Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications. Triggers: "text translation", "translator", "translate text", "transliterate", "TextTranslationClient".
apm install @microsoft/azure-ai-translation-text-py---
name: azure-ai-translation-text-py
description: |
Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
Triggers: "text translation", "translator", "translate text", "transliterate", "TextTranslationClient".
package: azure-ai-translation-text
---
# Azure AI Text Translation SDK for Python
Client library for Azure AI Translator text translation service for real-time text translation, transliteration, and language operations.
## Installation
```bash
pip install azure-ai-translation-text
```
## Environment Variables
```bash
AZURE_TRANSLATOR_KEY=<your-api-key>
AZURE_TRANSLATOR_REGION=<your-region> # e.g., eastus, westus2
# Or use custom endpoint
AZURE_TRANSLATOR_ENDPOINT=https://<resource>.cognitiveservices.azure.com
```
## Authentication
### API Key with Region
```python
import os
from azure.ai.translation.text import TextTranslationClient
from azure.core.credentials import AzureKeyCredential
key = os.environ["AZURE_TRANSLATOR_KEY"]
region = os.environ["AZURE_TRANSLATOR_REGION"]
# Create credential with region
credential = AzureKeyCredential(key)
client = TextTranslationClient(credential=credential, region=region)
```
### API Key with Custom Endpoint
```python
endpoint = os.environ["AZURE_TRANSLATOR_ENDPOINT"]
client = TextTranslationClient(
credential=AzureKeyCredential(key),
endpoint=endpoint
)
```
### Entra ID (Recommended)
```python
from azure.ai.translation.text import TextTranslationClient
from azure.identity import DefaultAzureCredential
client = TextTranslationClient(
credential=DefaultAzureCredential(),
endpoint=os.environ["AZURE_TRANSLATOR_ENDPOINT"]
)
```
## Basic Translation
```python
# Translate to a single language
result = client.translate(
body=["Hello, how are you?", "Welcome to Azure!"],
to=["es"] # Spanish
)
for item in result:
for translation in item.translations:
print(f"Translated: {translation.text}")
print(f"Target language: {translation.to}")
```
## Translate to Multiple Languages
```python
result = client.translate(
body=["Hello, world!"],
to=["es", "fr", "de", "ja"] # Spanish, French, German, Japanese
)
for item in result:
print(f"Source: {item.detected_language.language if item.detected_language else 'unknown'}")
for translation in item.translations:
print(f" {translation.to}: {translation.text}")
```
## Specify Source Language
```python
result = client.translate(
body=["Bonjour le monde"],
from_parameter="fr", # Source is French
to=["en", "es"]
)
```
## Language Detection
```python
result = client.translate(
body=["Hola, como estas?"],
to=["en"]
)
for item in result:
if item.detected_language:
print(f"Detected language: {item.detected_language.language}")
print(f"Confidence: {item.detected_language.score:.2f}")
```
## Transliteration
Convert text from one script to another:
```python
result = client.transliterate(
body=["konnichiwa"],
language="ja",
from_script="Latn", # From Latin script
to_script="Jpan" # To Japanese script
)
for item in result:
print(f"Transliterated: {item.text}")
print(f"Script: {item.script}")
```
## Dictionary Lookup
Find alternate translations and definitions:
```python
result = client.lookup_dictionary_entries(
body=["fly"],
from_parameter="en",
to="es"
)
for item in result:
print(f"Source: {item.normalized_source} ({item.display_source})")
for translation in item.translations:
print(f" Translation: {translation.normalized_target}")
print(f" Part of speech: {translation.pos_tag}")
print(f" Confidence: {translation.confidence:.2f}")
```
## Dictionary Examples
Get usage examples for translations:
```python
from azure.ai.translation.text.models import DictionaryExampleTextItem
result = client.lookup_dictionary_examples(
body=[DictionaryExampleTextItem(text="fly", translation="volar")],
from_parameter="en",
to="es"
)
for item in result:
for example in item.examples:
print(f"Source: {example.source_prefix}{example.source_term}{example.source_suffix}")
print(f"Target: {example.target_prefix}{example.target_term}{example.target_suffix}")
```
## Get Supported Languages
```python
# Get all supported languages
languages = client.get_supported_languages()
# Translation languages
print("Translation languages:")
for code, lang in languages.translation.items():
print(f" {code}: {lang.name} ({lang.native_name})")
# Transliteration languages
print("\nTransliteration languages:")
for code, lang in languages.transliteration.items():
print(f" {code}: {lang.name}")
for script in lang.scripts:
print(f" {script.code} -> {[t.code for t in script.to_scripts]}")
# Dictionary languages
print("\nDictionary languages:")
for code, lang in languages.dictionary.items():
print(f" {code}: {lang.name}")
```
## Break Sentence
Identify sentence boundaries:
```python
result = client.find_sentence_boundaries(
body=["Hello! How are you? I hope you are well."],
language="en"
)
for item in result:
print(f"Sentence lengths: {item.sent_len}")
```
## Translation Options
```python
result = client.translate(
body=["Hello, world!"],
to=["de"],
text_type="html", # "plain" or "html"
profanity_action="Marked", # "NoAction", "Deleted", "Marked"
profanity_marker="Asterisk", # "Asterisk", "Tag"
include_alignment=True, # Include word alignment
include_sentence_length=True # Include sentence boundaries
)
for item in result:
translation = item.translations[0]
print(f"Translated: {translation.text}")
if translation.alignment:
print(f"Alignment: {translation.alignment.proj}")
if translation.sent_len:
print(f"Sentence lengths: {translation.sent_len.src_sent_len}")
```
## Async Client
```python
from azure.ai.translation.text.aio import TextTranslationClient
from azure.core.credentials import AzureKeyCredential
async def translate_text():
async with TextTranslationClient(
credential=AzureKeyCredential(key),
region=region
) as client:
result = await client.translate(
body=["Hello, world!"],
to=["es"]
)
print(result[0].translations[0].text)
```
## Client Methods
| Method | Description |
|--------|-------------|
| `translate` | Translate text to one or more languages |
| `transliterate` | Convert text between scripts |
| `detect` | Detect language of text |
| `find_sentence_boundaries` | Identify sentence boundaries |
| `lookup_dictionary_entries` | Dictionary lookup for translations |
| `lookup_dictionary_examples` | Get usage examples |
| `get_supported_languages` | List supported languages |
## Best Practices
1. **Batch translations** — Send multiple texts in one request (up to 100)
2. **Specify source language** when known to improve accuracy
3. **Use async client** for high-throughput scenarios
4. **Cache language list** — Supported languages don't change frequently
5. **Handle profanity** appropriately for your application
6. **Use html text_type** when translating HTML content
7. **Include alignment** for applications needing word mapping