# DeepL Python Library
[](https://pypi.org/project/deepl/)
[](https://pypi.org/project/deepl/)
[](https://github.com/DeepLcom/deepl-python/blob/main/LICENSE)
The [DeepL API][api-docs] is a language translation API that allows other
computer programs to send texts and documents to DeepL's servers and receive
high-quality translations. This opens a whole universe of opportunities for
developers: any translation product you can imagine can now be built on top of
DeepL's best-in-class translation technology.
The DeepL Python library offers a convenient way for applications written in
Python to interact with the DeepL API. We intend to support all API functions
with the library, though support for new features may be added to the library
after they’re added to the API.
## Getting an authentication key
To use the DeepL Python Library, you'll need an API authentication key. To get a
key, [please create an account here][create-account]. With a DeepL API Free
account you can translate up to 500,000 characters/month for free.
## Installation
The library can be installed from [PyPI][pypi-project] using pip:
```shell
pip install --upgrade deepl
```
If you need to modify this source code, install the dependencies using poetry:
```shell
poetry install
```
On Ubuntu 22.04 an error might occur: `ModuleNotFoundError: No module named
'cachecontrol'`. Use the workaround `sudo apt install python3-cachecontrol` as
explained in this [bug report][bug-report-ubuntu-2204].
### Requirements
The library is tested with Python versions 3.6 to 3.11.
The `requests` module is used to perform HTTP requests; the minimum is version
2.0.
Starting in 2024, we will drop support for older Python versions that have
reached official end-of-life. You can find the Python versions and support
timelines [here][python-version-list].
To continue using this library, you should update to Python 3.8+.
## Usage
Import the package and construct a `Translator`. The first argument is a string
containing your API authentication key as found in your
[DeepL Pro Account][pro-account].
Be careful not to expose your key, for example when sharing source code.
```python
import deepl
auth_key = "f63c02c5-f056-..." # Replace with your key
translator = deepl.Translator(auth_key)
result = translator.translate_text("Hello, world!", target_lang="FR")
print(result.text) # "Bonjour, le monde !"
```
This example is for demonstration purposes only. In production code, the
authentication key should not be hard-coded, but instead fetched from a
configuration file or environment variable.
`Translator` accepts additional options, see [Configuration](#configuration)
for more information.
### Translating text
To translate text, call `translate_text()`. The first argument is a string
containing the text you want to translate, or a list of strings if you want to
translate multiple texts.
`source_lang` and `target_lang` specify the source and target language codes
respectively. The `source_lang` is optional, if it is unspecified the source
language will be auto-detected.
Language codes are **case-insensitive** strings according to ISO 639-1, for
example `'DE'`, `'FR'`, `'JA''`. Some target languages also include the regional
variant according to ISO 3166-1, for example `'EN-US'`, or `'PT-BR'`. The full
list of supported languages is in the
[API documentation][api-docs-lang-list].
There are additional optional arguments to control translation, see
[Text translation options](#text-translation-options) below.
`translate_text()` returns a `TextResult`, or a list of `TextResult`s
corresponding to your input text(s). `TextResult` has the following properties:
- `text` is the translated text,
- `detected_source_lang` is the detected source language code,
- `billed_characters` is the number of characters billed for the translation.
- `model_type_used` indicates the translation model used, but is `None` unless
the `model_type` option is specified.
```python
# Translate text into a target language, in this case, French:
result = translator.translate_text("Hello, world!", target_lang="FR")
print(result.text) # "Bonjour, le monde !"
# Translate multiple texts into British English
result = translator.translate_text(
["お元気ですか？", "¿Cómo estás?"],
target_lang="EN-GB",
)
print(result[0].text) # "How are you?"
print(result[0].detected_source_lang) # "JA" the language code for Japanese
print(result[0].billed_characters) # 7 - the number of characters in the source text "お元気ですか？"
print(result[1].text) # "How are you?"
print(result[1].detected_source_lang) # "ES" the language code for Spanish
print(result[1].billed_characters) # 12 - the number of characters in the source text "¿Cómo estás?"
# Translate into German with less and more Formality:
print(
translator.translate_text(
"How are you?", target_lang="DE", formality="less"
)
) # 'Wie geht es dir?'
print(
translator.translate_text(
"How are you?", target_lang="DE", formality="more"
)
) # 'Wie geht es Ihnen?'
```
#### Text translation options
In addition to the input text(s) argument, the available `translate_text()`
arguments are:
- `source_lang`: Specifies the source language code, but may be omitted to
auto-detect the source language.
- `target_lang`: Required. Specifies the target language code.
- `split_sentences`: specify how input text should be split into sentences,
default: `'on'`.
- `'on''` (`SplitSentences.ON`): input text will be split into sentences
using both newlines and punctuation.
- `'off'` (`SplitSentences.OFF`): input text will not be split into
sentences. Use this for applications where each input text contains only
one sentence.
- `'nonewlines'` (`SplitSentences.NO_NEWLINES`): input text will be split
into sentences using punctuation but not newlines.
- `preserve_formatting`: controls automatic-formatting-correction. Set to `True`
to prevent automatic-correction of formatting, default: `False`.
- `formality`: controls whether translations should lean toward informal or
formal language. This option is only available for some target languages, see
[Listing available languages](#listing-available-languages).
- `'less'` (`Formality.LESS`): use informal language.
- `'more'` (`Formality.MORE`): use formal, more polite language.
- `glossary`: specifies a glossary to use with translation, either as a string
containing the glossary ID, or a `GlossaryInfo` as returned by
`get_glossary()`.
- `context`: specifies additional context to influence translations, that is not
translated itself. Characters in the `context` parameter are not counted toward billing.
See the [API documentation][api-docs-context-param] for more information and
example usage.
- `model_type`: specifies the type of translation model to use, options are:
- `'quality_optimized'` (`ModelType.QUALITY_OPTIMIZED`): use a translation
model that maximizes translation quality, at the cost of response time.
This option may be unavailable for some language pairs.
- `'prefer_quality_optimized'` (`ModelType.PREFER_QUALITY_OPTIMIZED`): use
the highest-quality translation model for the given language pair.
