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"""
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NS-PrivLogQC
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Created by:
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Emanuel Borges
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11.17.2025
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This program will assist with the process of performing QC on past and present NS privilege logs.
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"""
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import os, re
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from collections import namedtuple
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from MyCode.Tool_Box import FileEncodingLib
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import MyCode.Active_prgs.Redgrave.NS_MasterAttorneyList
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class QcPrivLog(object):
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"""A class for automating the process of performing QC on the NS privilege logs, including names normalization analysis"""
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version = '0.2.0'
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def __init__(self, cleanedDatExportFileName, metaFromFieldName, plogFromFieldName, metaToFieldName, plogToFieldName, metaCcFieldName, plogCcFieldName, metaBccFieldName, plogBccFieldName, metaAuthorFieldName, plogAuthorFieldName, fileEncoding = 'UTF8'):
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"""Initializes the data structures. cleanedDatExportFileName should be the full path to the file. Assumes the first row of the data file is the header and first column is DocID."""
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print("Initializing data structures...")
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self.issuesMatrix = {}
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self.metadataValuesDict = {}
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self.formattedValuesDict = {}
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self.additionalValuesDict = {}
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self.allPossibleEmailAddressesRegExPattern = r"[\w.+-]+@[\w-]+\.[\w.-]+"
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contents = open(cleanedDatExportFileName,encoding = fileEncoding).readlines()
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self.cleanedInputDataFileHeader = contents[0].replace("\n","")
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self.cleanedInputDataFileHeaderList = self.cleanedInputDataFileHeader.split("|")
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self.cleanedInputDataFileHeaderPositionalMatrix = {v: i for i, v in enumerate(self.cleanedInputDataFileHeaderList)}
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contents = contents[1:]
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print (f"There are {len(contents)} rows of data in this input file.\n\n")
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print (f"The data structure will be made of following field pairs:")
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print(f"{metaFromFieldName} | {plogFromFieldName}")
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print(f"{metaToFieldName} | {plogToFieldName}")
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print(f"{metaCcFieldName} | {plogCcFieldName}")
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print(f"{metaBccFieldName} | {plogBccFieldName}")
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print(f"{metaAuthorFieldName} | {plogAuthorFieldName}\n\n")
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RecordValues = namedtuple("RecordValues","fromValues toValues ccValues bccValues docAuthor")
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self.recordValuesFieldList = RecordValues._fields
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for line in contents:
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line = line.replace("\n","")
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line = line.split("|")
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docID = line[0]
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self.metadataValuesDict[docID] = RecordValues(self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[metaFromFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[metaToFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[metaCcFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[metaBccFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[metaAuthorFieldName]]))
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self.formattedValuesDict[docID] = RecordValues(self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[plogFromFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[plogToFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[plogCcFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[plogBccFieldName]]),
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self.__SplitAndClean(line[self.cleanedInputDataFileHeaderPositionalMatrix[plogAuthorFieldName]]))
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#print(self.formattedValuesDict[docID])
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print("Data structures created.")
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def __SplitAndClean(self, rawVal, delim = ";"):
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"""Pseudo-private method which will take a raw string and split this into a list, removing any leading or trailing whitespace"""
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if rawVal:
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newVal = [x.strip() for x in rawVal.split(delim)]
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else: newVal = ""
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return newVal
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def __FieldDedupeByEmailAddress(self, valuesList):
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"""Pseudo-private method which will attempt to deduplicate a list of values from a specific field by pulling out email addresses as the deduplication criteria. Returns deduplicated count."""
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## This should ONLY be used for deduplication for counting and not for true deduplication because it removes a duplicate value at random and sometimes this will be the value with more information.
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## TODO: update this to be case insensitive.
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tempEmailList = []
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newList = []
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for item in valuesList:
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result = re.findall(self.allPossibleEmailAddressesRegExPattern, item)
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if result:
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for r in result:
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if r.upper() in tempEmailList:
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pass
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else:
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newList.append(item)
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tempEmailList.append(r.upper())
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else:
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newList.append(item)
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return len(newList)
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def __FieldFullValueDedupe(self, valuesList):
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"""Pseudo-private method which will attempt to deduplicate a list of values from a specific field using the FULL VALUE. This was created because there appears to be duplicate values in the formatted fields"""
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## Going to do this the long way because of possible uppercase-lowercase issues. These should all be uppercase but there shouldnt have been dups either...
