async def translation_status_checks_async(self):
# import libraries
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation.aio import DocumentTranslationClient
from azure.ai.documenttranslation import (BatchDocumentInput,
StorageTarget)
# get service secrets
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_container_url_es = os.environ["AZURE_TARGET_CONTAINER_URL_ES"]
target_container_url_fr = os.environ["AZURE_TARGET_CONTAINER_URL_FR"]
# prepare translation input
batch = [
BatchDocumentInput(
source_url=source_container_url,
targets=[
StorageTarget(target_url=target_container_url_es,
language="es"),
StorageTarget(target_url=target_container_url_fr,
language="fr")
],
storage_type="folder",
prefix="document_2021")
]
# create translation client
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
# run translation job
async with client:
job_detail = await client.create_translation_job(batch)
while True:
job_detail = await client.get_job_status(
job_detail.id) # type: JobStatusDetail
if job_detail.status in ["NotStarted", "Running"]:
await asyncio.sleep(30)
continue
elif job_detail.status in ["Failed", "ValidationFailed"]:
if job_detail.error:
print("Translation job failed: {}: {}".format(
job_detail.error.code, job_detail.error.message))
await self.check_documents(client, job_detail.id)
exit(1)
elif job_detail.status == "Succeeded":
print("We translated our documents!")
if job_detail.documents_failed_count > 0:
await self.check_documents(client, job_detail.id)
break
def sample_batch_translation():
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (DocumentTranslationClient,
BatchDocumentInput,
StorageTarget)
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url_en = os.environ["AZURE_SOURCE_CONTAINER_URL_EN"]
source_container_url_de = os.environ["AZURE_SOURCE_CONTAINER_URL_DE"]
target_container_url_es = os.environ["AZURE_TARGET_CONTAINER_URL_ES"]
target_container_url_fr = os.environ["AZURE_TARGET_CONTAINER_URL_FR"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
batch = [
BatchDocumentInput(
source_url=source_container_url_en,
targets=[
StorageTarget(target_url=target_container_url_es,
language="es"),
StorageTarget(target_url=target_container_url_fr,
language="fr")
]),
BatchDocumentInput(
source_url=source_container_url_de,
targets=[
StorageTarget(target_url=target_container_url_es,
language="es"),
StorageTarget(target_url=target_container_url_fr,
language="fr")
])
]
job_detail = client.create_translation_job(batch) # type: JobStatusDetail
print("Job initial status: {}".format(job_detail.status))
print("Number of translations on documents: {}".format(
job_detail.documents_total_count))
job_result = client.wait_until_done(job_detail.id) # type: JobStatusDetail
if job_result.status == "Succeeded":
print("We translated our documents!")
if job_result.documents_failed_count > 0:
check_documents(client, job_result.id)
elif job_result.status in ["Failed", "ValidationFailed"]:
if job_result.error:
print("Translation job failed: {}: {}".format(
job_result.error.code, job_result.error.message))
check_documents(client, job_result.id)
exit(1)
def sample_translation_status_checks():
import os
import time
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (DocumentTranslationClient,
BatchDocumentInput,
StorageTarget)
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_container_url_es = os.environ["AZURE_TARGET_CONTAINER_URL_ES"]
target_container_url_fr = os.environ["AZURE_TARGET_CONTAINER_URL_FR"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
batch = [
BatchDocumentInput(
source_url=source_container_url,
targets=[
StorageTarget(target_url=target_container_url_es,
language="es"),
StorageTarget(target_url=target_container_url_fr,
language="fr")
],
storage_type="folder",
prefix="document_2021")
]
job_detail = client.create_translation_job(batch)
while True:
job_detail = client.get_job_status(
job_detail.id) # type: JobStatusDetail
if job_detail.status in ["NotStarted", "Running"]:
time.sleep(30)
continue
elif job_detail.status in ["Failed", "ValidationFailed"]:
if job_detail.error:
print("Translation job failed: {}: {}".format(
job_detail.error.code, job_detail.error.message))
check_documents(client, job_detail.id)
exit(1)
elif job_detail.status == "Succeeded":
print("We translated our documents!")
