created main.py with code

This commit is contained in:
Nate Hammer 2023-03-27 17:14:07 -04:00
parent 3dfe20153d
commit d18a6f5b16
2 changed files with 86 additions and 8 deletions

80
pythonCode/main.py Normal file
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import spacy
from collections import Counter
import os
# Uncomment this line if you need the language model.
# If you already have it, comment it ou.
# Let's try the different spaCy language models for this. We can compare _lg with _md or _sm
workingDir = os.getcwd()
CollPath = os.path.join(workingDir, '../regexConsp')
insideDir = os.listdir(CollPath)
print(insideDir)
nlp = spacy.load("en_core_web_lg")
def readTextFiles(filepath):
with open(filepath, 'r', encoding='utf8') as f:
readFile = f.read()
# print(readFile)
stringFile = str(readFile)
# lengthFile = len(readFile)
# print(lengthFile)
tokens = nlp(stringFile)
# print(tokens)
listEntities = entitycollector(tokens)
print(listEntities)
# cardinal_freq = Counter(listCardinals)
# topTen = cardinal_freq.most_common(10)
# print(topTen)
def entitycollector(tokens):
entities = []
for entity in tokens.ents:
# if entity.label_ == "CARDINAL":
print(entity.text, entity.label_, spacy.explain(entity.label_))
entities.append(entity.text)
return entities
for file in os.listdir(CollPath):
if file.endswith(".xml"):
filepath = f"{CollPath}/{file}"
print(filepath)
readTextFiles(filepath)
# print(listCardinals)
# cardinal_freq = Counter(listCardinals)
# topTen = cardinal_freq.most_common(10)
# print(topTen)
# grimm = open('grimm.txt', 'r', encoding='utf8')
# grimmDoc = grimm.read()
# grimmNLP = nlp(grimmDoc)
# grimmmSentences = grimmNLP.sents
# def sentenceLengths(sentences):
# lengths = []
# for s in sentences:
# length = len(s.text)
# lengths.append(length)
# return sorted(lengths)
# grimmLengths = sentenceLengths(grimmmSentences)
# # print(grimmLengths)
# maxVal = max(grimmLengths)
# minVal = min(grimmLengths)
# print('The shortest sentence is ' + str(minVal) + ' characters long.')
# print('The longest sentence is ' + str(maxVal) + ' characters long.')
# for sentence in grimmNLP.sents:
# # print(sentence.text)
# length = len(sentence.text)
# if length == minVal:
# print("The shortest sentence is: " + sentence.text)
# if len(sentence.text) == maxVal:
# print('The longest sentence is: ' + sentence.text + ' :' + str(maxVal) + 'characters')

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home = C:\Users\Nathan\AppData\Local\Programs\Python\Python311 import os
implementation = CPython
version_info = 3.11.1.final.0 workingDir = os.getcwd()
virtualenv = 20.16.7 CollPath = os.path.join(workingDir, '../regexConsp')
include-system-site-packages = false insideDir = os.listdir(CollPath)
base-prefix = C:\Users\Nathan\AppData\Local\Programs\Python\Python311 print(insideDir)
base-exec-prefix = C:\Users\Nathan\AppData\Local\Programs\Python\Python311
base-executable = C:\Users\Nathan\AppData\Local\Programs\Python\Python311\python.exe