Use good gitignore

.gitignore

@@ -1,3 +1,138 @@
-__pycache__
-*.swp
-venv
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/

MANIFEST

@@ -1,5 +0,0 @@
-# file GENERATED by distutils, do NOT edit
-README
-setup.py
-gptc/__init__.py
-gptc/__main__.py

build/lib/gptc/__init__.py

@@ -1,76 +0,0 @@
-#!/usr/bin/env python3
-import sys
-import spacy
-
-nlp = spacy.load('en_core_web_sm')
-
-def listify(text):
-    return [string.lemma_.lower() for string in nlp(text) if string.lemma_[0] in 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ']
-
-
-def compile(raw_model):
-    model = {}
-
-    for portion in raw_model:
-        text = listify(portion['text'])
-        category = portion['category']
-        for word in text:
-            try:
-                model[category].append(word)
-            except:
-                model[category] = [word]
-            model[category].sort()
-    all_models = [ { 'text': model, 'stopword': i/10} for i in range(0, 21) ]
-    for test_model in all_models:
-        correct = 0
-        classifier = Classifier(test_model)
-        for text in raw_model:
-            if classifier.check(text['text']) == text['category']:
-                correct += 1
-        test_model['correct'] = correct
-        print('tested a model')
-    best = all_models[0]
-    for test_model in all_models:
-        if test_model['correct'] > best['correct']:
-            best = test_model
-    del best['correct']
-    return best
-    return {'text': model}
-
-
-class Classifier:
-    def __init__(self, model, supress_uncompiled_model_warning=False):
-        if type(model['text']) == dict:
-            self.model = model
-        else:
-            self.model = compile(model)
-            if not supress_uncompiled_model_warning:
-                print('WARNING: model was not compiled', file=sys.stderr)
-                print('In development, this is OK, but precompiling the model is preferred for production use.', file=sys.stderr)
-        self.warn = supress_uncompiled_model_warning
-
-    def check(self, text):
-        model = self.model
-        stopword_value = 0.5
-        try:
-            stopword_value = model['stopword']
-        except:
-            pass
-        stopwords = spacy.lang.en.stop_words.STOP_WORDS
-        model = model['text']
-        text = listify(text)
-        probs = {}
-        for word in text:
-            for category in model.keys():
-                for catword in model[category]:
-                    if word == catword:
-                        weight = ( stopword_value if word in stopwords else 1 ) / len(model[category])
-                        try:
-                            probs[category] += weight 
-                        except:
-                            probs[category] = weight
-        most_likely = ['unknown', 0]
-        for category in probs.keys():
-            if probs[category] > most_likely[1]:
-                most_likely = [category, probs[category]]
-        return most_likely[0]

build/lib/gptc/__main__.py

@@ -1,24 +0,0 @@
-#!/usr/bin/env python3
-import argparse
-import json
-
-parser = argparse.ArgumentParser(description="General Purpose Text Classifier")
-parser.add_argument('model', help='model to use')
-parser.add_argument('-c', '--compile', help='compile raw model model to outfile', metavar='outfile')
-args = parser.parse_args()
-
-import gptc # PEP 8 violation, but don't fix it
-# Way better for performance of argparse checking
-
-with open(args.model, 'r') as f:
-    raw_model = json.load(f)
-if args.compile:
-    with open(args.compile, 'w+') as f:
-        json.dump(gptc.compile(raw_model), f)
-else:
-    classifier = gptc.Classifier(raw_model)
-    if sys.stdin.isatty():
-        text = input('Text to analyse: ')
-    else:
-        text = sys.stdin.read()
-    print(classifier.check(text))