https://github.com/DeepLcom/deepl-python

Official Python library for the DeepL language translation API.
https://github.com/DeepLcom/deepl-python

api deepl i18n language official python translation translator

Last synced: 3 months ago
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Official Python library for the DeepL language translation API.

• Host: GitHub
• URL: https://github.com/DeepLcom/deepl-python
• Owner: DeepLcom
• License: mit
• Created: 2021-07-19T13:12:53.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2025-05-30T09:17:48.000Z (5 months ago)
• Last Synced: 2025-06-22T05:19:52.874Z (4 months ago)
• Topics: api, deepl, i18n, language, official, python, translation, translator
• Language: Python
• Homepage: https://www.deepl.com
• Size: 695 KB
• Stars: 1,245
• Watchers: 27
• Forks: 84
• Open Issues: 40
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md

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README

          
# DeepL Python Library

[![PyPI version](https://img.shields.io/pypi/v/deepl.svg)](https://pypi.org/project/deepl/)

[![Supported Python versions](https://img.shields.io/pypi/pyversions/deepl.svg)](https://pypi.org/project/deepl/)

[![License: MIT](https://img.shields.io/badge/license-MIT-blueviolet.svg)](https://github.com/DeepLcom/deepl-python/blob/main/LICENSE)

The [DeepL API][api-docs] is a language AI API that allows other computer programs

to send texts and documents to DeepL's servers and receive high-quality

translations and improvements to the text. 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 consume 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 `DeepLClient`. 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

deepl_client = deepl.DeepLClient(auth_key)

result = deepl_client.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.

`DeepLClient` 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 = deepl_client.translate_text("Hello, world!", target_lang="FR")

print(result.text)  # "Bonjour, le monde !"

# Translate multiple texts into British English

result = deepl_client.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(

    deepl_client.translate_text(

        "How are you?", target_lang="DE", formality="less"

    )

)  # 'Wie geht es dir?'

print(

    deepl_client.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].

### Improving text (Write API)

You can use the Write API to improve or rephrase text. This is implemented in

the `rephrase_text()` method. 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.

`target_lang` optionally specifies the target language, e.g. when you want to change

the variant of a text (for example, you can send an english text to the write API and

use `target_lang` to turn it into British or American English). Please note that the

Write API itself does NOT translate. If you wish to translate and improve a text, you

will need to make multiple calls in a chain.

Language codes are the same as for translating text.

Example call:

```python

result = deepl_client.rephrase_text("A rainbouw has seven colours.", target_lang="EN-US")

print(result.text)

```

Additionally, you can optionally specify a style OR a tone (not both at once) that the

improvement should be in. The following styles are supported (`default` will be used if

nothing is selected):

- `academic`

- `business`

- `casual`

- `default`

- `simple`

The following tones are supported (`default` will be used if nothing is selected):

- `confident`

- `default`

- `diplomatic`

- `enthusiastic`

- `friendly`

You can also prefix any non-default style or tone with `prefer_` (`prefer_academic`, etc.),

in which case the style/tone will only be applied if the language supports it. If you do not

use `prefer_`, requests with `target_lang`s or detected languages that do not support

styles and tones will fail. The current list of supported languages can be found in our

[API documentation][api-docs]. We plan to also expose this information via an API endpoint

in the future.

You can use the predefined constants in the library to use a style:

```python

result = deepl_client.rephrase_text(

    "A rainbouw has seven colours.", target_lang="EN-US", style=WritingStyle.BUSINESS.value

)

print(result.text)

```

### 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 

    deepl_client.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:

        deepl_client.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.

#### v2 versus v3 glossary APIs

The newest version of the glossary APIs are the `/v3` endpoints, allowing both

editing functionality plus support for multilingual glossaries. New methods and

objects have been created to support interacting with these new glossaries. 

Due to this  new functionality, users are recommended to utilize these 

multilingual glossary methods. However, to continue using the `v2` glossary API 

endpoints, please continue to use the existing endpoints in the `translator.py` 

(e.g. `create_glossary()`, `get_glossary()`, etc).

