mirror of
https://github.com/nhammer514/textfiles-politics.git
synced 2024-10-01 01:15:38 -04:00
81 lines
2.3 KiB
Python
81 lines
2.3 KiB
Python
import spacy
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from collections import Counter
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import os
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# Uncomment this line if you need the language model.
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# If you already have it, comment it ou.
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# Let's try the different spaCy language models for this. We can compare _lg with _md or _sm
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workingDir = os.getcwd()
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CollPath = os.path.join(workingDir, '../regexConsp')
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insideDir = os.listdir(CollPath)
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print(insideDir)
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nlp = spacy.load("en_core_web_lg")
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def readTextFiles(filepath):
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with open(filepath, 'r', encoding='utf8') as f:
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readFile = f.read()
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# print(readFile)
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stringFile = str(readFile)
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# lengthFile = len(readFile)
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# print(lengthFile)
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tokens = nlp(stringFile)
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# print(tokens)
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listEntities = entitycollector(tokens)
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print(listEntities)
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# cardinal_freq = Counter(listCardinals)
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# topTen = cardinal_freq.most_common(10)
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# print(topTen)
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def entitycollector(tokens):
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entities = []
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for entity in tokens.ents:
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# if entity.label_ == "CARDINAL":
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print(entity.text, entity.label_, spacy.explain(entity.label_))
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entities.append(entity.text)
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return entities
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for file in os.listdir(CollPath):
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if file.endswith(".xml"):
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filepath = f"{CollPath}/{file}"
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print(filepath)
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readTextFiles(filepath)
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# print(listCardinals)
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# cardinal_freq = Counter(listCardinals)
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# topTen = cardinal_freq.most_common(10)
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# print(topTen)
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# grimm = open('grimm.txt', 'r', encoding='utf8')
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# grimmDoc = grimm.read()
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# grimmNLP = nlp(grimmDoc)
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# grimmmSentences = grimmNLP.sents
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# def sentenceLengths(sentences):
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# lengths = []
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# for s in sentences:
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# length = len(s.text)
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# lengths.append(length)
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# return sorted(lengths)
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# grimmLengths = sentenceLengths(grimmmSentences)
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# # print(grimmLengths)
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# maxVal = max(grimmLengths)
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# minVal = min(grimmLengths)
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# print('The shortest sentence is ' + str(minVal) + ' characters long.')
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# print('The longest sentence is ' + str(maxVal) + ' characters long.')
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# for sentence in grimmNLP.sents:
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# # print(sentence.text)
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# length = len(sentence.text)
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# if length == minVal:
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# print("The shortest sentence is: " + sentence.text)
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# if len(sentence.text) == maxVal:
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# print('The longest sentence is: ' + sentence.text + ' :' + str(maxVal) + 'characters')
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