- `'latency_optimized'` (`ModelType.LATENCY_OPTIMIZED`): use a translation
model that minimizes response time, at the cost of translation quality.
- `tag_handling`: type of tags to parse before translation, options are `'html'`
and `'xml'`.
The following options are only used if `tag_handling` is `'xml'`:
- `outline_detection`: specify `False` to disable automatic tag detection,
default is `True`.
- `splitting_tags`: list of XML tags that should be used to split text into
sentences. Tags may be specified as an array of strings (`['tag1', 'tag2']`),
or a comma-separated list of strings (`'tag1,tag2'`). The default is an empty
list.
- `non_splitting_tags`: list of XML tags that should not be used to split text
into sentences. Format and default are the same as for `splitting_tags`.
- `ignore_tags`: list of XML tags that containing content that should not be
translated. Format and default are the same as for `splitting_tags`.
For a detailed explanation of the XML handling options, see the
[API documentation][api-docs-xml-handling].
### Translating documents
To translate documents, you may call either `translate_document()` using file IO
objects, or `translate_document_from_filepath()` using file paths. For both
functions, the first and second arguments correspond to the input and output
files respectively.
Just as for the `translate_text()` function, the `source_lang` and
`target_lang` arguments specify the source and target language codes.
There are additional optional arguments to control translation, see
[Document translation options](#document-translation-options) below.
```python
# Translate a formal document from English to German
input_path = "/path/to/Instruction Manual.docx"
output_path = "/path/to/Bedienungsanleitung.docx"
try:
# Using translate_document_from_filepath() with file paths
translator.translate_document_from_filepath(
input_path,
output_path,
target_lang="DE",
formality="more"
)
# Alternatively you can use translate_document() with file IO objects
with open(input_path, "rb") as in_file, open(output_path, "wb") as out_file:
translator.translate_document(
in_file,
out_file,
target_lang="DE",
formality="more"
)
except deepl.DocumentTranslationException as error:
# If an error occurs during document translation after the document was
# already uploaded, a DocumentTranslationException is raised. The
# document_handle property contains the document handle that may be used to
# later retrieve the document from the server, or contact DeepL support.
doc_id = error.document_handle.id
doc_key = error.document_handle.key
print(f"Error after uploading ${error}, id: ${doc_id} key: ${doc_key}")
except deepl.DeepLException as error:
# Errors during upload raise a DeepLException
print(error)
```
`translate_document()` and `translate_document_from_filepath()` are convenience
functions that wrap multiple API calls: uploading, polling status until the
translation is complete, and downloading. If your application needs to execute
these steps individually, you can instead use the following functions directly:
- `translate_document_upload()`,
- `translate_document_get_status()` (or
`translate_document_wait_until_done()`), and
- `translate_document_download()`
#### Document translation options
In addition to the input file, output file, `source_lang` and `target_lang`
arguments, the available `translate_document()` and
`translate_document_from_filepath()` arguments are:
- `formality`: same as in [Text translation options](#text-translation-options).
- `glossary`: same as in [Text translation options](#text-translation-options).
- `output_format`: (`translate_document()` only)
file extension of desired format of translated file, for example: `'pdf'`. If
unspecified, by default the translated file will be in the same format as the
input file.
### Glossaries
Glossaries allow you to customize your translations using user-defined terms.
Multiple glossaries can be stored with your account, each with a user-specified
name and a uniquely-assigned ID.
#### Creating a glossary
You can create a glossary with your desired terms and name using
`create_glossary()`. Each glossary applies to a single source-target language
pair. Note: Glossaries are only supported for some language pairs, see
[Listing available glossary languages](#listing-available-glossary-languages)
for more information. The entries should be specified as a dictionary.
If successful, the glossary is created and stored with your DeepL account, and
a `GlossaryInfo` object is returned including the ID, name, languages and entry
count.
```python
# Create an English to German glossary with two terms:
entries = {"artist": "Maler", "prize": "Gewinn"}
my_glossary = translator.create_glossary(
"My glossary",
source_lang="EN",
target_lang="DE",
entries=entries,
)
print(
f"Created '{my_glossary.name}' ({my_glossary.glossary_id}) "
f"{my_glossary.source_lang}->{my_glossary.target_lang} "
f"containing {my_glossary.entry_count} entries"
)
# Example: Created 'My glossary' (559192ed-8e23-...) EN->DE containing 2 entries
```
You can also upload a glossary downloaded from the DeepL website using
`create_glossary_from_csv()`. Instead of supplying the entries as a dictionary,
specify the CSV data as `csv_data` either as a file-like object or string or
bytes containing file content:
```python
# Open the CSV file assuming UTF-8 encoding. If your file contains a BOM,
# consider using encoding='utf-8-sig' instead.
with open('/path/to/glossary_file.csv', 'r', encoding='utf-8') as csv_file:
csv_data = csv_file.read() # Read the file contents as a string
my_csv_glossary = translator.create_glossary_from_csv(
"CSV glossary",
source_lang="EN",
target_lang="DE",
csv_data=csv_data,
)
```
The [API documentation][api-docs-csv-format] explains the expected CSV format in
detail.
#### Getting, listing and deleting stored glossaries
Functions to get, list, and delete stored glossaries are also provided:
- `get_glossary()` takes a glossary ID and returns a `GlossaryInfo` object for a
stored glossary, or raises an exception if no such glossary is found.
- `list_glossaries()` returns a list of `GlossaryInfo` objects corresponding to
all of your stored glossaries.
- `delete_glossary()` takes a glossary ID or `GlossaryInfo` object and deletes
the stored glossary from the server, or raises an exception if no such
glossary is found.
```python
# Retrieve a stored glossary using the ID
glossary_id = "559192ed-8e23-..."
my_glossary = translator.get_glossary(glossary_id)
# Find and delete glossaries named 'Old glossary'
glossaries = translator.list_glossaries()
for glossary in glossaries:
if glossary.name == "Old glossary":
translator.delete_glossary(glossary)
```
#### Listing entries in a stored glossary
The `GlossaryInfo` object does not contain the glossary entries, but instead
only the number of entries in the `entry_count` property.
