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 (DocumentTranslationInput,
TranslationTarget)
# 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
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_url,
targets=[
TranslationTarget(target_url=target_container_url_es,
language_code="es"),
TranslationTarget(target_url=target_container_url_fr,
language_code="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(translation_inputs
)
while True:
job_detail = await client.get_job_status(
job_detail.id) # type: JobStatusResult
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,
DocumentTranslationInput,
TranslationTarget)
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))
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_url_en,
targets=[
TranslationTarget(target_url=target_container_url_es,
language_code="es"),
TranslationTarget(target_url=target_container_url_fr,
language_code="fr")
]),
DocumentTranslationInput(
source_url=source_container_url_de,
targets=[
TranslationTarget(target_url=target_container_url_es,
language_code="es"),
TranslationTarget(target_url=target_container_url_fr,
language_code="fr")
])
]
job_detail = client.create_translation_job(
translation_inputs) # type: JobStatusResult
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: JobStatusResult
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,
DocumentTranslationInput,
TranslationTarget)
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))
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_url,
targets=[
TranslationTarget(target_url=target_container_url_es,
language_code="es"),
TranslationTarget(target_url=target_container_url_fr,
language_code="fr")
],
storage_type="folder",
prefix="document_2021")
]
job_detail = client.create_translation_job(translation_inputs)
while True:
job_detail = client.get_job_status(
job_detail.id) # type: JobStatusResult
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 sample_translation_with_glossaries_async():
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation.aio import DocumentTranslationClient
from azure.ai.documenttranslation import (DocumentTranslationInput,
TranslationTarget,
TranslationGlossary)
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 = os.environ["AZURE_TARGET_CONTAINER_URL"]
glossary_url = os.environ["AZURE_TRANSLATION_GLOSSARY_URL"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
inputs = DocumentTranslationInput(
source_url=source_container_url,
targets=[
TranslationTarget(target_url=target_container_url,
language_code="es",
glossaries=[
TranslationGlossary(
glossary_url=glossary_url,
file_format="TSV")
])
])
async with client:
job = await client.create_translation_job(inputs=[inputs]
) # type: JobStatusResult
job_result = await client.wait_until_done(job.id
) # type: JobStatusResult
print("Job status: {}".format(job_result.status))
print("Job created on: {}".format(job_result.created_on))
print("Job last updated on: {}".format(job_result.last_updated_on))
print("Total number of translations on documents: {}".format(
job_result.documents_total_count))
print("\nOf total documents...")
print("{} failed".format(job_result.documents_failed_count))
print("{} succeeded".format(job_result.documents_succeeded_count))
doc_results = client.list_all_document_statuses(
job_result.id) # type: AsyncItemPaged[DocumentStatusResult]
async for document in doc_results:
print("Document ID: {}".format(document.id))
print("Document status: {}".format(document.status))
if document.status == "Succeeded":
print("Document location: {}".format(
document.translated_document_url))
print("Translated to language: {}\n".format(
document.translate_to))
else:
print("Error Code: {}, Message: {}\n".format(
document.error.code, document.error.message))
def sample_document_status_checks():
import os
import time
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (DocumentTranslationClient,
DocumentTranslationInput,
TranslationTarget)
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 = os.environ["AZURE_TARGET_CONTAINER_URL"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
job_result = client.create_translation_job(inputs=[
DocumentTranslationInput(source_url=source_container_url,
targets=[
TranslationTarget(
target_url=target_container_url,
language_code="es")
])
]) # type: JobStatusResult
completed_docs = []
while not job_result.has_completed:
time.sleep(30)
doc_statuses = client.list_all_document_statuses(job_result.id)
for document in doc_statuses:
if document.id not in completed_docs:
if document.status == "Succeeded":
print(
"Document at {} was translated to {} language".format(
document.translated_document_url,
document.translate_to))
completed_docs.append(document.id)
if document.status == "Failed":
print(
"Document ID: {}, Error Code: {}, Message: {}".format(
document.id, document.error.code,
document.error.message))
completed_docs.append(document.id)
if document.status == "Running":
print(
"Document ID: {}, translation progress is {} percent".
format(document.id,
document.translation_progress * 100))
job_result = client.get_job_status(job_result.id)
print("\nTranslation job completed.")
