semvec/pypi-packages huggingface dataset:
pydeepl 0.13
A python API wrapper for DeepL translating service.
Keywords: deepl,API,translate,translation

Note: The comercial `DeepL API <https://www.deepl.com/api.html>`_ has been released. You should use it instead subscribing to DeepL Pro.
========================================================================================================================================

pydeepl
=======
.. image:: https://api.travis-ci.org/EmilioK97/pydeepl.svg?branch=master


A Python API wrapper for the `DeepL <https://www.deepl.com/>`_ translation service.

Installation
------------

.. code:: python

    pip install pydeepl

Getting Started
---------------

Python Version
~~~~~~~~~~~~~~

Pydeepl was written for both Python 2 and Python 3.

Add pydeepl to your application
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

    import pydeepl

    sentence = 'I like turtles.'
    from_language = 'EN'
    to_language = 'ES'

    translation = pydeepl.translate(sentence, to_language, from_lang=from_language)
    print(translation)

    # Using auto-detection
    translation = pydeepl.translate(sentence, to_language)
    print(translation)

Supported Languages
-------------------

Pydeepl supports these languages:

+--------+-----------------+
| Code   | Language        |
+========+=================+
| auto   | *Auto detect*   |
+--------+-----------------+
| DE     | German          |
+--------+-----------------+
| EN     | English         |
+--------+-----------------+
| FR     | French          |
+--------+-----------------+
| ES     | Spanish         |
+--------+-----------------+
| IT     | Italian         |
+--------+-----------------+
| NL     | Dutch           |
+--------+-----------------+
| PL     | Polish          |
+--------+-----------------+

    Note that auto detection is only possible for the source language.

Disclaimer
----------

DeepL is a product from DeepL GmbH. More info:
`deepl.com/publisher.html <https://www.deepl.com/publisher.html>`__

This package has been heavily inspired by
`node-deepls <https://github.com/pbrln/node-deepl>`__ and
`DeepLy <https://github.com/chriskonnertz/DeepLy>`__.

License
-------

This project is licensed under the MIT License - see the
`LICENSE <LICENSE>`__ file for details
excelschema 0.1.2.4
Excel records' parser and schema viewing and validating tools.
Keywords: excel

# excelschema

Excel records' parser and schema viewing and validating tools.

## Installation

Method 1:

```
$ pip install excelschema
```

Method 2:
- Clone the project from GitHub
- `poetry install`

## Usage

To read an Excel file, you may also need to install [`pyexcel`](https://github.com/pyexcel/pyexcel) and [`pyexcel-xlsx`](https://github.com/pyexcel/pyexcel-xlsx) as well.

```python
>>> from excelschema import SchemaParser
>>> import pyexcel
>>> sp = SchemaParser(records=pyexcel.get_records(file_name='foo.xlsx', sheet_name='bar'))
>>> sp.schema
{
    'record_id': <class 'int'>,
    'modified': <class 'datetime.datetime'>,
    'data': <class 'str'>
}
```

Validating records and convert it to a usable one.

```python
>>> sp.ensure_one({'record_id': ' 12', 'data': 567})
{'record_id', 12, 'data': '567'}
```

Setting constraints

```python
>>> from excelschema import Constraint
>>> sp.update_schema({
...     'user_id': Constraint(type_=int, unique=True, not_null=True)
... })
```

It is also possible to create an custom schema without an Excel

```python
>>> sp = SchemaParser(schema={
...     'record_id': Constraint(type_=int, unique=True, not_null=True),
...     'modified': datetime
... })
```

## Bonus functions

Cleaning dirty Excel records

```python
>>> from excelschema import parse_record
>>> parse_record({'foo': ' 1', 'bar': ' - ', 'baz': ' '})
{'foo', 1}
```


## Related projects

- https://github.com/patarapolw/tinydb-constraint