if job_detail.documents_failed_count > 0:
check_documents(client, job_detail.id)
break
async def custom_translation_async(self):
# import libraries
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation.aio import DocumentTranslationClient
from azure.ai.documenttranslation import (BatchDocumentInput,
StorageTarget)
# get service secrets
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_container_url_fr = os.environ["AZURE_TARGET_CONTAINER_URL_FR"]
category_id = os.environ["AZURE_DOCUMENT_TRANSLATION_MODEL_ID"]
# prepare translation job input
batch = [
BatchDocumentInput(source_url=source_container_url,
targets=[
StorageTarget(
target_url=target_container_url_fr,
language="fr",
category_id=category_id,
glossaries=["https://exampleglossary"])
],
prefix="document_2021")
]
# create translation client
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
# run translation job
async with client:
job_detail = await client.create_translation_job(batch)
print("Job initial status: {}".format(job_detail.status))
print("Number of translations on documents: {}".format(
job_detail.documents_total_count))
job_result = await client.wait_until_done(
job_detail.id) # type: JobStatusDetail
if job_result.status == "Succeeded":
print("We translated our documents!")
if job_result.documents_failed_count > 0:
await self.check_documents(client, job_result.id)
elif job_result.status in ["Failed", "ValidationFailed"]:
if job_result.error:
print("Translation job failed: {}: {}".format(
job_result.error.code, job_result.error.message))
await self.check_documents(client, job_result.id)
exit(1)
async def cancel_translation_job_async(self):
# import libraries
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation.aio import DocumentTranslationClient
from azure.ai.documenttranslation import (BatchDocumentInput,
StorageTarget)
# get service secrets
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_container_url_es = os.environ["AZURE_TARGET_CONTAINER_URL_ES"]
# prepare translation job input
batch = [
BatchDocumentInput(source_url=source_container_url,
targets=[
StorageTarget(
target_url=target_container_url_es,
language="es")
],
storage_type="file")
]
# create translation client
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
# run job
async with client:
job_detail = await client.create_translation_job(batch)
print("Job initial status: {}".format(job_detail.status))
print("Number of translations on documents: {}".format(
job_detail.documents_total_count))
await client.cancel_job(job_detail.id)
job_detail = await client.get_job_status(job_detail.id
) # type: JobStatusDetail
if job_detail.status in ["Cancelled", "Cancelling"]:
print("We cancelled job with ID: {}".format(job_detail.id))
def sample_cancel_translation_job():
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (
DocumentTranslationClient,
BatchDocumentInput,
StorageTarget
)
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_container_url_es = os.environ["AZURE_TARGET_CONTAINER_URL_ES"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
batch = [
BatchDocumentInput(
source_url=source_container_url,
targets=[
StorageTarget(
target_url=target_container_url_es,
language="es"
)
],
storage_type="file"
)
]
job_detail = client.create_translation_job(batch) # type: JobStatusDetail
print("Job initial status: {}".format(job_detail.status))
print("Number of translations on documents: {}".format(job_detail.documents_total_count))
client.cancel_job(job_detail.id)
job_detail = client.get_job_status(job_detail.id) # type: JobStatusDetail
if job_detail.status in ["Cancelled", "Cancelling"]:
print("We cancelled job with ID: {}".format(job_detail.id))
async def batch_translation_with_storage_async(self):
# import libraries
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation.aio import DocumentTranslationClient
from azure.ai.documenttranslation import (BatchDocumentInput,
StorageTarget)
from azure.storage.blob.aio import ContainerClient
from azure.storage.blob import (generate_container_sas,
ContainerSasPermissions)
# get service secrets
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_storage_endpoint = os.environ["AZURE_STORAGE_SOURCE_ENDPOINT"]
source_storage_account_name = os.environ[
"AZURE_STORAGE_SOURCE_ACCOUNT_NAME"]
source_storage_container_name = os.environ[
"AZURE_STORAGE_SOURCE_CONTAINER_NAME"]
source_storage_key = os.environ["AZURE_STORAGE_SOURCE_KEY"]
target_storage_endpoint = os.environ["AZURE_STORAGE_TARGET_ENDPOINT"]
target_storage_account_name = os.environ[
"AZURE_STORAGE_TARGET_ACCOUNT_NAME"]
target_storage_container_name = os.environ[
"AZURE_STORAGE_TARGET_CONTAINER_NAME"]
target_storage_key = os.environ["AZURE_STORAGE_TARGET_KEY"]
# create service clients
translation_client = DocumentTranslationClient(endpoint,
AzureKeyCredential(key))
container_client = ContainerClient(
source_storage_endpoint,
container_name=source_storage_container_name,
credential=source_storage_key)
# upload some document for translation
with open("document.txt", "rb") as doc:
await container_client.upload_blob(name="document.txt", data=doc)
# prepare translation job input
source_container_sas = generate_container_sas(
account_name=source_storage_account_name,
container_name=source_storage_container_name,
account_key=source_storage_key,
permission=ContainerSasPermissions.from_string("rl"))
target_container_sas = generate_container_sas(
account_name=target_storage_account_name,
container_name=target_storage_container_name,
account_key=target_storage_key,
permission=ContainerSasPermissions.from_string("rlwd"))
source_container_url = source_storage_endpoint + "/" + source_storage_container_name + "?" + source_container_sas
target_container_url = target_storage_endpoint + "/" + target_storage_container_name + "?" + target_container_sas
batch = [
BatchDocumentInput(source_url=source_container_url,
targets=[
StorageTarget(
target_url=target_container_url,
language="es")
],
prefix="document")
]
# run job
async with translation_client:
job_detail = await translation_client.create_translation_job(batch)
job_result = await translation_client.wait_until_done(job_detail.id
)
# poll status result
if job_result.status == "Succeeded":
print("We translated our documents!")
