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main.py outputs new files and wraps elements around tokens
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335 changed files with 242619 additions and 29 deletions
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@ -2,44 +2,64 @@ import spacy
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from collections import Counter
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import re as regex
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import os
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# nlp = spacy.cli.download("en_core_web_lg")
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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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#### Loads all of the necessary variables and functions.
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nlp = spacy.load("en_core_web_lg")
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workingDir = os.getcwd()
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CollPath = os.path.join(workingDir, '../regexConsp')
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outputPath = os.path.join(workingDir, 'output/')
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# Everything in original conspiracy directory.
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insideDir = os.listdir(CollPath)
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print(insideDir)
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if os.path.isfile("outputNames.txt"):
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open("outputNames.txt", 'w').close();
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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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stringFile = str(readFile)
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# Using REGEX to delete all element tags.
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elementsRemoved = regex.sub('<.+?>', '', stringFile)
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# Using REGEX to delete all \n.
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cleanedFile = regex.sub('\n', ' ', elementsRemoved)
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tokens = nlp(cleanedFile)
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listEntities = entitycollector(tokens)
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# Copies files in case they do not exist
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def copyTextFiles(file):
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content = []
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# Reads the contents of file, and saves each line of file into the content array.
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with open(CollPath + "/" + file, 'r', encoding='utf8') as inFile:
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for line in inFile:
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content.append(line)
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print("copying " + file)
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inFile.close()
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# With the contents copied, a loop will go through the array and write it all in a new file in output folder.
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with open(outputPath + "/" + file, 'w', encoding='utf8') as f:
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for line in content:
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f.write(str(line))
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# Function runs through the tokens of given file. Entities are stored in array, then returned. Called by regexFile().
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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_ == "PERSON":
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with open("outputNames.txt", 'a') as f:
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f.write("\n" + entity.text)
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print("Writing in outputNames.txt: " + entity.text)
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## Below includes entity values and stuf
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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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# Function runs regex through given file.
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def regexFile(file):
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# First, it reads file given. Supposedly, the newly created file in output folder.
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with open(outputPath + "/" + file, 'r', encoding='utf8') as inFile:
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rawText = str(inFile.read())
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# Regex finds all elements in a file and deletes them. Then Regex finds anything that is not a letter, and
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# deletes. It is stored in a variable that is supposedly clean from anything extra.
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cleanedText = regex.sub('[^A-z]+', ' ', regex.sub('<.+?>', ' ', rawText))
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# token stuff
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tokens = nlp(cleanedText)
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listEntities = entitycollector(tokens)
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# If the listEntity array has content in it, it will go through the list to see if the content is located
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# anywhere in the original, raw text.
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if listEntities:
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for entity in listEntities:
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wrappedText = regex.sub(str(entity), '<person>' + entity + '</person>',rawText)
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# Saves newly wrapped elements and then writes it into the copied file.
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with open(outputPath + "/" + file, 'w', encoding='utf8') as f:
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f.write(wrappedText)
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print("WRAPPING " + entity)
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f.close()
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else:
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print("No names... Probably did not detect any?")
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# Goes through all of the original conspiracy texts
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for file in insideDir:
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copyTextFiles(file)
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regexFile(file)
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