mirror of
https://github.com/nhammer514/textfiles-politics.git
synced 2024-12-24 14:59:38 -05:00
108 lines
4.6 KiB
Python
108 lines
4.6 KiB
Python
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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from saxonche import PySaxonProcessor
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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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# 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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# creates a new file that includes all of the found entities.
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with open('output.txt', 'w') as f:
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entities = {}
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# goes through each entity in the token list.
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for ent in sorted(tokens.ents):
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entityInfo = [ent.text, ent.label_, spacy.explain(ent.label_)]
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stringify = str(entityInfo)
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f.write(stringify)
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f.write('\n')
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entities[ent.text] = ent.label_
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# return all entities with its label and text.
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return entities
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# Function runs regex through given file.
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def regexFile(file):
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fileDir = os.path.join(outputPath, file)
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with PySaxonProcessor(license=False) as proc:
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# grabs the original xml file and stores it in a variable for later. this some xquery bs
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xml = open(fileDir, encoding='utf-8').read()
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xp = proc.new_xpath_processor()
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node = proc.parse_xml(xml_text=xml)
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xp.set_context(xdm_item=node)
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# xquery goes through original text, and stores it all in a single string.
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xpath = xp.evaluate('//p ! normalize-space() => string-join()')
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string = xpath.__str__()
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# regex goes through the text and deletes anything that is not a letter or space.
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cleanedText = regex.sub('[^A-z]+', ' ', string)
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# gets the tokens of the clean text.
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tokens = nlp(cleanedText)
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wrappedText = xml
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# grabs all the entities in file and stores it in a list/array.
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listEntities = entitycollector(tokens)
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# if anything exists in the list, the following code will run.
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if listEntities:
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# it will check through each entity in the list and see its entity type. it is looking for "PERSON" tokens
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# in this instance, which includes of nouns and names.
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for entity in listEntities.keys():
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if listEntities[entity] == "PERSON":
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# key_template variable is the elements we wrap around found instances.
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key_template = "<ent type = 'person'>" + entity + "</ent>"
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# loops through wrappedText until all entities are wrapped.
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wrappedText = wrappedText.replace(entity, key_template)
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# Saves newly wrapped elements and then writes it into new file.
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with open(fileDir, 'w', encoding='utf8') as f:
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f.write(wrappedText)
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print("WRAPPING " + entity)
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# This part of the code does not run. It is a WIP.
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## It tries to find weird or invalid elements/tags and fix them.
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def checkTags(file):
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content = []
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fileDir = os.path.join(outputPath, file)
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with open(fileDir, 'r', encoding='utf8') as inFile:
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for line in inFile:
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content.append(line)
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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(fileDir, 'w', encoding='utf8') as f:
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for line in content:
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match1 = regex.search("(<ent type = 'person'>){2,}(.+?)</ent>", line)
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if match:
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print("broken line found, fixing...")
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newLine = regex.sub("(<ent type = 'person'>){2,}(.+?)</ent>",r"\1 \2",line)
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print(line + "\n INTO.")
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print(newLine)
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for file in insideDir:
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copyTextFiles(file)
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regexFile(file)
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#checkTags(file)
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print("File checking finished.") |