How to write to a CSV using Python logging library?

Question

I'm trying to use the logging library in Python to write lists of strings to a CSV log file

Logger creation:

export_logger = logging.getLogger('exportLogger')
export_logger.setLevel(logging.INFO)
file_handler = logging.FileHandler('export_log.csv',mode='w')
export_logger.addHandler(file_handler)
export_logger.info(",".join(['status', 'view', 'filename', 'stdout', 'stderr', 'time']))

Logging:

column_list = [status, view, filename, out, err, current_time]
message = ",".join([str(item) for item in column_list])
export_logger.info(message)

My problem is that if any of the strings contain a new line character or comma, it breaks the output. I could surround them in quotes, but then it would break if they contain quotes. I can escape those, but I'd rather not rewrite code for parsing all the edge cases of CSV file writing. Is there a good way to handle this?

Is there a way to easily sanitize strings for writing to CSVs? I could do this: How do I write data into csv format as string (not file)? But that seems very roundabout and unreadable.

I'm only using the logging library because I thought that was best practice, but if it can't handle CSV formatting I may as well just open a module level CSV file and write lines to it using the python csv library, right?

Unless you have a very compelling reason to use logging for this, you should be using csv. — Patrick Haugh
– Patrick Haugh, Commented Oct 30, 2018 at 19:08
@CertainPerformance I thought I did have a solution but then realized I didn't and undeleted the question again haha. I thought the solution in my linked article worked because I modified it to keep arrays as arrays, but then found it wasn't even a deep copy at all. screencast.com/t/ZYoHERJt6v — pyjamas
– pyjamas, Commented Nov 13, 2018 at 3:22

Sam Mason · Accepted Answer · 2018-10-30 23:52:55Z

2

the logging library is mostly for adhoc runtime/diagnostic/debug output

intended/expected output (which it seems like you're after) should be handled more directly — in your case I'd suggest directly opening the output file, wrapping in a csv.writer and then calling writerow as needed

for example:

import csv

output = csv.writer(open('export_log.csv', 'w'))
output.writerow(['status', 'view', 'filename', 'stdout', 'stderr', 'time'])

for foo in bar:
   # do work
   output.writerow([status, view, filename, out, err, current_time])

note that File objects are also "Context Managers" and hence it might make sense to do:

with open('export_log.csv', 'w') as fd:
  output = csv.writer(fd)
  …

if you want to make sure the file gets closed appropriately

answered Oct 30, 2018 at 23:52

Sam Mason

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Ali Waqas · Accepted Answer · 2022-09-21 16:42:35Z

If you want a dedicated logger class for huge applications. You can create seperate objects to log multiple seperate files. I will suggest using pandas library since it is faster and bug-free.

import pandas as pd

class csvLogger:
    def __init__(self, filename):
        self.count = 1
        self.filename = filename

    def __call__(self, named_dict):
        df = pd.DataFrame(named_dict, index=[self.count])
        df.to_csv("./results/{}.csv".format(self.filename), mode='a', header=self.count == 1)

As you can see, the class will append new data to new row in csv file. You can take a hint from below code snippet.

mycsvLogger = csvLogger("file.csv")
data = {"x": 1, "y": 2}
mycsvLogger(data)

That should be a general code for many advance csv logging applications. Enjoy :)

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