matrices.py

import pandas as pd
import ERFormatConstants as const


"""_summary_
Parses csv table and returns a dataframe
This is quite finicky as lucidchart has a very weird way of structuring tables as it is based on when different cells were created
This is quite a big EDGE case and will only work for the specific table shape that I have created
"""
def parseTable(df, metricsDict):
    
    cols = [const.Er_ID, const.Bowtie_ID, const.Metric_ID, const.Metric_Name, const.Value, const.Measure_date, const.Frequency ,const.Measurement_guide]
        
    table = df.loc[df[const.Name]=='Metric matrix']    # Defines the table
    
    matrics = pd.DataFrame(columns=cols)

    print(len(table))

    # ! Parsing the first row of the table which has a fucked structure because lucidchart is garbage : ) 
    erID1 = table[const.textArea4].item()              # Define the ER ID
    BowTieID1 = table[const.textArea5].item()          # Define the Bowtie ID
    MetricID1 = table[const.textArea6].item()          # Define the Metric ID
    MetricName1 = table[const.textArea15].item()        # Define the Metric Name
    Value1 = table[const.textArea16].item()            # Define the Value
    MeasureDate1 = table[const.textArea17].item()      # Define the Measure Date
    Frequency1 = table[const.textArea18].item()        # Define the Frequency
    Guide1 = table[const.textArea19].item()            # Define the Measurement guide
    
    
    matrics.loc[0] = erID1, BowTieID1, MetricID1, MetricName1, Value1, MeasureDate1, Frequency1, Guide1 # Fill inn dataframe
    
    # TODO Error handle/Communicate to end user here, "You seem to have a metric in your table which is not used etc"
    metricsdict = fillMetricinfo(erID1, BowTieID1, MetricID1, MetricName1, Value1, MeasureDate1, Frequency1, Guide1, metricsDict)    
    
    
    # Parsing the second row, this row is also specialized    
    erID2 = table[const.textArea7].item()              # Define the ER ID
    BowTieID2 = table[const.textArea8].item()          # Define the Bowtie ID
    MetricID2 = table[const.textArea9].item()          # Define the Metric ID
    MetricName2 = table[const.textArea20].item()        # Define the Metric Name
    Value2 = table[const.textArea21].item()            # Define the Value
    MeasureDate2 = table[const.textArea22].item()      # Define the Measure Date
    Frequency2 = table[const.textArea23].item()        # Define the Frequency
    Guide2 = table[const.textArea24].item()            # Define the Measurement guide    
    
    matrics.loc[1] = erID2, BowTieID2, MetricID2, MetricName2, Value2, MeasureDate2, Frequency2, Guide2
    
    metric = metricsDict[MetricID2]  # Access the appropriate metric in the dictionary 
    
    # TODO Error handle/Communicate to end user here, "You seem to have a metric in your table which is not used etc"
    if metric == None: 
        handleMissingMetric()
    
    
        
    matricsIndex = 2

    # Parsing from the third row and onwards is standard format
    for i in range(25, len(table.columns), 8):
        if pd.isnull(table["Text Area "+str(i)].item()) == True or pd.isnull(table["Text Area "+str(i+1)].item()) == True:
            break
        
        erID = table["Text Area "+str(i)].item()              # Define the ER ID
        BowTieID = table["Text Area "+str(i+1)].item()          # Define the Bowtie ID
        MetricID = table["Text Area "+str(i+2)].item()          # Define the Metric ID
        MetricName = table["Text Area "+str(i+3)].item()        # Define the Metric Name
        Value = table["Text Area "+str(i+4)].item()             # Define the Value
        MeasureDate = table["Text Area "+str(i+5)].item()       # Define the Measure Date
        Frequency = table["Text Area "+str(i+6)].item()         # Define the Frequency
        Guide = table["Text Area "+str(i+7)].item()            # Define the Measurement guide
        
        series = pd.Series([erID, BowTieID, MetricID, MetricName, Value, MeasureDate, Frequency, Guide])
        
        matrics.loc[matricsIndex] = erID, BowTieID, MetricID, MetricName, Value, MeasureDate, Frequency, Guide
        matricsIndex += 1    
    
    return matrics

def handleMissingMetric():
    """Function will communicate to end user that a metric is in the matrics but is not used in the diagram 
    This will provide clarity to the end user and inform them of unlinked metrics
    """
    pass

def fillMetricinfo(erID1: str, 
                   BowTieID1: str, 
                   MetricID1: str, 
                   MetricName1: str, 
                   Value1: str, 
                   MeasureDate1: str, 
                   Frequency1: str, 
                   Guide1: str, metricsDict: dict)-> dict:
    """Function will fill in the metric information in the dataframe into the metric object and return the updated dictionary
    """
    metric = metricsDict[MetricID1]  # Access the appropriate metric in the dictionary
    
    if metric == None: 
        print("Metric is not used in the diagram!!!")
        return
    
    # Updates the metric with the information found in the dynamics matrix
    metric.erID = erID1                 # Should be string
    metric.bowtieID = BowTieID1         # is list and should be i guess
    metric.name = MetricName1           # Should be string
    metric.value = Value1               # Should be string
    metric.date = MeasureDate1          # TODO Parse this and change it to a date object maybe? Not sure if its necessary...
    metric.frequency = Frequency1       # Should be string
    metric.guide = Guide1               # Should be string
    
    metricsDict[MetricID1] = metric
    
    return metricsDict