To list the entries contained within a stored glossary, use
`get_glossary_entries()` providing either the `GlossaryInfo` object or glossary
ID:
```python
entries = translator.get_glossary_entries(my_glossary)
print(entries) # "{'artist': 'Maler', 'prize': 'Gewinn'}"
```
#### Using a stored glossary
You can use a stored glossary for text translation by setting the `glossary`
argument to either the glossary ID or `GlossaryInfo` object. You must also
specify the `source_lang` argument (it is required when using a glossary):
```python
text = "The artist was awarded a prize."
with_glossary = translator.translate_text(
text, source_lang="EN", target_lang="DE", glossary=my_glossary,
)
print(with_glossary) # "Der Maler wurde mit einem Gewinn ausgezeichnet."
# For comparison, the result without a glossary:
without_glossary = translator.translate_text(text, target_lang="DE")
print(without_glossary) # "Der Künstler wurde mit einem Preis ausgezeichnet."
```
Using a stored glossary for document translation is the same: set the `glossary`
argument and specify the `source_lang` argument:
```python
translator.translate_document(
in_file, out_file, source_lang="EN", target_lang="DE", glossary=my_glossary,
)
```
The `translate_document()`, `translate_document_from_filepath()` and
`translate_document_upload()` functions all support the `glossary` argument.
### Checking account usage
To check account usage, use the `get_usage()` function.
The returned `Usage` object contains three usage subtypes: `character`,
`document` and `team_document`. Depending on your account type, some usage
subtypes may be invalid; this can be checked using the `valid` property. For API
accounts:
- `usage.character.valid` is `True`,
- `usage.document.valid` and `usage.team_document.valid` are `False`.
Each usage subtype (if valid) has `count` and `limit` properties giving the
amount used and maximum amount respectively, and the `limit_reached` property
that checks if the usage has reached the limit. The top level `Usage` object has
the `any_limit_reached` property to check all usage subtypes.
```python
usage = translator.get_usage()
if usage.any_limit_reached:
print('Translation limit reached.')
if usage.character.valid:
print(
f"Character usage: {usage.character.count} of {usage.character.limit}")
if usage.document.valid:
print(f"Document usage: {usage.document.count} of {usage.document.limit}")
```
### Listing available languages
You can request the list of languages supported by DeepL for text and documents
using the `get_source_languages()` and `get_target_languages()` functions. They
both return a list of `Language` objects.
The `name` property gives the name of the language in English, and the `code`
property gives the language code. The `supports_formality` property only appears
for target languages, and indicates whether the target language supports the
optional `formality` parameter.
```python
print("Source languages:")
for language in translator.get_source_languages():
print(f"{language.name} ({language.code})") # Example: "German (DE)"
print("Target languages:")
for language in translator.get_target_languages():
if language.supports_formality:
print(f"{language.name} ({language.code}) supports formality")
# Example: "Italian (IT) supports formality"
else:
print(f"{language.name} ({language.code})")
# Example: "Lithuanian (LT)"
```
#### Listing available glossary languages
Glossaries are supported for a subset of language pairs. To retrieve those
languages use the `get_glossary_languages()` function, which returns an array
of `GlossaryLanguagePair` objects. Each has `source_lang` and `target_lang`
properties indicating that that pair of language codes is supported.
```python
glossary_languages = translator.get_glossary_languages()
for language_pair in glossary_languages:
print(f"{language_pair.source_lang} to {language_pair.target_lang}")
# Example: "EN to DE", "DE to EN", etc.
```
You can also find the list of supported glossary language pairs in the
[API documentation][api-docs-glossary-lang-list].
Note that glossaries work for all target regional-variants: a glossary for the
target language English (`"EN"`) supports translations to both American English
(`"EN-US"`) and British English (`"EN-GB"`).
### Writing a Plugin
If you use this library in an application, please identify the application with
`deepl.Translator.set_app_info`, which needs the name and version of the app:
```python
translator = deepl.Translator(...).set_app_info("sample_python_plugin", "1.0.2")
```
This information is passed along when the library makes calls to the DeepL API.
Both name and version are required. Please note that setting the `User-Agent` header
via `deepl.http_client.user_agent` will override this setting, if you need to use this,
please manually identify your Application in the `User-Agent` header.
### Exceptions
All module functions may raise `deepl.DeepLException` or one of its subclasses.
If invalid arguments are provided, they may raise the standard exceptions
`ValueError` and `TypeError`.
### Configuration
#### Logging
Logging can be enabled to see the HTTP requests sent and responses received by
the library. Enable and control logging using Python's `logging` module, for
example:
```python
import logging
logging.basicConfig()
logging.getLogger('deepl').setLevel(logging.DEBUG)
```
#### Server URL configuration
You can override the URL of the DeepL API by specifying the `server_url`
argument when constructing a `deepl.Translator`. This may be useful for testing
purposes. You **do not** need to specify the URL to distinguish API Free and API
Pro accounts, the library selects the correct URL automatically.
```python
server_url = "http://user:pass@localhost:3000"
translator = deepl.Translator(..., server_url=server_url)
```
#### Proxy configuration
You can configure a proxy by specifying the `proxy` argument when constructing a
`deepl.Translator`:
```python
proxy = "http://user:pass@10.10.1.10:3128"
translator = deepl.Translator(..., proxy=proxy)
```
The proxy argument is passed to the underlying `requests` session, see the
[documentation for requests][requests-proxy-docs]; a dictionary of schemes to
proxy URLs is also accepted.
#### Override SSL verification
You can control how `requests` performs SSL verification by specifying the
`verify_ssl` option when constructing a `deepl.Translator`, for example to
disable SSL certificate verification:
```python
translator = deepl.Translator(..., verify_ssl=False)
```
This option is passed to the underlying `requests` session as the `verify`
option, see the [documentation for requests][requests-verify-ssl-docs].
#### Configure automatic retries
This SDK will automatically retry failed HTTP requests (if the failures could
be transient, e.g. a HTTP 429 status code). This behaviour can be configured
in `http_client.py`, for example by default the number of retries is 5. This
can be changed to 3 as follows:
```python
import deepl
deepl.http_client.max_network_retries = 3
t = deepl.Translator(...)
t.translate_text(...)