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newSet = set()
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for item in valuesList:
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newSet.add(item.upper())
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return len(newSet)
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def __AddToIssuesMatrix(self,docID,issueMessage):
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"""This method will add a single issue to the issues matrix."""
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if docID in list(self.issuesMatrix.keys()):
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self.issuesMatrix[docID].append(issueMessage)
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else:
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self.issuesMatrix[docID] = [issueMessage,]
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def PerformValueCountChecks(self, countsOnly = True):
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"""Performs the inital value count checks between the metadata values and formatted values, looking for red flags and warnings. By default reports numbers. Set countsOnly to false to export reports."""
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workList = self.metadataValuesDict.keys()
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#misCount = 0
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#redFlagDocList = []
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#warningDocList = []
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#misList = []
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redFlagDocSet = set()
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redFlagDocMatrix = {}
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warningDocSet = set()
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warningDocMatrix = {}
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#duplicatesInFormattedSet = set()
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duplicatesInFormattedMatrix = {}
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for docID in workList:
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for fieldName in self.recordValuesFieldList:
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metadataFieldValues = self.metadataValuesDict[docID]._asdict()[fieldName]
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formattedFieldValues = self.formattedValuesDict[docID]._asdict()[fieldName]
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if len(metadataFieldValues) - len(formattedFieldValues) == 0:
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pass
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else:
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if len(metadataFieldValues) == 0:
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## Have to account for instances where the meta docAuthor is blank because it's an email and the formatted just has the from value in it.
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if fieldName == 'docAuthor':
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if self.metadataValuesDict[docID].fromValues:
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pass
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else:
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redFlagDocSet.add(docID)
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#print(docID)
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try:
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redFlagDocMatrix[docID].append(fieldName+"-No_Metadata_Entries-A")
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except KeyError:
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redFlagDocMatrix[docID] = [fieldName+"-No_Metadata_Entries-A",]
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else:
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redFlagDocSet.add(docID)
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try:
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redFlagDocMatrix[docID].append(fieldName+"-No_Metadata_Entries-B")
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except KeyError:
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redFlagDocMatrix[docID] = [fieldName+"-No_Metadata_Entries-B",]
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elif len(formattedFieldValues) == 0:
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redFlagDocSet.add(docID)
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try:
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redFlagDocMatrix[docID].append(fieldName+"-No_Formatted_Entries")
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except KeyError:
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redFlagDocMatrix[docID] = [fieldName+"-No_Formatted_Entries",]
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else:
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## try the count again by deduplicating the metadata field values. Never on the formatted field values.
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deduplicatedFieldCount = self.__FieldDedupeByEmailAddress(metadataFieldValues)
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if deduplicatedFieldCount - len(formattedFieldValues) == 0:
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pass
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else:
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distanceBetween = abs(deduplicatedFieldCount - len(formattedFieldValues))
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if deduplicatedFieldCount > 30:
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if distanceBetween > (10 * deduplicatedFieldCount)/100:
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#print(docID,fieldName)
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redFlagDocSet.add(docID)
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try:
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redFlagDocMatrix[docID].append(fieldName)
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except KeyError:
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redFlagDocMatrix[docID] = [fieldName,]
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else:
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warningDocSet.add(docID)
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try:
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warningDocMatrix[docID].append(fieldName)
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except KeyError:
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warningDocMatrix[docID]= [fieldName,]
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else:
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if distanceBetween > 2:
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#print(docID,fieldName)
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redFlagDocSet.add(docID)
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try:
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redFlagDocMatrix[docID].append(fieldName)
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except KeyError:
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redFlagDocMatrix[docID] = [fieldName,]
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else:
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warningDocSet.add(docID)
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try:
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warningDocMatrix[docID].append(fieldName)
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except KeyError:
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warningDocMatrix[docID]= [fieldName,]
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## Perform a separate check for duplicates in the formatted field.
