Feature/spacy requirements (#29)

* Update requirements 📌

* Bump version 🔖

* 🎨

* Update readme file 📝

* ✅

README.md

@@ -16,6 +16,8 @@ pip install spacy-udpipe
 
 After installation, use `spacy_udpipe.download()` to download the pre-trained model for the desired language.
 
+A full list of pre-trained UDPipe models for supported languages can be found in [`languages.json`](https://github.com/TakeLab/spacy-udpipe/blob/master/spacy_udpipe/languages.json).
+
 ## Usage
 The loaded UDPipeLanguage class returns a spaCy [`Language` object](https://spacy.io/api/language), i.e., the object you can use to process text and create a [`Doc` object](https://spacy.io/api/doc).
 
@@ -39,7 +41,7 @@ The type of `text` can be one of the following:
   * presegmented: `List[str]`,
   * pretokenized: `List[List[str]]`.
 
-#### Loading a custom model
+### Loading a custom model
 The following code snippet demonstrates how to load a custom `UDPipe` model (for the Croatian language):
 ```python
 import spacy_udpipe
@@ -55,25 +57,20 @@ for token in doc:
 ```
 This can be done for any of the languages supported by spaCy. For an exhaustive list, see [spaCy languages](https://spacy.io/usage/models#languages).
 
-## Authors and acknowledgment
-Created by [Antonio Šajatović](http://github.com/asajatovic) during an internship at [Text Analysis and Knowledge Engineering Lab (TakeLab)](http://takelab.fer.hr/).
-
 ## Contributing
 Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
 
 Please make sure to update the tests as appropriate. Tests are run automatically for each pull request on the master branch.
 To start the tests locally, first, install the package with `pip install -e .`, then run [`pytest`](https://docs.pytest.org/en/latest/contents.html) in the root source directory.
 
 ## License
-[MIT](https://choosealicense.com/licenses/mit/) © Text Analysis and Knowledge Engineering Lab (TakeLab)
+* Source code: [MIT](https://choosealicense.com/licenses/mit/) © Text Analysis and Knowledge Engineering Lab (TakeLab)
+* Available pre-trained models: [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
 
 ## Project status
 Maintained by [Text Analysis and Knowledge Engineering Lab (TakeLab)](http://takelab.fer.hr/).
 
 ## Notes
-* All available pre-trained models are licensed under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
-
-* A full list of pre-trained models for supported languages is available in [`languages.json`](https://github.com/TakeLab/spacy-udpipe/blob/master/spacy_udpipe/languages.json).
 
 * This package exposes a `spacy_languages` entry point in its [`setup.py`](https://github.com/TakeLab/spacy-udpipe/blob/master/setup.py) so full suport for serialization is enabled:
     ```python

requirements.txt

@@ -1,4 +1,4 @@
-spacy>=2.1.0
+spacy>=2.1.0,<3.0.0
 ufal.udpipe>=1.2.0
 # Development dependencies
 pytest>=5.0.0

setup.py

@@ -54,7 +54,7 @@ def get_version(fname: str) -> str:
     license="MIT",
     keywords="nlp udpipe spacy python",
     packages=setuptools.find_packages(),
-    install_requires=["spacy>=2.1.0", "ufal.udpipe>=1.2.0"],
+    install_requires=["spacy>=2.1.0,<3.0.0", "ufal.udpipe>=1.2.0"],
     python_requires=">=3.6",
     entry_points=ENTRY_POINTS,
     tests_require=["pytest>=5.0.0"],

spacy_udpipe/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.3.1"
+__version__ = "0.3.2"
 __all__ = ["UDPipeLanguage", "UDPipeModel",
            "load", "load_from_path", "download"]
 

spacy_udpipe/utils.py

@@ -14,7 +14,7 @@
 
 def _check_language(lang: str) -> None:
     if lang not in LANGUAGES:
-        raise Exception("'{}' language not available".format(lang))
+        raise Exception(f"'{lang}' language not available")
 
 
 def _check_models_dir(lang: str) -> None:

tests/test_spacy_udpipe.py

@@ -7,7 +7,7 @@
 
 EN = "en"
 RO = "ro"
-SPACY_VERSION = "2.2.4"
+SPACY_VERSION = "3.0.0"
 
 
 @pytest.fixture