```
You can configure the timeout `min_connection_timeout` the same way, as well
as set a custom `user_agent`, see the next section.
#### Anonymous platform information
By default, we send some basic information about the platform the client library is running on with each request, see [here for an explanation](https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/User-Agent). This data is completely anonymous and only used to improve our product, not track any individual users. If you do not wish to send this data, you can opt-out when creating your `deepl.Translator` object by setting the `send_platform_info` flag like so:
```python
translator = deepl.Translator(..., send_platform_info=False)
```
You can also customize the `user_agent` by setting its value explicitly before constructing your `deepl.Translator` object.
```python
deepl.http_client.user_agent = 'my custom user agent'
translator = deepl.Translator(os.environ["DEEPL_AUTH_KEY"])
```
## Command Line Interface
The library can be run on the command line supporting all API functions. Use the
`--help` option for usage information:
```shell
python3 -m deepl --help
```
The CLI requires your DeepL authentication key specified either as the
`DEEPL_AUTH_KEY` environment variable, through the `keyring` module, or
using the `--auth-key` option, for example:
```shell
python3 -m deepl --auth-key=YOUR_AUTH_KEY usage
```
Note that the `--auth-key` argument must appear *before* the command argument.
To use the [keyring](https://pypi.org/project/keyring/) module, set the
*DEEPL_AUTH_KEY* field in the service *deepl* to your API key.
The recognized commands are:
| Command | Description |
| :-------- | :----------------------------------------------------- |
| text | translate text(s) |
| document | translate document(s) |
| usage | print usage information for the current billing period |
| languages | print available languages |
| glossary | create, list, and remove glossaries |
For example, to translate text:
```shell
python3 -m deepl --auth-key=YOUR_AUTH_KEY text --to=DE "Text to be translated."
```
Wrap text arguments in quotes to prevent the shell from splitting sentences into
words.
## Issues
If you experience problems using the library, or would like to request a new
feature, please open an [issue][issues].
## Development
We welcome Pull Requests, please read the
[contributing guidelines](CONTRIBUTING.md).
### Tests
Execute the tests using `pytest`. The tests communicate with the DeepL API using
the auth key defined by the `DEEPL_AUTH_KEY` environment variable.
Be aware that the tests make DeepL API requests that contribute toward your API
usage.
The test suite may instead be configured to communicate with the mock-server
provided by [deepl-mock][deepl-mock]. Although most test cases work for either,
some test cases work only with the DeepL API or the mock-server and will be
otherwise skipped. The test cases that require the mock-server trigger server
errors and test the client error-handling. To execute the tests using
deepl-mock, run it in another terminal while executing the tests. Execute the
tests using `pytest` with the `DEEPL_MOCK_SERVER_PORT` and `DEEPL_SERVER_URL`
environment variables defined referring to the mock-server.
[api-docs]: https://www.deepl.com/docs-api?utm_source=github&utm_medium=github-python-readme
[api-docs-csv-format]: https://www.deepl.com/docs-api/managing-glossaries/supported-glossary-formats/?utm_source=github&utm_medium=github-python-readme
[api-docs-xml-handling]: https://www.deepl.com/docs-api/handling-xml/?utm_source=github&utm_medium=github-python-readme
[api-docs-context-param]: https://www.deepl.com/docs-api/translating-text/?utm_source=github&utm_medium=github-python-readme
[api-docs-lang-list]: https://www.deepl.com/docs-api/translating-text/?utm_source=github&utm_medium=github-python-readme
[api-docs-glossary-lang-list]: https://www.deepl.com/docs-api/managing-glossaries/?utm_source=github&utm_medium=github-python-readme
[bug-report-ubuntu-2204]: https://bugs.launchpad.net/ubuntu/+source/poetry/+bug/1958227
[create-account]: https://www.deepl.com/pro?utm_source=github&utm_medium=github-python-readme#developer
[deepl-mock]: https://www.github.com/DeepLcom/deepl-mock
[issues]: https://www.github.com/DeepLcom/deepl-python/issues
[pypi-project]: https://pypi.org/project/deepl/
[pro-account]: https://www.deepl.com/pro-account/?utm_source=github&utm_medium=github-python-readme
[python-version-list]: https://devguide.python.org/versions/
[requests-proxy-docs]: https://docs.python-requests.org/en/latest/user/advanced/#proxies
[requests-verify-ssl-docs]: https://docs.python-requests.org/en/latest/user/advanced/#ssl-cert-verification
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"description": "# DeepL Python Library\n\n[](https://pypi.org/project/deepl/)\n[](https://pypi.org/project/deepl/)\n[](https://github.com/DeepLcom/deepl-python/blob/main/LICENSE)\n\nThe [DeepL API][api-docs] is a language translation API that allows other\ncomputer programs to send texts and documents to DeepL's servers and receive\nhigh-quality translations. This opens a whole universe of opportunities for\ndevelopers: any translation product you can imagine can now be built on top of\nDeepL's best-in-class translation technology.\n\nThe DeepL Python library offers a convenient way for applications written in\nPython to interact with the DeepL API. We intend to support all API functions\nwith the library, though support for new features may be added to the library\nafter they\u2019re added to the API.\n\n## Getting an authentication key\n\nTo use the DeepL Python Library, you'll need an API authentication key. To get a\nkey, [please create an account here][create-account]. With a DeepL API Free\naccount you can translate up to 500,000 characters/month for free.\n\n## Installation\n\nThe library can be installed from [PyPI][pypi-project] using pip:\n\n```shell\npip install --upgrade deepl\n```\n\nIf you need to modify this source code, install the dependencies using poetry:\n\n```shell\npoetry install\n```\n\nOn Ubuntu 22.04 an error might occur: `ModuleNotFoundError: No module named \n'cachecontrol'`. Use the workaround `sudo apt install python3-cachecontrol` as\nexplained in this [bug report][bug-report-ubuntu-2204].