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if len(formattedFieldValues) == self.__FieldFullValueDedupe(formattedFieldValues):
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pass
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else:
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try:
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duplicatesInFormattedMatrix[docID].append(fieldName)
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except KeyError:
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duplicatesInFormattedMatrix[docID] = [fieldName,]
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print(f"There are a total of {len(redFlagDocSet)} red flag documents and {len(warningDocSet)} warnings where the matching field value counts that do not match.")
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if countsOnly == False:
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warningsOutputFile = open(r"C:\Test_Dir\NS\warnings.txt",'w')
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redFladsOutputFile = open(r"C:\Test_Dir\NS\redFlags.txt",'w')
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duplicatesInFormattedOutputFile = open(r"C:\Test_Dir\NS\dupesInFormattedFields.txt",'w')
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for x in warningDocMatrix:
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warningsOutputFile.write(f"{x} | {*warningDocMatrix[x],}\n")
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warningsOutputFile.close()
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for y in redFlagDocMatrix:
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redFladsOutputFile.write(f"{y} | {*redFlagDocMatrix[y],}\n")
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redFladsOutputFile.close()
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for z in duplicatesInFormattedMatrix:
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duplicatesInFormattedOutputFile.write(f"{z} | {*duplicatesInFormattedMatrix[z],}\n")
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duplicatesInFormattedOutputFile.close()
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def PerformNamesToMalChecks(self):
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"""This method will compare the normalized names to the MAL, using the metadata values."""
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masterAttorneyListFileName = r"C:\Users\eborges\OneDrive - Redgrave LLP\Documents\Cases\Norfolk Southern\_NS_Current_MAL\RG - NS Cross-Matter Master Attorney List 20260120 (20260120-0136).xlsx"
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nsMal = MyCode.Active_prgs.Redgrave.NS_MasterAttorneyList.NS_MasterAttorneyList(masterAttorneyListFileName)
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workList = self.metadataValuesDict.keys()
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matches = []
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used_full_names = set()
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remaining_emails = []
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for docID in workList:
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for fieldName in self.recordValuesFieldList:
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matches = []
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used_full_names = set()
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remaining_emails = []
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#print(docID)
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#print(fieldName)
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metadataFieldValues = self.metadataValuesDict[docID]._asdict()[fieldName]
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#print(metadataFieldValues)
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formattedFieldValues = self.formattedValuesDict[docID]._asdict()[fieldName]
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#print(formattedFieldValues)
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normalized_full_names = {name.upper().replace("^","").strip(): name for name in formattedFieldValues}
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#print(normalized_full_names)
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#formattedFieldValues = [x.upper().replace("^","").strip() for x in formattedFieldValues]
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if metadataFieldValues:
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for metadataFieldValue in metadataFieldValues:
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result = re.findall(self.allPossibleEmailAddressesRegExPattern, metadataFieldValue)
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if result:
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for email in result:
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person = nsMal.malPeopleList.search_by_email(email.upper().strip())
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if not person:
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#remaining_emails.append(email)
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##self.__AddToIssuesMatrix(docID,f"There is no MAL match for email address {email}.")
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continue
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## With this single email address, generate all possible names
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possible_names = [name.upper() for name in nsMal.malPeopleList.return_person_all_name_variations(person)]
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#print(possible_names)
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attorneyStatus = person.is_attorney
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## Attempt to find a full name match.
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found_match = None
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for candidate in possible_names:
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#print(candidate)
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if candidate in normalized_full_names:
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full_name = normalized_full_names[candidate]
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if full_name not in used_full_names:
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#matches.append((email, full_name))
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## TO DO: Change these next 2 lines as soon as you support SPLIT ROLE
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if attorneyStatus == "SPLIT ROLE":
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attorneyStatus = "YES"
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if attorneyStatus == "YES" and "^" in full_name:
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pass
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elif attorneyStatus == "NO" and "^" not in full_name:
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pass
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elif attorneyStatus == "NO":
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self.__AddToIssuesMatrix(docID,f"{full_name} has an ^ but is a high confidence non-attorney match.")
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else:
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self.__AddToIssuesMatrix(docID,f"{full_name} does not have an ^ but is a high confidence attorney match.")
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used_full_names.add(full_name)
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found_match = full_name
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break
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if not found_match:
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#remaining_emails.append(email)
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if attorneyStatus == "YES":
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self.__AddToIssuesMatrix(docID,f"{email} from {fieldName} does not have a corresponding normalized name match but is a high confidence attorney match.")
