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# Thanks to Sumarigo-MSFT
# https://learn.microsoft.com/en-us/answers/questions/1105984/delete-folder-in-storage-account-through-sdk

from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient
account_url = "https://{container}.blob.core.windows.net"
default_credential = DefaultAzureCredential()

# Create the BlobServiceClient object
blob_service_client = BlobServiceClient(account_url, credential=default_credential)

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import csv
import sys
import os

# example usage: python split.py example.csv 200
# above command would split the `example.csv` into smaller CSV files of 200 rows each (with header included)
# if example.csv has 401 rows for instance, this creates 3 files in same directory:
#   - `example_1.csv` (row 1 - 200)
#   - `example_2.csv` (row 201 - 400)
#   - `example_3.csv` (row 401)

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/*
Notes:

Despite Scala's appearances, it is, in fact, a Statically Typed language.
It has just eliminated a great deal of the "type vomit" people are used
to seeing in Statically Typed languages (e.g. C, C++, Java). It often
can infer the type on its own. It also combines functional and
object-oriented programming paradigms in a fashion that feels similar
to Python.
*/

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Amazon Rekognition - Python Code Samples

1. Labels Detection
2. Faces Detection
3. Faces Comparison
4. Faces Indexing
5. Faces Search

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def search_text(text, keyword):
	with open(text,'r') as t:
		for period in t:
			for sentence in period.split('.'):
				if keyword in sentence:
					print sentence 

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import os 

def list_dir(parent):
    dir = os.listdir(parent)
    for lists in dir: 
        directory = os.path.join(parent, lists) 
        print directory 
        if os.path.isdir(directory): 
            list_dir(directory)

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import pandas as pd
from leilao.models import Lance

lista = ['PTN07-17A-SUCATAS', 'PTN07-17B-SUCATAS', 'PTN07-17C-SUCATAS','PTN07-17D-SUCATAS']

queryset = (
    Lance.objects
        .filter(lote__leilao__nome__in=lista)
        .values('lote__leilao__nome', 'user__userprofile__nome', 'user__email', 'user__userprofile__telefone1', 'user__userprofile__telefone2')
        .distinct()