\n\n### Requirements\n\nThe library is tested with Python versions 3.6 to 3.11.\n\nThe `requests` module is used to perform HTTP requests; the minimum is version\n2.0.\n\nStarting in 2024, we will drop support for older Python versions that have\nreached official end-of-life. You can find the Python versions and support\ntimelines [here][python-version-list].\nTo continue using this library, you should update to Python 3.8+.\n\n## Usage\n\nImport the package and construct a `Translator`. The first argument is a string\ncontaining your API authentication key as found in your\n[DeepL Pro Account][pro-account].\n\nBe careful not to expose your key, for example when sharing source code.\n\n```python\nimport deepl\n\nauth_key = \"f63c02c5-f056-...\" # Replace with your key\ntranslator = deepl.Translator(auth_key)\n\nresult = translator.translate_text(\"Hello, world!\", target_lang=\"FR\")\nprint(result.text) # \"Bonjour, le monde !\"\n```\n\nThis example is for demonstration purposes only. In production code, the\nauthentication key should not be hard-coded, but instead fetched from a\nconfiguration file or environment variable.\n\n`Translator` accepts additional options, see [Configuration](#configuration)\nfor more information.\n\n### Translating text\n\nTo translate text, call `translate_text()`. The first argument is a string\ncontaining the text you want to translate, or a list of strings if you want to\ntranslate multiple texts.\n\n`source_lang` and `target_lang` specify the source and target language codes\nrespectively. The `source_lang` is optional, if it is unspecified the source\nlanguage will be auto-detected.\n\nLanguage codes are **case-insensitive** strings according to ISO 639-1, for\nexample `'DE'`, `'FR'`, `'JA''`. Some target languages also include the regional\nvariant according to ISO 3166-1, for example `'EN-US'`, or `'PT-BR'`. The full\nlist of supported languages is in the\n[API documentation][api-docs-lang-list].\n\nThere are additional optional arguments to control translation, see\n[Text translation options](#text-translation-options) below.\n\n`translate_text()` returns a `TextResult`, or a list of `TextResult`s\ncorresponding to your input text(s). `TextResult` has the following properties:\n- `text` is the translated text,\n- `detected_source_lang` is the detected source language code,\n- `billed_characters` is the number of characters billed for the translation.\n- `model_type_used` indicates the translation model used, but is `None` unless\n the `model_type` option is specified. \n\n```python\n# Translate text into a target language, in this case, French:\nresult = translator.translate_text(\"Hello, world!\", target_lang=\"FR\")\nprint(result.text) # \"Bonjour, le monde !\"\n\n# Translate multiple texts into British English\nresult = translator.translate_text(\n [\"\u304a\u5143\u6c17\u3067\u3059\u304b\uff1f\", \"\u00bfC\u00f3mo est\u00e1s?\"],\n target_lang=\"EN-GB\",\n)\nprint(result[0].text) # \"How are you?\"\nprint(result[0].detected_source_lang) # \"JA\" the language code for Japanese\nprint(result[0].billed_characters) # 7 - the number of characters in the source text \"\u304a\u5143\u6c17\u3067\u3059\u304b\uff1f\"\nprint(result[1].text) # \"How are you?\"\nprint(result[1].detected_source_lang) # \"ES\" the language code for Spanish\nprint(result[1].billed_characters) # 12 - the number of characters in the source text \"\u00bfC\u00f3mo est\u00e1s?\"\n\n# Translate into German with less and more Formality:\nprint(\n translator.translate_text(\n \"How are you?\", target_lang=\"DE\", formality=\"less\"\n )\n) # 'Wie geht es dir?'\nprint(\n translator.translate_text(\n \"How are you?\", target_lang=\"DE\", formality=\"more\"\n )\n) # 'Wie geht es Ihnen?'\n```\n\n#### Text translation options\n\nIn addition to the input text(s) argument, the available `translate_text()`\narguments are:\n\n- `source_lang`: Specifies the source language code, but may be omitted to\n auto-detect the source language.\n- `target_lang`: Required. Specifies the target language code.\n- `split_sentences`: specify how input text should be split into sentences,\n default: `'on'`.\n - `'on''` (`SplitSentences.ON`): input text will be split into sentences\n using both newlines and punctuation.\n - `'off'` (`SplitSentences.OFF`): input text will not be split into\n sentences. Use this for applications where each input text contains only\n one sentence.\n - `'nonewlines'` (`SplitSentences.NO_NEWLINES`): input text will be split\n into sentences using punctuation but not newlines.\n- `preserve_formatting`: controls automatic-formatting-correction. Set to `True`\n to prevent automatic-correction of formatting, default: `False`.\n- `formality`: controls whether translations should lean toward informal or\n formal language. This option is only available for some target languages, see\n [Listing available languages](#listing-available-languages).\n - `'less'` (`Formality.LESS`): use informal language.\n - `'more'` (`Formality.MORE`): use formal, more polite language.\n- `glossary`: specifies a glossary to use with translation, either as a string\n containing the glossary ID, or a `GlossaryInfo` as returned by\n `get_glossary()`.\n- `context`: specifies additional context to influence translations, that is not\n translated itself. Characters in the `context` parameter are not counted toward billing.\n See the [API documentation][api-docs-context-param] for more information and \n example usage.\n- `model_type`: specifies the type of translation model to use, options are:\n - `'quality_optimized'` (`ModelType.QUALITY_OPTIMIZED`): use a translation\n model that maximizes translation quality, at the cost of response time. \n This option may be unavailable for some language pairs.\n - `'prefer_quality_optimized'` (`ModelType.PREFER_QUALITY_OPTIMIZED`): use \n the highest-quality translation model for the given language pair.\n - `'latency_optimized'` (`ModelType.LATENCY_OPTIMIZED`): use a translation\n model that minimizes response time, at the cost of translation quality.\n- `tag_handling`: type of tags to parse before translation, options are `'html'`\n and `'xml'`.\n\nThe following options are only used if `tag_handling` is `'xml'`:\n\n- `outline_detection`: specify `False` to disable automatic tag detection,\n default is `True`.