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else:
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pass
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#self.__AddToIssuesMatrix(docID,f"{email} from {fieldName} does not have a corresponding normalized name match but is a high confidence non-attorney match.")
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elif "EXCHANGE" in metadataFieldValue.upper():
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## The metadata field parsed value didnt have an email address. Try a username lookup.
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userNameId = metadataFieldValue.split("-")[-1]
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## Finding that there is garbage in the userIDs... cleaning that.
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userNameId = userNameId.replace("]","")
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userNameId = userNameId.replace('">','')
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userNameId = userNameId.replace('"','')
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if userNameId:
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userNameId = userNameId.upper()
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person = nsMal.malPeopleList.search_by_login_id(userNameId.upper().strip())
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if not person:
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#remaining_emails.append(email)
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##self.__AddToIssuesMatrix(docID,f"There is no MAL match for User Name Id {userNameId}.")
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continue
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## With this user login id, generate all possible names
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possible_names = [name.upper() for name in nsMal.malPeopleList.return_person_all_name_variations(person)]
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attorneyStatus = person.is_attorney
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## Attempt to find a full name match.
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found_match = None
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for candidate in possible_names:
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if candidate in normalized_full_names:
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full_name = normalized_full_names[candidate]
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if full_name not in used_full_names:
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#matches.append((email, full_name))
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## TO DO: Change these next 2 lines as soon as you support SPLIT ROLE
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if attorneyStatus == "SPLIT ROLE":
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attorneyStatus = "YES"
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if attorneyStatus == "YES" and "^" in full_name:
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pass
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elif attorneyStatus == "NO" and "^" not in full_name:
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pass
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elif attorneyStatus == "NO":
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self.__AddToIssuesMatrix(docID,f"{full_name} has an ^ but is a high confidence non-attorney match.")
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else:
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self.__AddToIssuesMatrix(docID,f"{full_name} does not have an ^ but is a high confidence attorney match.")
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used_full_names.add(full_name)
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found_match = full_name
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break
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if not found_match:
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#remaining_emails.append(email)
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if attorneyStatus == "YES":
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self.__AddToIssuesMatrix(docID,f"User Login ID {userNameId} from {fieldName} does not have a corresponding normalized name match but is a high confidence attorney match.")
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else:
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pass
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| 339 |
## Compute remaining full names
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| 340 |
remaining_full_names = [name for name in formattedFieldValues if name not in used_full_names]
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for y in remaining_full_names:
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pass
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#self.__AddToIssuesMatrix(docID,f"{y} from {fieldName} normalized field has no matching metadata value.")
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return self.issuesMatrix
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#return matches, remaining_emails, remaining_full_names
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| 346 |
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| 348 |
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| 349 |
if __name__ == '__main__':
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cleanedDatExportFileName = r"C:\Test_Dir\NS\PrivLogTest\20260210\Search 1\export_20260211_182928_Converted.txt"
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qcP = QcPrivLog(cleanedDatExportFileName, "From", "PLOG_Norm_From", "To", "PLOG_Norm_To",
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"CC", "PLOG_Norm_CC", "BCC", "PLOG_Norm_BCC", "Author", "PLOG_Norm_Author", fileEncoding = 'utf-8')
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print(qcP.cleanedInputDataFileHeaderPositionalMatrix)
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qcP.PerformValueCountChecks(countsOnly = False)
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masterAttorneyListFileName = r"C:\Users\eborges\OneDrive - Redgrave LLP\Documents\Cases\Norfolk Southern\_NS_Current_MAL\RG - NS Cross-Matter Master Attorney List 20260120 (20260120-0136).xlsx"
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nsMal = MyCode.Active_prgs.Redgrave.NS_MasterAttorneyList.NS_MasterAttorneyList(masterAttorneyListFileName)
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issuesMatrix = qcP.PerformNamesToMalChecks()
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outputFile = open(r"C:\Test_Dir\NS\namesNormTestOutput.txt",'w',encoding='utf-8')
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| 360 |
for docID in list(issuesMatrix.keys()):
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| 361 |
outputFile.write(f"{docID}|{';'.join(issuesMatrix[docID])}\n")
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| 362 |
outputFile.close()
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|
