Release 0.0.19

.github/workflows/docs.yml

@@ -8,6 +8,8 @@ on:
 jobs:
   doc_build:
     runs-on: ubuntu-latest
+    permissions:
+      contents: write
 
     steps:
     - name: checkout and set up

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "type_infer"
-version = "0.0.18"
+version = "0.0.19"
 description = "Automated type inference for Machine Learning pipelines."
 authors = ["MindsDB Inc. <[email protected]>"]
 license = "GPL-3.0"
@@ -19,7 +19,7 @@ psutil = "^5.9.0"
 toml = "^0.10.2"
 
 # rule based deps, part of core
-langid = "^1.1.6"
+py3langid = ">=0.2.2,<0.3"
 nltk = "^3"
 
 [build-system]

tests/unit_tests/test_helpers.py

@@ -1,6 +1,7 @@
 import unittest
 
 from type_infer import helpers
+from type_infer.rule_based.helpers import get_language_dist
 
 
 class TestCastStringToPythonType(unittest.TestCase):
@@ -32,3 +33,10 @@ def test_nan_is_numeric(self):
     def test_inf_is_numeric(self):
         self.assertTrue(helpers.is_nan_numeric('inf'))
         self.assertTrue(helpers.is_nan_numeric(float('inf')))
+
+
+class TestLangid(unittest.TestCase):
+    def test_get_language_dist(self):
+        dist = get_language_dist(['This is clearly English', 'Y esto es claramente español'])
+        self.assertTrue('en' in dist and dist['en'] == 1)
+        self.assertTrue('es' in dist and dist['es'] == 1)

type_infer/__init__.py

@@ -3,7 +3,7 @@
 from type_infer import api
 from type_infer import helpers
 
-__version__ = '0.0.18'
+__version__ = '0.0.19'
 
 
 __all__ = [

type_infer/rule_based/helpers.py

@@ -6,8 +6,8 @@
 
 import numpy as np
 import scipy.stats as st
-from langid.langid import LanguageIdentifier
-from langid.langid import model as langid_model
+from py3langid.langid import LanguageIdentifier
+from py3langid.langid import MODEL_FILE as LANGID_MODEL_FILE
 
 from type_infer.dtype import dtype
 
@@ -109,7 +109,7 @@ def get_language_dist(data):
     lang_dist = defaultdict(lambda: 0)
     lang_dist['Unknown'] = 0
     lang_probs_cache = dict()
-    identifier = LanguageIdentifier.from_modelstring(langid_model, norm_probs=True)
+    identifier = LanguageIdentifier.from_pickled_model(LANGID_MODEL_FILE, norm_probs=True)
     for text in data:
         text = str(text)
         text = text.translate(str.maketrans('', '', string.punctuation))