How to sort .csv file test log which item first fail and paint color

[DeaD_EyE]

It's not so easy because you need to know how csv.reader works and you need to convert str into float for example.
Otherwise you can't do the comparison.

Here an example with:

• skipping first line before using csv.DictReader
  
• DictReader gets automatically the first list (after skipping, it's the second line) for the column names, which are later the keys
  
• reading two rows, where the first one should be the minimum limits and the second the maximum limits
  
• converting this str to a float and putting them as attribute on the instance of Reader
  
• iterate through the remaining data and using the methods reader.test_pass(row) and reader.in_valid_range(row)
  

Code:

import csv
from operator import itemgetter


class Reader:
    def __init__(self, csv_file, sort_fields):
        self.fd = open(csv_file, newline="")
        self.sort_fields = itemgetter(*sort_fields)
        # self.sort_fields(row) -> return a list
        # with the wanted data from the mapping

        # skipping first line
        next(self.fd)

        # DictReader reads automatically the first line
        # to get the column names
        self.csv = csv.DictReader(self.fd, delimiter=",")

        # getting minium and maximum values
        self.minimum_values = next(self.csv)
        self.maximum_values = next(self.csv)

        # getting the limit values from the dict and converting them to a float
        # that they could used for comparison
        self.vdd_continuity_min = float(self.minimum_values["VDD Continuity"])
        self.vdd_continuity_max = float(self.maximum_values["VDD Continuity"])
        self.lr_continuity_min = float(self.minimum_values["LR Continuity"])
        self.lr_continuity_max = float(self.maximum_values["LR Continuity"])

    @staticmethod
    def sort_by_float(row):
        # calling self.sort_fields with row -> data
        # map takes each element from data and call it with float()
        # tuple consumes the map
        # a tuple with floats is returned
        return tuple(map(float, self.sort_fields(row)))

    def __iter__(self):
        yield from self.csv

    def __enter__(self):
        return self

    def __exit__(self, exc_typ, exc_obj, exc_tb):
        # closes files automatically when leaving
        # the context manager
        self.fd.close()

    @staticmethod
    def test_pass(row):
        # no instance (self) is needed to do the test
        return row.get("Pass/Fail", "").lower() == "passed"

    def in_valid_range(self, row):
        # here self is needed, because attributes from this
        # instance are read
        vdd = float(row["VDD Continuity"])
        lr = float(row["LR Continuity"])
        return (self.vdd_continuity_min <= lr <= self.vdd_continuity_max) and (
            self.lr_continuity_min <= lr <= self.lr_continuity_max
        )


if __name__ == "__main__":
    with Reader("Log.csv", sort_fields=["VDD Continuity", "Temperature"]) as reader:
        # reader instance has now some attributes
        print(f"{reader.vdd_continuity_min=}")
        print(f"{reader.vdd_continuity_max=}")
        print(f"{reader.lr_continuity_min=}")
        print(f"{reader.lr_continuity_max=}")

        # calls implicity the __iter__ method of the instance of Reader
        for row in reader:
            if reader.test_pass(row) and reader.in_valid_range(row):
                part_id = row.get("Part ID")
                if part_id:
                    print(part_id)

The output could be made with: https://www.geeksforgeeks.org/working-wi...in-python/
But working directly with Excel will solve your task faster (currently). Later if you more experienced, this code is nothing difficult to write.

EDIT: Added the sorting. It's not possible to use this method, if the file is the half of your RAM.