I would like to make the default cache dir configurable with an environmental variable. This is a simple PR to allow one to do that with the variable DACY_CACHE_DIR.

dacy has a very tight version bound on some auxiliary libraries like protobuf. It's not apparent why this is required as it does not appear to be a library used internally, but it could of course be intentional. But the version is lagging enough that it is starting to cause compatibility problems with other libraries, so if it can be relaxed that would be very helpful.

After removing readability it would be nice with a tutorial on: "Extracting text statistics and readability metrics using DaCy and Textdescriptives"

Potentially using the packages to describe the examining the language complexity between conversational data and legal documents on DAGW or a similar task using a publicly available dataset.

The requirements of this package are unnecessarily strict. Specifically, I am having issues with tqdm. I have a more in-depth explaination in the issue that I create centre-for-humanities-computing/DaCy#75. There are also a few optimizations to your setup.py file. I notice that the requirements.txt file is not used, which could cause a mismatch when doing pip install -r requirements.txt and pip install .

updates:

• github.com/asottile/pyupgrade: v2.38.0 → v3.3.1
• github.com/asottile/add-trailing-comma: v2.3.0 → v2.4.0
• github.com/PyCQA/docformatter: v1.5.0 → v1.5.1
• github.com/psf/black: 22.8.0 → 22.12.0
• github.com/charliermarsh/ruff-pre-commit: v0.0.194 → v0.0.206

Moved from #133, originally posted by @EaLindhardt

I've tried to download dacy through anaconda, both with pip and conda install and the different ways of installing: https://centre-for-humanities-computing.github.io/DaCy/installation.html

when running

import dacy

i get the following

`--------------------------------------------------------------------------- ContextualVersionConflict Traceback (most recent call last) Input In [14], in <cell line: 1>() ----> 1 import dacy

File ~\AppData\Roaming\Python\Python39\site-packages\dacy_init_.py:4, in 1 from dacy.hate_speech import make_offensive_transformer # noqa 2 from dacy.sentiment import make_emotion_transformer # noqa ----> 4 from .about import download_url, title, version # noqa 5 from .download import download_model # noqa 6 from .load import load, models, where_is_my_dacy

File ~\AppData\Roaming\Python\Python39\site-packages\dacy\about.py:3, in 1 import pkg_resources ----> 3 version = pkg_resources.get_distribution("dacy").version 4 title = "dacy" 5 download_url = "https://github.com/centre-for-humanities-computing/DaCy"

File ~\Anaconda3\lib\site-packages\pkg_resources_init_.py:477, in get_distribution(dist) 475 dist = Requirement.parse(dist) 476 if isinstance(dist, Requirement): --> 477 dist = get_provider(dist) 478 if not isinstance(dist, Distribution): 479 raise TypeError("Expected string, Requirement, or Distribution", dist)

File ~\Anaconda3\lib\site-packages\pkg_resources_init_.py:353, in get_provider(moduleOrReq) 351 """Return an IResourceProvider for the named module or requirement""" 352 if isinstance(moduleOrReq, Requirement): --> 353 return working_set.find(moduleOrReq) or require(str(moduleOrReq))[0] 354 try: 355 module = sys.modules[moduleOrReq]

File ~\Anaconda3\lib\site-packages\pkg_resources_init_.py:897, in WorkingSet.require(self, *requirements) 888 def require(self, *requirements): 889 """Ensure that distributions matching requirements are activated 890 891 requirements must be a string or a (possibly-nested) sequence (...) 895 included, even if they were already activated in this working set. 896 """ --> 897 needed = self.resolve(parse_requirements(requirements)) 899 for dist in needed: 900 self.add(dist)

File ~\Anaconda3\lib\site-packages\pkg_resources_init_.py:788, in WorkingSet.resolve(self, requirements, env, installer, replace_conflicting, extras) 785 if dist not in req: 786 # Oops, the "best" so far conflicts with a dependency 787 dependent_req = required_by[req] --> 788 raise VersionConflict(dist, req).with_context(dependent_req) 790 # push the new requirements onto the stack 791 new_requirements = dist.requires(req.extras)[::-1]

ContextualVersionConflict: (spacy 3.3.1 (c:\users\au576018\anaconda3\lib\site-packages), Requirement.parse('spacy<3.3.0,>=3.2.0'), {'dacy'})`

How do I solve this?