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 (DocumentTranslationInput,
TranslationTarget)
# 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
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_url,
targets=[
TranslationTarget(target_url=target_container_url_fr,
language_code="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(translation_inputs
)
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: JobStatusResult
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)
def sample_translation():
import os
# [START wait_until_done]
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (DocumentTranslationClient,
DocumentTranslationInput,
TranslationTarget)
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 = os.environ["AZURE_TARGET_CONTAINER_URL"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
job = client.create_translation_job(inputs=[
DocumentTranslationInput(source_url=source_container_url,
targets=[
TranslationTarget(
target_url=target_container_url,
language_code="es")
])
]) # type: JobStatusResult
job_result = client.wait_until_done(job.id) # type: JobStatusResult
print("Job status: {}".format(job_result.status))
print("Job created on: {}".format(job_result.created_on))
print("Job last updated on: {}".format(job_result.last_updated_on))
print("Total number of translations on documents: {}".format(
job_result.documents_total_count))
print("\nOf total documents...")
print("{} failed".format(job_result.documents_failed_count))
print("{} succeeded".format(job_result.documents_succeeded_count))
# [END wait_until_done]
# [START list_all_document_statuses]
doc_results = client.list_all_document_statuses(
job_result.id) # type: ItemPaged[DocumentStatusResult]
for document in doc_results:
print("Document ID: {}".format(document.id))
print("Document status: {}".format(document.status))
if document.status == "Succeeded":
print("Document location: {}".format(
document.translated_document_url))
print("Translated to language: {}\n".format(document.translate_to))
else:
print("Error Code: {}, Message: {}\n".format(
document.error.code, document.error.message))
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 (DocumentTranslationInput,
TranslationTarget)
# 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
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_url,
targets=[
TranslationTarget(target_url=target_container_url_es,
language_code="es")
],
storage_type="file")
]
# create translation client
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
# run job
async with client:
job_detail = await client.create_translation_job(translation_inputs
)
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: JobStatusResult
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,
DocumentTranslationInput,
TranslationTarget)
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))
translation_inputs = [
DocumentTranslationInput(source_url=source_container_url,
targets=[
TranslationTarget(
target_url=target_container_url_es,
language_code="es")
],
storage_type="file")
]
job_detail = client.create_translation_job(
translation_inputs) # type: JobStatusResult
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: JobStatusResult
if job_detail.status in ["Cancelled", "Cancelling"]:
print("We cancelled job with ID: {}".format(job_detail.id))
async def sample_translation_with_azure_blob(self):
translation_client = DocumentTranslationClient(
self.endpoint, AzureKeyCredential(self.key))
blob_service_client = BlobServiceClient(self.storage_endpoint,
credential=self.storage_key)
source_container = await self.create_container(
blob_service_client,
container_name=self.storage_source_container_name
or "translation-source-container",
)
target_container = await self.create_container(
blob_service_client,
container_name=self.storage_target_container_name
or "translation-target-container")
if self.document_name:
with open(self.document_name, "rb") as doc:
await source_container.upload_blob(self.document_name, doc)
else:
self.document_name = "example_document.txt"
await source_container.upload_blob(
name=self.document_name,
data=
b"This is an example translation with the document translation client library"
)
print("Uploaded document {} to storage container {}".format(
self.document_name, source_container.container_name))
source_container_sas_url = self.generate_sas_url(source_container,
permissions="rl")
target_container_sas_url = self.generate_sas_url(target_container,
permissions="wl")
translation_inputs = [
DocumentTranslationInput(
source_url=source_container_sas_url,
targets=[
TranslationTarget(target_url=target_container_sas_url,
language_code="fr")
])
]
job = await translation_client.create_translation_job(
translation_inputs)
print("Created translation job with ID: {}".format(job.id))
print("Waiting until job completes...")
job_result = await translation_client.wait_until_done(job.id)
print("Job status: {}".format(job_result.status))
doc_results = translation_client.list_all_document_statuses(
job_result.id)
print("\nDocument results:")
async for document in doc_results:
print("Document ID: {}".format(document.id))
print("Document status: {}".format(document.status))
if document.status == "Succeeded":
print("Document location: {}".format(
document.translated_document_url))
print("Translated to language: {}\n".format(
document.translate_to))
blob_client = BlobClient.from_blob_url(
document.translated_document_url,
credential=self.storage_key)
async with blob_client:
with open("translated_" + self.document_name,
"wb") as my_blob:
download_stream = await blob_client.download_blob()
my_blob.write(await download_stream.readall())
print("Downloaded {} locally".format("translated_" +
self.document_name))
else:
print("\nThere was a problem translating your document.")
print("Document Error Code: {}, Message: {}\n".format(
document.error.code, document.error.message))
await translation_client.close()
await blob_service_client.close()
def sample_batch_translation_with_storage():
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documenttranslation import (DocumentTranslationClient,
DocumentTranslationInput,
TranslationTarget)
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
translation_inputs = [
DocumentTranslationInput(source_url=source_container_url,
targets=[
TranslationTarget(
target_url=target_container_url,
language_code="es")
],
prefix="document")
]
job_detail = translation_client.create_translation_job(translation_inputs)
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())
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 (DocumentTranslationInput,
TranslationTarget)
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
translation_inputs = [
DocumentTranslationInput(source_url=source_container_url,
targets=[
TranslationTarget(
target_url=target_container_url,
language_code="es")
],
prefix="document")
]
# run job
async with translation_client:
job_detail = await translation_client.create_translation_job(
translation_inputs)
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())
