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Problem triggering nested dependencies in Azure Function

I have a problem using the videohash package for python when deployed to Azure function.
My deployed azure function does not seem to be able to use a nested dependency properly. Specifically, I am trying to use the package “videohash” and the function VideoHash from it. The
input to VideoHash is a SAS url token for a video placed on an Azure blob storage.  
In the monitor of my output it prints: 
Accessing the sas url token directly takes me to the video, so that part seems to be working.  
Looking at the source code for videohash this error seems to occur in the process of downloading the video from a given url (link:
https://github.com/akamhy/videohash/blob/main/videohash/downloader.py). 
.. where self.yt_dlp_path = str(which("yt-dlp")). This to me indicates, that after deploying the function, the package yt-dlp isn’t properly activated. This is a dependency from the videohash
module, but adding yt-dlp directly to the requirements file of the azure function also does not solve the issue. 
Any ideas on what is happening? 
 
Deploying code to Azure function, which resulted in the details highlighted in the issue description.

I have a work around where you download the video file on you own instead of the videohash using azure.storage.blob
To download you will need a BlobServiceClient , ContainerClient and connection string of azure storage account.
Please create two files called v1.mp3 and v2.mp3 before downloading the video.
file structure:
Complete Code:
import logging
from videohash import VideoHash
import azure.functions as func
import subprocess
import tempfile
import os
from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient
def main(req: func.HttpRequest) -> func.HttpResponse:
# local file path on the server
local_path = tempfile.gettempdir()
filepath1 = os.path.join(local_path, "v1.mp3")
filepath2 = os.path.join(local_path,"v2.mp3")
# Reference to Blob Storage
client = BlobServiceClient.from_connection_string("<Connection String >")
# Reference to Container
container = client.get_container_client(container= "test")
# Downloading the file
with open(file=filepath1, mode="wb") as download_file:
download_file.write(container.download_blob("v1.mp3").readall())
with open(file=filepath2, mode="wb") as download_file:
download_file.write(container.download_blob("v2.mp3").readall())
// video hash code .
videohash1 = VideoHash(path=filepath1)
videohash2 = VideoHash(path=filepath2)
t = videohash2.is_similar(videohash1)
return func.HttpResponse(f"Hello, {t}. This HTTP triggered function executed successfully.")
Output :
Now here I am getting the ffmpeg error which related to my test file and not related to error you are facing.
This work around as far as I know will not affect performance as in both scenario you are downloading blobs anyway

Azure Functions - How to Connect to other services using API connections

I'm new to azure functions, I want to deploy my python code in function app, where my code is linked with SharePoint, Outlook, SQL Server, could some one suggest me the best way to connect all 3 of them in azure functions App....#python #sql #sharepoint #azure

Firstly, would like to discuss about accessing SharePoint files from Azure function, we just need to use few imports for it from VSCode and we also have the python documentation for Office365-Rest-Client.
Below is one of the examples to download a file from SharePoint:
Import os
import tempfile
from office365.sharepoint.client_context import ClientContext
from tests import test_team_site_url, test_client_credentials
ctx = ClientContext(test_team_site_url).with_credentials(test_client_credentials)
# file_url = '/sites/team/Shared Documents/big_buck_bunny.mp4'
file_url = "/sites/team/Shared Documents/report #123.csv"
download_path = os.path.join(tempfile.mkdtemp(), os.path.basename(file_url))
with open(download_path, "wb") as local_file:
file = ctx.web.get_file_by_server_relative_path(file_url).download(local_file).execute_query()
print("[Ok] file has been downloaded into: {0}".format(download_path))
To get all the details of files folders and their operations refer to this GIT link
For connecting to SQL we have a blog which has all insights with Python code, thanks to lieben.

Get Properties of storage blobs returning empty dict

I've just uploaded a 5GB of data and would like to verify that the MD5 sums match. I've calculated this for my local copy of the files, but am having problems fetching ContentMD5 from Azure. So far, I get an empty dict, but I can see the blob names. I've limited it to the first 10 items at the moment, just for debugging. I'm aware that MD5 is different on Azure from a typical md5sum call and have allowed for that locally. But, currently, I cannot see any blob properties. The properties are there when I browse via the Azure console (as is the ContentMD5 property).
Where am I going wrong?
Here's my code at the moment:
import os
from os import sys
from azure.storage.blob import BlobServiceClient
def remote_check(connection_str):
blob_service_client = BlobServiceClient.from_connection_string(connection_str)
container_name = "global"
container = blob_service_client.get_container_client(container=container_name)
blob_list = container.list_blobs()
count = 0
for blob in blob_list:
if count < 10:
blob_client = blob_service_client.get_blob_client(container=container_name, blob=blob)
a = blob_client.get_blob_properties()
print(a.metadata)
print("Blob name: " + str(blob_client.blob_name))
count = count + 1
else:
break
def main():
try:
CONNECTION_STRING = os.environ['AZURE_STORAGE_CONNECTION_STRING']
remote_check(CONNECTION_STRING)
except KeyError:
print("AZURE_STORAGE_CONNECTION_STRING must be set.")
sys.exit(1)
if __name__ == '__main__':
main()

Please make sure you're using the latest version of package azure-storage-blob 12.6.0.
Some properties are in the content_settings, for example, to get content_md5, you should use the following code:
a=blob_client.get_blob_properties()
print(a.content_settings.content_md5)
Here is the my test result:

Maybe you can check the blob properties with a rest (e.g. with an rest client like postman) call described here:
https://learn.microsoft.com/en-us/rest/api/storageservices/get-blob-properties
The "Content-MD5" is returned as HTTP-Response Header.