if job_result.documents_failed_count > 0:
await self.check_documents(translation_client,
job_result.id)
elif job_result.status in ["Failed", "ValidationFailed"]:
if job_result.error:
print("Translation job failed: {}: {}".format(
job_result.error.code, job_result.error.message))
await self.check_documents(translation_client, job_result.id)
exit(1)
# store result documents
container_client = ContainerClient(
target_storage_endpoint,
container_name=target_storage_container_name,
credential=target_storage_key)
with open("translated.txt", "wb") as my_blob:
download_stream = await container_client.download_blob(
"document.txt")
my_blob.write(await download_stream.readall())
def sample_batch_translation_with_storage():
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (
DocumentTranslationClient,
BatchDocumentInput,
StorageTarget
)
from azure.storage.blob import ContainerClient, generate_container_sas, ContainerSasPermissions
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
source_storage_endpoint = os.environ["AZURE_STORAGE_SOURCE_ENDPOINT"]
source_storage_account_name = os.environ["AZURE_STORAGE_SOURCE_ACCOUNT_NAME"]
source_storage_container_name = os.environ["AZURE_STORAGE_SOURCE_CONTAINER_NAME"]
source_storage_key = os.environ["AZURE_STORAGE_SOURCE_KEY"]
target_storage_endpoint = os.environ["AZURE_STORAGE_TARGET_ENDPOINT"]
target_storage_account_name = os.environ["AZURE_STORAGE_TARGET_ACCOUNT_NAME"]
target_storage_container_name = os.environ["AZURE_STORAGE_TARGET_CONTAINER_NAME"]
target_storage_key = os.environ["AZURE_STORAGE_TARGET_KEY"]
translation_client = DocumentTranslationClient(
endpoint, AzureKeyCredential(key)
)
container_client = ContainerClient(
source_storage_endpoint,
container_name=source_storage_container_name,
credential=source_storage_key
)
with open("document.txt", "rb") as doc:
container_client.upload_blob("document.txt", doc)
source_container_sas = generate_container_sas(
account_name=source_storage_account_name,
container_name=source_storage_container_name,
account_key=source_storage_key,
permission=ContainerSasPermissions.from_string("rl")
)
target_container_sas = generate_container_sas(
account_name=target_storage_account_name,
container_name=target_storage_container_name,
account_key=target_storage_key,
permission=ContainerSasPermissions.from_string("rlwd")
)
source_container_url = source_storage_endpoint + "/" + source_storage_container_name + "?" + source_container_sas
target_container_url = target_storage_endpoint + "/" + target_storage_container_name + "?" + target_container_sas
batch = [
BatchDocumentInput(
source_url=source_container_url,
targets=[
StorageTarget(
target_url=target_container_url,
language="es"
)
],
prefix="document"
)
]
job_detail = translation_client.create_translation_job(batch)
job_result = translation_client.wait_until_done(job_detail.id)
if job_result.status == "Succeeded":
print("We translated our documents!")
if job_result.documents_failed_count > 0:
check_documents(translation_client, job_result.id)
elif job_result.status in ["Failed", "ValidationFailed"]:
if job_result.error:
print("Translation job failed: {}: {}".format(job_result.error.code, job_result.error.message))
check_documents(translation_client, job_result.id)
exit(1)
container_client = ContainerClient(
target_storage_endpoint,
container_name=target_storage_container_name,
credential=target_storage_key
)
target_container_client = container_client.from_container_url(target_container_url)
with open("translated.txt", "wb") as my_blob:
download_stream = target_container_client.download_blob("document.txt")
my_blob.write(download_stream.readall())