\n- `splitting_tags`: list of XML tags that should be used to split text into\n sentences. Tags may be specified as an array of strings (`['tag1', 'tag2']`),\n or a comma-separated list of strings (`'tag1,tag2'`). The default is an empty\n list.\n- `non_splitting_tags`: list of XML tags that should not be used to split text\n into sentences. Format and default are the same as for `splitting_tags`.\n- `ignore_tags`: list of XML tags that containing content that should not be\n translated. Format and default are the same as for `splitting_tags`.\n\nFor a detailed explanation of the XML handling options, see the\n[API documentation][api-docs-xml-handling].\n\n### Translating documents\n\nTo translate documents, you may call either `translate_document()` using file IO\nobjects, or `translate_document_from_filepath()` using file paths. For both\nfunctions, the first and second arguments correspond to the input and output\nfiles respectively.\n\nJust as for the `translate_text()` function, the `source_lang` and\n`target_lang` arguments specify the source and target language codes.\n\nThere are additional optional arguments to control translation, see\n[Document translation options](#document-translation-options) below.\n\n```python\n# Translate a formal document from English to German\ninput_path = \"/path/to/Instruction Manual.docx\"\noutput_path = \"/path/to/Bedienungsanleitung.docx\"\ntry:\n # Using translate_document_from_filepath() with file paths \n translator.translate_document_from_filepath(\n input_path,\n output_path,\n target_lang=\"DE\",\n formality=\"more\"\n )\n\n # Alternatively you can use translate_document() with file IO objects\n with open(input_path, \"rb\") as in_file, open(output_path, \"wb\") as out_file:\n translator.translate_document(\n in_file,\n out_file,\n target_lang=\"DE\",\n formality=\"more\"\n )\n\nexcept deepl.DocumentTranslationException as error:\n # If an error occurs during document translation after the document was\n # already uploaded, a DocumentTranslationException is raised. The\n # document_handle property contains the document handle that may be used to\n # later retrieve the document from the server, or contact DeepL support.\n doc_id = error.document_handle.id\n doc_key = error.document_handle.key\n print(f\"Error after uploading ${error}, id: ${doc_id} key: ${doc_key}\")\nexcept deepl.DeepLException as error:\n # Errors during upload raise a DeepLException\n print(error)\n```\n\n`translate_document()` and `translate_document_from_filepath()` are convenience\nfunctions that wrap multiple API calls: uploading, polling status until the\ntranslation is complete, and downloading. If your application needs to execute\nthese steps individually, you can instead use the following functions directly:\n\n- `translate_document_upload()`,\n- `translate_document_get_status()` (or\n `translate_document_wait_until_done()`), and\n- `translate_document_download()`\n\n#### Document translation options\n\nIn addition to the input file, output file, `source_lang` and `target_lang`\narguments, the available `translate_document()` and\n`translate_document_from_filepath()` arguments are:\n\n- `formality`: same as in [Text translation options](#text-translation-options).\n- `glossary`: same as in [Text translation options](#text-translation-options).\n- `output_format`: (`translate_document()` only)\n file extension of desired format of translated file, for example: `'pdf'`. If\n unspecified, by default the translated file will be in the same format as the\n input file. \n\n### Glossaries\n\nGlossaries allow you to customize your translations using user-defined terms.\nMultiple glossaries can be stored with your account, each with a user-specified\nname and a uniquely-assigned ID.\n\n#### Creating a glossary\n\nYou can create a glossary with your desired terms and name using\n`create_glossary()`. Each glossary applies to a single source-target language\npair. Note: Glossaries are only supported for some language pairs, see\n[Listing available glossary languages](#listing-available-glossary-languages)\nfor more information. The entries should be specified as a dictionary.\n\nIf successful, the glossary is created and stored with your DeepL account, and\na `GlossaryInfo` object is returned including the ID, name, languages and entry\ncount.\n\n```python\n# Create an English to German glossary with two terms:\nentries = {\"artist\": \"Maler\", \"prize\": \"Gewinn\"}\nmy_glossary = translator.create_glossary(\n \"My glossary\",\n source_lang=\"EN\",\n target_lang=\"DE\",\n entries=entries,\n)\nprint(\n f\"Created '{my_glossary.name}' ({my_glossary.glossary_id}) \"\n f\"{my_glossary.source_lang}->{my_glossary.target_lang} \"\n f\"containing {my_glossary.entry_count} entries\"\n)\n# Example: Created 'My glossary' (559192ed-8e23-...) EN->DE containing 2 entries\n```\n\nYou can also upload a glossary downloaded from the DeepL website using\n`create_glossary_from_csv()`. Instead of supplying the entries as a dictionary,\nspecify the CSV data as `csv_data` either as a file-like object or string or\nbytes containing file content:\n\n```python\n# Open the CSV file assuming UTF-8 encoding. If your file contains a BOM,\n# consider using encoding='utf-8-sig' instead.\nwith open('/path/to/glossary_file.csv', 'r', encoding='utf-8') as csv_file:\n csv_data = csv_file.read() # Read the file contents as a string\n my_csv_glossary = translator.create_glossary_from_csv(\n \"CSV glossary\",\n source_lang=\"EN\",\n target_lang=\"DE\",\n csv_data=csv_data,\n )\n```\n\nThe [API documentation][api-docs-csv-format] explains the expected CSV format in\ndetail.\n\n#### Getting, listing and deleting stored glossaries\n\nFunctions to get, list, and delete stored glossaries are also provided:\n\n- `get_glossary()` takes a glossary ID and returns a `GlossaryInfo` object for a\n stored glossary, or raises an exception if no such glossary is found.\n- `list_glossaries()` returns a list of `GlossaryInfo` objects corresponding to\n all of your stored glossaries.\n- `delete_glossary()` takes a glossary ID or `GlossaryInfo` object and deletes\n the stored glossary from the server, or raises an exception if no such\n glossary is found.\n\n```python\n# Retrieve a stored glossary using the ID\nglossary_id = \"559192ed-8e23-...