@EaLindhardt will you please add the following information:

• DaCy Version Used:
• Operating System:
• Python Version Used:
• spaCy Version Used:
• Environment Information:

you can also type python -m spacy info --markdown and copy-paste the result here along with the DaCy version, which you can get using python -c "import dacy; print(dacy.__version__)"

Update WandbLogger in configs to v2. This version has the same experiment tracking features as v1 but also has model checkpointing and dataset versioning possibilities.

• [x] Entity augmentation
  • [x] Gender augmentation (awareness of gender)
  • [x] Second order person augmentation (Lastname, Firstname)
  • [ ] Usernames (autogenerates e.g. WhiteTruffle101 or Kenneth Enevoldsen -> KennethEnevoldsen)
• [ ] Mispellings Augmentations, se e.g. this repo
  • [x] Keystroke error based on keyboard distance
• [ ] Historic augmentations
  • [x]   æ->ae, å -> aa (and a), ø->oe
  • [ ] uppercasing of nouns
• [ ] Social media
  • [ ] Adding hashtags augmentation
• [ ] Others, potentially see this tweet or this kaggle summary

Updates the requirements on sphinxext-opengraph to permit the latest version.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

updates:

• github.com/asottile/pyupgrade: v2.34.0 → v2.37.3
• github.com/myint/docformatter: v1.3.1 → v1.5.0
• github.com/psf/black: 22.3.0 → 22.8.0
• github.com/PyCQA/flake8: 4.0.1 → 5.0.4

Bumps schneegans/dynamic-badges-action from 1.2.0 to 1.3.0.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

When running:

import dacy

for model in dacy.models():
    print(model)

dacy_nlp = dacy.load('medium')

doc = dacy_nlp("DaCy er en hurtig og effektiv pipeline til dansk sprogprocessering bygget i SpaCy.")

print('hej')

I get the following warning:

da_dacy_small_tft-0.0.0
da_dacy_medium_tft-0.0.0
da_dacy_large_tft-0.0.0
da_dacy_small_trf-0.1.0
da_dacy_medium_trf-0.1.0
da_dacy_large_trf-0.1.0
/venv/lib/python3.9/site-packages/spacy/util.py:833: UserWarning: [W095] Model 'da_dacy_medium_trf' (0.1.0) was trained with spaCy v3.1 and may not be 100% compatible with the current version (3.2.4). If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current spaCy version. For more details and available updates, run: python -m spacy validate
  warnings.warn(warn_msg)
/venv/lib/python3.9/site-packages/spacy/util.py:833: UserWarning: [W095] Model 'da_dacy_small_trf' (0.1.0) was trained with spaCy v3.1 and may not be 100% compatible with the current version (3.2.4). If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current spaCy version. For more details and available updates, run: python -m spacy validate
  warnings.warn(warn_msg)
/venv/lib/python3.9/site-packages/spacy_transformers/pipeline_component.py:406: UserWarning: Automatically converting a transformer component from spacy-transformers v1.0 to v1.1+. If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current spacy-transformers version. For more details and available updates, run: python -m spacy validate
  warnings.warn(warn_msg)
/venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:198: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
  warnings.warn('User provided device_type of \'cuda\', but CUDA is not available. Disabling')
/venv/lib/python3.9/site-packages/spacy/pipeline/attributeruler.py:150: UserWarning: [W036] The component 'matcher' does not have any patterns defined.
  matches = self.matcher(doc, allow_missing=True, as_spans=False)
hej

Notably this this includes three warning, including SpaCy version, cuda device and matcher object (see also #72)

originally version sent to me by mail

Note: While this is a warning there, DaCy still works as intended. The version of spaCy does not influence model performance.