Python 3 and Azure table storage tablestorageaccount not working

I'm trying to use the sample provided by Microsoft to connect to an Azure storage table using Python. The code below fail because of tablestorageaccount not found. What I'm missing I installed the azure package but still complaining that it's not found.
import azure.common
from azure.storage import CloudStorageAccount
from tablestorageaccount import TableStorageAccount
print('Azure Table Storage samples for Python')
# Create the storage account object and specify its credentials
# to either point to the local Emulator or your Azure subscription
if IS_EMULATED:
account = TableStorageAccount(is_emulated=True)
else:
account_connection_string = STORAGE_CONNECTION_STRING
# Split into key=value pairs removing empties, then split the pairs into a dict
config = dict(s.split('=', 1) for s in account_connection_string.split(';') if s)
# Authentication
account_name = config.get('AccountName')
account_key = config.get('AccountKey')
# Basic URL Configuration
endpoint_suffix = config.get('EndpointSuffix')
if endpoint_suffix == None:
table_endpoint = config.get('TableEndpoint')
table_prefix = '.table.'
start_index = table_endpoint.find(table_prefix)
end_index = table_endpoint.endswith(':') and len(table_endpoint) or table_endpoint.rfind(':')
endpoint_suffix = table_endpoint[start_index+len(table_prefix):end_index]
account = TableStorageAccount(account_name = account_name, connection_string = account_connection_string, endpoint_suffix=endpoint_suffix)

I find the source sample code, and in the sample code there is still a custom module tablestorageaccount.py, it's just used to return TableService. If you already have the storage connection string and want to have a test, you could connect to table directly.
Sample:
from azure.storage.table import TableService, Entity
account_connection_string = 'DefaultEndpointsProtocol=https;AccountName=account name;AccountKey=account key;EndpointSuffix=core.windows.net'
tableservice=TableService(connection_string=account_connection_string)
Also you could refer to the new sdk to connect table. Here is the official tutorial about Get started with Azure Table storage.

FileUploadMiscError while persisting output file from Azure Batch

I'm facing the following error while trying to persist log files to Azure Blob storage from Azure Batch execution - "FileUploadMiscError - A miscellaneous error was encountered while uploading one of the output files". This error doesn't give a lot of information as to what might be going wrong. I tried checking the Microsoft Documentation for this error code, but it doesn't mention this particular error code.
Below is the relevant code for adding the task to Azure Batch that I have ported from C# to Python for persisting the log files.
Note: The container that I have configured gets created when the task is added, but there's no blob inside.
import datetime
import logging
import os
import azure.storage.blob.models as blob_model
import yaml
from azure.batch import models
from azure.storage.blob.baseblobservice import BaseBlobService
from azure.storage.common.cloudstorageaccount import CloudStorageAccount
from dotenv import load_dotenv
LOG = logging.getLogger(__name__)
def add_tasks(batch_client, job_id, task_id, io_details, blob_details):
task_commands = "This is a placeholder. Actual code has an actual task. This gets completed successfully."
LOG.info("Configuring the blob storage details")
base_blob_service = BaseBlobService(
account_name=blob_details['account_name'],
account_key=blob_details['account_key'])
LOG.info("Base blob service created")
base_blob_service.create_container(
container_name=blob_details['container_name'], fail_on_exist=False)
LOG.info("Container present")
container_sas = base_blob_service.generate_container_shared_access_signature(
container_name=blob_details['container_name'],
permission=blob_model.ContainerPermissions(write=True),
expiry=datetime.datetime.now() + datetime.timedelta(days=1))
LOG.info(f"Container SAS created: {container_sas}")
container_url = base_blob_service.make_container_url(
container_name=blob_details['container_name'], sas_token=container_sas)
LOG.info(f"Container URL created: {container_url}")
# fpath = task_id + '/output.txt'
fpath = task_id
LOG.info(f"Creating output file object:")
out_files_list = list()
out_files = models.OutputFile(
file_pattern=r"../stderr.txt",
destination=models.OutputFileDestination(
container=models.OutputFileBlobContainerDestination(
container_url=container_url, path=fpath)),
upload_options=models.OutputFileUploadOptions(
upload_condition=models.OutputFileUploadCondition.task_completion))
out_files_list.append(out_files)
LOG.info(f"Output files: {out_files_list}")
LOG.info(f"Creating the task now: {task_id}")
task = models.TaskAddParameter(
id=task_id, command_line=task_commands, output_files=out_files_list)
batch_client.task.add(job_id=job_id, task=task)
LOG.info(f"Added task: {task_id}")

There is a bug in Batch's OutputFile handling which causes it to fail to upload to containers if the full container URL includes any query-string parameters other than the ones included in the SAS token. Unfortunately, the azure-storage-blob Python module includes an extra query string parameter when generating the URL via make_container_url.
This issue was just raised to us, and a fix will be released in the coming weeks, but an easy workaround is instead of using make_container_url to craft the URL, craft it yourself like so: container_url = 'https://{}/{}?{}'.format(blob_service.primary_endpoint, blob_details['container_name'], container_sas).
The resulting URL should look something like this: https://<account>.blob.core.windows.net/<container>?se=2019-01-12T01%3A34%3A05Z&sp=w&sv=2018-03-28&sr=c&sig=<sig> - specifically it shouldn't have restype=container in it (which is what the azure-storage-blob package is including)