\"\nmy_glossary = translator.get_glossary(glossary_id)\n\n# Find and delete glossaries named 'Old glossary'\nglossaries = translator.list_glossaries()\nfor glossary in glossaries:\n if glossary.name == \"Old glossary\":\n translator.delete_glossary(glossary)\n```\n\n#### Listing entries in a stored glossary\n\nThe `GlossaryInfo` object does not contain the glossary entries, but instead\nonly the number of entries in the `entry_count` property.\n\nTo list the entries contained within a stored glossary, use\n`get_glossary_entries()` providing either the `GlossaryInfo` object or glossary\nID:\n\n```python\nentries = translator.get_glossary_entries(my_glossary)\nprint(entries) # \"{'artist': 'Maler', 'prize': 'Gewinn'}\"\n```\n\n#### Using a stored glossary\n\nYou can use a stored glossary for text translation by setting the `glossary`\nargument to either the glossary ID or `GlossaryInfo` object. You must also\nspecify the `source_lang` argument (it is required when using a glossary):\n\n```python\ntext = \"The artist was awarded a prize.\"\nwith_glossary = translator.translate_text(\n text, source_lang=\"EN\", target_lang=\"DE\", glossary=my_glossary,\n)\nprint(with_glossary) # \"Der Maler wurde mit einem Gewinn ausgezeichnet.\"\n\n# For comparison, the result without a glossary:\nwithout_glossary = translator.translate_text(text, target_lang=\"DE\")\nprint(without_glossary) # \"Der K\u00fcnstler wurde mit einem Preis ausgezeichnet.\"\n```\n\nUsing a stored glossary for document translation is the same: set the `glossary`\nargument and specify the `source_lang` argument:\n\n```python\ntranslator.translate_document(\n in_file, out_file, source_lang=\"EN\", target_lang=\"DE\", glossary=my_glossary,\n)\n```\n\nThe `translate_document()`, `translate_document_from_filepath()` and\n`translate_document_upload()` functions all support the `glossary` argument.\n\n### Checking account usage\n\nTo check account usage, use the `get_usage()` function.\n\nThe returned `Usage` object contains three usage subtypes: `character`,\n`document` and `team_document`. Depending on your account type, some usage\nsubtypes may be invalid; this can be checked using the `valid` property. For API\naccounts:\n\n- `usage.character.valid` is `True`,\n- `usage.document.valid` and `usage.team_document.valid` are `False`.\n\nEach usage subtype (if valid) has `count` and `limit` properties giving the\namount used and maximum amount respectively, and the `limit_reached` property\nthat checks if the usage has reached the limit. The top level `Usage` object has\nthe `any_limit_reached` property to check all usage subtypes.\n\n```python\nusage = translator.get_usage()\nif usage.any_limit_reached:\n print('Translation limit reached.')\nif usage.character.valid:\n print(\n f\"Character usage: {usage.character.count} of {usage.character.limit}\")\nif usage.document.valid:\n print(f\"Document usage: {usage.document.count} of {usage.document.limit}\")\n```\n\n### Listing available languages\n\nYou can request the list of languages supported by DeepL for text and documents\nusing the `get_source_languages()` and `get_target_languages()` functions. They\nboth return a list of `Language` objects.\n\nThe `name` property gives the name of the language in English, and the `code`\nproperty gives the language code. The `supports_formality` property only appears\nfor target languages, and indicates whether the target language supports the\noptional `formality` parameter.\n\n```python\nprint(\"Source languages:\")\nfor language in translator.get_source_languages():\n print(f\"{language.name} ({language.code})\") # Example: \"German (DE)\"\n\nprint(\"Target languages:\")\nfor language in translator.get_target_languages():\n if language.supports_formality:\n print(f\"{language.name} ({language.code}) supports formality\")\n # Example: \"Italian (IT) supports formality\"\n else:\n print(f\"{language.name} ({language.code})\")\n # Example: \"Lithuanian (LT)\"\n```\n\n#### Listing available glossary languages\n\nGlossaries are supported for a subset of language pairs. To retrieve those\nlanguages use the `get_glossary_languages()` function, which returns an array\nof `GlossaryLanguagePair` objects. Each has `source_lang` and `target_lang`\nproperties indicating that that pair of language codes is supported.\n\n```python\nglossary_languages = translator.get_glossary_languages()\nfor language_pair in glossary_languages:\n print(f\"{language_pair.source_lang} to {language_pair.target_lang}\")\n # Example: \"EN to DE\", \"DE to EN\", etc.\n```\n\nYou can also find the list of supported glossary language pairs in the\n[API documentation][api-docs-glossary-lang-list].\n\nNote that glossaries work for all target regional-variants: a glossary for the\ntarget language English (`\"EN\"`) supports translations to both American English\n(`\"EN-US\"`) and British English (`\"EN-GB\"`).\n\n### Writing a Plugin\n\nIf you use this library in an application, please identify the application with\n`deepl.Translator.set_app_info`, which needs the name and version of the app:\n\n```python\ntranslator = deepl.Translator(...).set_app_info(\"sample_python_plugin\", \"1.0.2\")\n```\n\nThis information is passed along when the library makes calls to the DeepL API.\nBoth name and version are required. Please note that setting the `User-Agent` header\nvia `deepl.http_client.user_agent` will override this setting, if you need to use this,\nplease manually identify your Application in the `User-Agent` header.\n\n### Exceptions\n\nAll module functions may raise `deepl.DeepLException` or one of its subclasses.\nIf invalid arguments are provided, they may raise the standard exceptions\n`ValueError` and `TypeError`.\n\n### Configuration\n\n#### Logging\n\nLogging can be enabled to see the HTTP requests sent and responses received by\nthe library. Enable and control logging using Python's `logging` module, for\nexample:\n\n```python\nimport logging\n\nlogging.basicConfig()\nlogging.getLogger('deepl').setLevel(logging.DEBUG)\n```\n\n#### Server URL configuration\n\nYou can override the URL of the DeepL API by specifying the `server_url`\nargument when constructing a `deepl.Translator`. This may be useful for testing\npurposes. You **do not** need to specify the URL to distinguish API Free and API\nPro accounts, the library selects the correct URL automatically.