To migrate to use the new multilingual glossary methods from the current 

monolingual glossary methods, please refer to 

[this migration guide](upgrading_to_multilingual_glossaries.md).

The following sections describe how to interact with multilingual glossaries 

using the new functionality:

#### Creating a glossary

You can create a multi-lingual glossary with your desired terms and name using

`create_multilingual_glossary()`. Glossaries created via the /v3 endpoints can now 

support multiple source-target language pairs. 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 `MultilingualGlossaryInfo` object is returned including the ID, name, and glossary

dictionaries. The glossary dictionaries would be an array of 

`MultilingualGlossaryDictionaryInfo` objects, each containing its own languages and 

entry count.

```python

# Create a glossary with an English to German dictionary containing two terms:

entries = {"artist": "Maler", "prize": "Gewinn"}

dictionaries = [MultilingualGlossaryDictionaryEntries("EN", "DE", entries)]

my_glossary = deepl_client.create_multilingual_glossary(

    "My glossary",

    dictionaries

)

my_glossary_dict = my_glossary.dictionaries[0]

print(

    f"Created '{my_glossary.name}' ({my_glossary.glossary_id}) "

    f"with {len(my_glossary.dictionaries)} dictionary where "

    f"its language pair is {my_glossary_dict.source_lang}->"

    f"{my_glossary_dict.target_lang} containing "

    f"{my_glossary.entry_count} entries"

)

# Example: Created 'My glossary' (559192ed-8e23-...) with 1 dictionary where

# its language pair is EN->DE containing 2 entries

```

You can also upload a glossary downloaded from the DeepL website using

`create_multilingual_glossary_from_csv()`. Instead of supplying the entries as a 

dictionary within a MultilingualGlossaryDictionaryEntries object, you can 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 = deepl_client.create_multilingual_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_multilingual_glossary()` takes a glossary ID and returns a 

  `MultilingualGlossaryInfo` object for a stored glossary, or raises an 

  exception if no such glossary is found.

- `list_multilingual_glossaries()` returns a list of `MultilingualGlossaryInfo` objects 

  corresponding to all of your stored glossaries.

- `delete_multilingual_glossary()` takes a glossary ID or `MultilingualGlossaryInfo` 

  object and deletes the stored glossary from the server, or raises an 

  exception if no such glossary is found.

- `delete_multilingual_glossary_dictionary()` takes a glossary ID or `GlossaryInfo` object to 

  identify the glossary. Additionally takes in a source and target language or a 

  `MultilingualGlossaryDictionaryInfo` object and deletes the stored dictionary

   from the server, or raises an exception if no such glossary dictionary is found.

```python

# Retrieve a stored glossary using the ID

glossary_id = "559192ed-8e23-..."

my_glossary = deepl_client.get_multilingual_glossary(glossary_id)

# Delete a glossary dictionary from a stored glossary

deepl_client.delete_multilingual_glossary_dictionary(my_glossary, my_glossary.dictionaries[0])

# Find and delete glossaries named 'Old glossary'

glossaries = deepl_client.list_multilingual_glossaries()

for glossary in glossaries:

    if glossary.name == "Old glossary":

        deepl_client.delete_multilingual_glossary(glossary)

```

#### Listing entries in a stored glossary

The `MultilingualGlossaryInfo` 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_multilingual_glossary_entries()` providing either the `MultilingualGlossaryInfo` object or glossary

ID and either a `MultilingualGlossaryDictionaryInfo` or source and target language pair:

```python

entries = deepl_client.get_multilingual_glossary_entries(my_glossary, "EN", "DE")

print(entries.dictionaries[0])  # "{'artist': 'Maler', 'prize': 'Gewinn'}"

```

#### Editing a glossary

Functions to edit stored glossaries are also provided:

- `update_multilingual_glossary_dictionary()` takes a glossary ID or `MultilingualGlossaryInfo`

  object, plus a source language, target language, and a dictionary of entries.

