sample2.zip"
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
    file_list = zip_ref.namelist()
image_files = [f for f in file_list if f.lower().endswith(('.jpg', '.jpeg', '.png'))]
image_data = [(f, zip_ref.read(f)) for f in image_files]
df = spark.createDataFrame(image_data, ["filename", "image_bytes"])
df.show()

However, I am getting this following error:

No such file or directory: 'abfss://samplecontainersa@samplesa.dfs.core.windows.net/folder1/sample2.zip'

I can read other csv/txt files in the same directory, however only having issues with accessing exe and zip. Any thoughts? Thanks!

You can follow the below approach to extract all sample images from a .zip file into a Pyspark dataframe:

Read the Zip file and extract them to temporary file path and verify if images are uploaded to the path using below code:

  # Download the zip file
blob_client = blob_service_client.get_blob_client(container=container_name, blob="folder1/sample2.zip")
downloaded_blob = blob_client.download_blob().readall()

# Extract the zip file and upload images to ADLS
with zipfile.ZipFile(BytesIO(downloaded_blob)) as z:
    for file_info in z.infolist():
        if file_info.filename.endswith(('.jpg', '.png')):
            print(f"Extracting and uploading {file_info.filename}")
            with z.open(file_info.filename) as file:
                # Define the blob client for each file
                file_name = os.path.basename(file_info.filename)
                blob_client = blob_service_client.get_blob_client(container=container_name, blob=f"folder1/images/{file_name}")
                blob_client.upload_blob(file, overwrite=True)

# Verify if images are uploaded
blobs_list = blob_service_client.get_container_client(container_name).list_blobs(name_starts_with="folder1/images/")
for blob in blobs_list:
    print(f"Uploaded file: {blob.name}")

Read the extracted images into dataframe using below code:

df_images = spark \
    .read \
    .format("binaryFile") \
    .option("pathGlobFilter", "*.{jpg,png}") \
    .load("abfss://samplecontainersa@badls.dfs.core.windows.net/folder1/images/")
display(df_images)

You will get images as dataframe as shown below:

Here is the complete code for your reference:

import zipfile
from azure.storage.blob import BlobServiceClient
from io import BytesIO
from azure.storage.blob import BlobClient
import os

# Initialize connection to your ADLSv2
account_name = "<accountName>"
account_key = "<accountKey>"
container_name = "<containerName>"
blob_service_client = BlobServiceClient(account_url=f"https://{account_name}.blob.core.windows.net", credential=account_key)

# Download the zip file
blob_client = blob_service_client.get_blob_client(container=container_name, blob="folder1/sample2.zip")
downloaded_blob = blob_client.download_blob().readall()

# Extract the zip file and upload images to ADLS
with zipfile.ZipFile(BytesIO(downloaded_blob)) as z:
    for file_info in z.infolist():
        if file_info.filename.endswith(('.jpg', '.png')):
            print(f"Extracting and uploading {file_info.filename}")
            with z.open(file_info.filename) as file:
                # Define the blob client for each file
                file_name = os.path.basename(file_info.filename)
                blob_client = blob_service_client.get_blob_client(container=container_name, blob=f"folder1/images/{file_name}")
                blob_client.upload_blob(file, overwrite=True)

# Verify if images are uploaded
blobs_list = blob_service_client.get_container_client(container_name).list_blobs(name_starts_with="folder1/images/")
for blob in blobs_list:
    print(f"Uploaded file: {blob.name}")

# Read the extracted images
df_images = spark \
    .read \
    .format("binaryFile") \
    .option("pathGlobFilter", "*.{jpg,png}") \
    .load("abfss://samplecontainersa@badls.dfs.core.windows.net/folder1/images/")

display(df_images)