\n\n```python\nserver_url = \"http://user:pass@localhost:3000\"\ntranslator = deepl.Translator(..., server_url=server_url)\n```\n\n#### Proxy configuration\n\nYou can configure a proxy by specifying the `proxy` argument when constructing a\n`deepl.Translator`:\n\n```python\nproxy = \"http://user:pass@10.10.1.10:3128\"\ntranslator = deepl.Translator(..., proxy=proxy)\n```\n\nThe proxy argument is passed to the underlying `requests` session, see the\n[documentation for requests][requests-proxy-docs]; a dictionary of schemes to\nproxy URLs is also accepted.\n\n#### Override SSL verification\n\nYou can control how `requests` performs SSL verification by specifying the \n`verify_ssl` option when constructing a `deepl.Translator`, for example to\ndisable SSL certificate verification:\n\n```python\ntranslator = deepl.Translator(..., verify_ssl=False)\n```\n\nThis option is passed to the underlying `requests` session as the `verify`\noption, see the [documentation for requests][requests-verify-ssl-docs].\n\n#### Configure automatic retries\n\nThis SDK will automatically retry failed HTTP requests (if the failures could\nbe transient, e.g. a HTTP 429 status code). This behaviour can be configured\nin `http_client.py`, for example by default the number of retries is 5. This\ncan be changed to 3 as follows:\n\n```python\nimport deepl\n\ndeepl.http_client.max_network_retries = 3\nt = deepl.Translator(...)\nt.translate_text(...)\n```\n\nYou can configure the timeout `min_connection_timeout` the same way, as well\nas set a custom `user_agent`, see the next section.\n\n#### Anonymous platform information\n\nBy default, we send some basic information about the platform the client library is running on with each request, see [here for an explanation](https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/User-Agent). This data is completely anonymous and only used to improve our product, not track any individual users. If you do not wish to send this data, you can opt-out when creating your `deepl.Translator` object by setting the `send_platform_info` flag like so:\n\n```python\ntranslator = deepl.Translator(..., send_platform_info=False)\n```\n\nYou can also customize the `user_agent` by setting its value explicitly before constructing your `deepl.Translator` object.\n\n```python\ndeepl.http_client.user_agent = 'my custom user agent'\ntranslator = deepl.Translator(os.environ[\"DEEPL_AUTH_KEY\"])\n```\n\n## Command Line Interface\n\nThe library can be run on the command line supporting all API functions. Use the\n`--help` option for usage information:\n\n```shell\npython3 -m deepl --help\n```\n\nThe CLI requires your DeepL authentication key specified either as the\n`DEEPL_AUTH_KEY` environment variable, through the `keyring` module, or\nusing the `--auth-key` option, for example:\n\n```shell\npython3 -m deepl --auth-key=YOUR_AUTH_KEY usage\n```\n\nNote that the `--auth-key` argument must appear *before* the command argument.\nTo use the [keyring](https://pypi.org/project/keyring/) module, set the \n*DEEPL_AUTH_KEY* field in the service *deepl* to your API key.\nThe recognized commands are:\n\n| Command | Description |\n| :-------- | :----------------------------------------------------- |\n| text | translate text(s) |\n| document | translate document(s) |\n| usage | print usage information for the current billing period |\n| languages | print available languages |\n| glossary | create, list, and remove glossaries |\n\nFor example, to translate text:\n\n```shell\npython3 -m deepl --auth-key=YOUR_AUTH_KEY text --to=DE \"Text to be translated.\"\n```\n\nWrap text arguments in quotes to prevent the shell from splitting sentences into\nwords.\n\n## Issues\n\nIf you experience problems using the library, or would like to request a new\nfeature, please open an [issue][issues].\n\n## Development\n\nWe welcome Pull Requests, please read the\n[contributing guidelines](CONTRIBUTING.md).\n\n### Tests\n\nExecute the tests using `pytest`. The tests communicate with the DeepL API using\nthe auth key defined by the `DEEPL_AUTH_KEY` environment variable.\n\nBe aware that the tests make DeepL API requests that contribute toward your API\nusage.\n\nThe test suite may instead be configured to communicate with the mock-server\nprovided by [deepl-mock][deepl-mock]. Although most test cases work for either,\nsome test cases work only with the DeepL API or the mock-server and will be\notherwise skipped. The test cases that require the mock-server trigger server\nerrors and test the client error-handling. To execute the tests using\ndeepl-mock, run it in another terminal while executing the tests. Execute the\ntests using `pytest` with the `DEEPL_MOCK_SERVER_PORT` and `DEEPL_SERVER_URL`\nenvironment variables defined referring to the mock-server.\n\n[api-docs]: https://www.deepl.com/docs-api?utm_source=github&utm_medium=github-python-readme\n\n[api-docs-csv-format]: https://www.deepl.com/docs-api/managing-glossaries/supported-glossary-formats/?utm_source=github&utm_medium=github-python-readme\n\n[api-docs-xml-handling]: https://www.deepl.com/docs-api/handling-xml/?utm_source=github&utm_medium=github-python-readme\n\n[api-docs-context-param]: https://www.deepl.com/docs-api/translating-text/?utm_source=github&utm_medium=github-python-readme\n\n[api-docs-lang-list]: https://www.deepl.com/docs-api/translating-text/?utm_source=github&utm_medium=github-python-readme\n\n[api-docs-glossary-lang-list]: https://www.deepl.com/docs-api/managing-glossaries/?utm_source=github&utm_medium=github-python-readme\n\n[bug-report-ubuntu-2204]: https://bugs.launchpad.net/ubuntu/+source/poetry/+bug/1958227\n\n[create-account]: https://www.deepl.com/pro?utm_source=github&utm_medium=github-python-readme#developer\n\n[deepl-mock]: https://www.github.com/DeepLcom/deepl-mock\n\n[issues]: https://www.github.com/DeepLcom/deepl-python/issues\n\n[pypi-project]: https://pypi.org/project/deepl/\n\n[pro-account]: https://www.deepl.com/pro-account/?utm_source=github&utm_medium=github-python-readme\n\n[python-version-list]: https://devguide.python.org/versions/\n\n[requests-proxy-docs]: https://docs.python-requests.org/en/latest/user/advanced/#proxies\n\n[requests-verify-ssl-docs]: https://docs.python-requests.org/en/latest/user/advanced/#ssl-cert-verification\n",
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