  It will then either update the list of entries for that dictionary (either 

  inserting new entires or replacing the target phrase for any existing 

  entries) or will insert a new glossary dictionary if that language pair is 

  not currently in the stored glossary.

- `replace_multilingual_glossary_dictionary()` takes a glossary ID or `MultilingualGlossaryInfo`

  object, plus a source language, target language, and a dictionary of entries.

  It will then either set the entries to the parameter value, completely 

  replacing any pre-existing entries for that language pair.

- `update_multilingual_glossary_name()` takes a glossary ID or `MultilingualGlossaryInfo`

  object, plus the new name of the glossary. 

```python

# Update glossary dictionary

entries = {"artist": "Maler", "hello": "guten tag"}

dictionaries = [MultilingualGlossaryDictionaryEntries("EN", "DE", entries)]

my_glossary = deepl_client.create_multilingual_glossary(

    "My glossary",

    dictionaries

)

new_entries = {"hello": "hallo", "prize": "Gewinn"}

glossary_dict = MultilingualGlossaryDictionaryEntries("EN", "DE", new_entries)

updated_glossary = deepl_client.update_multilingual_glossary_dictionary(

    my_glossary,

    glossary_dict

)

entries_response = deepl_client.get_multilingual_glossary_entries(my_glossary, "EN", "DE")

print(entries_response.dictionaries[0])  # "{'artist': 'Maler', 'hello': 'hallo', 'prize': 'Gewinn'}"

# Update a glossary dictionary from CSV

# 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 = deepl_client.update_multilingual_glossary_dictionary_from_csv(

        glossary="4c81ffb4-2e...",

        source_lang="EN",

        target_lang="DE",

        csv_data=csv_data,

    )

# Replace glossary dictionary

replacement_entries = {"goodbye": "Auf Wiedersehen"}

glossary_dict = MultilingualGlossaryDictionaryEntries("EN", "DE", replacement_entries)

updated_glossary = deepl_client.replace_multilingual_glossary_dictionary(

  my_glossary,

  glossary_dict)

entries_response = deepl_client.get_multilingual_glossary_entries(my_glossary, "EN", "DE")

print(entries_response.dictionaries[0])  # "{'goodbye': 'Auf Wiedersehen'}"

# Replace a glossary dictionary from CSV

# 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 = deepl_client.replace_multilingual_glossary_dictionary_from_csv(

        glossary="4c81ffb4-2e...",

        source_lang="EN",

        target_lang="DE",

        csv_data=csv_data,

    )

# Update the glossary name

updated_glossary = deepl_client.update_multilingual_glossary_name(

  my_glossary,

  "My new glossary name"

)

print(updated_glossary.name) # 'My new glossary name'

```

#### 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`/`MultilingualGlossaryInfo` 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 = deepl_client.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 = deepl_client.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

deepl_client.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 = deepl_client.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 deepl_client.get_source_languages():

    print(f"{language.name} ({language.code})")  # Example: "German (DE)"

print("Target languages:")

for language in deepl_client.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 = deepl_client.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.DeepLClient.set_app_info`, which needs the name and version of the app:

```python

deepl_client = deepl.DeepLClient(...).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.DeepLClient`. 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"

deepl_client = deepl.DeepLClient(..., server_url=server_url)

```

#### Proxy configuration

You can configure a proxy by specifying the `proxy` argument when constructing a

`deepl.DeepLClient`:

```python

proxy = "http://user:pass@10.10.1.10:3128"

deepl_client = deepl.DeepLClient(..., 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.DeepLClient`, for example to

disable SSL certificate verification:

```python

deepl_client = deepl.DeepLClient(..., 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

c = deepl.DeepLClient(...)

c.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.DeepLClient` object by setting the `send_platform_info` flag like so:

```python

deepl_client = deepl.DeepLClient(..., send_platform_info=False)

```

You can also customize the `user_agent` by setting its value explicitly before constructing your `deepl.DeepLClient` object.

```python

deepl.http_client.user_agent = 'my custom user agent'

deepl_client = deepl.DeepLClient(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