Simple class to log to csv using the logging rotating handler, output is a rolling csv log
Project description
csv-logger
Simple class to log to csv using the logging rotating handler, output is a rolling csv log
Description
This library allows you to easily log information to CSV file format, in the same fashion as the logging package. This allows you to generate a rolling set of csv logs with a maximum file size and file count.
Inputs:
- filename
- main log file name or path. if path, will create subfolders as needed
- delimiter
- delimiter to use in the files. Defaults to
','
- delimiter to use in the files. Defaults to
- level
- logging level for logs, below which the logs will not be written to file. default
INFO
- logging level for logs, below which the logs will not be written to file. default
- add_level_names
- list fo strings, adds additional logging levels for custom log tagging. default:
[]
- list fo strings, adds additional logging levels for custom log tagging. default:
- add_level_nums
- assigns specific nums to
add_level_names
. default if None provided:[100,99,98,..]
- assigns specific nums to
- fmt
- output format. default
f'%(asctime)s,%(message)s'
. accepts:%(name)s
Name of the logger (logging channel)%(levelno)s
Numeric logging level for the message (DEBUG, INFO, WARNING, ERROR, CRITICAL)%(levelname)s
Text logging level for the message ("DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL")%(pathname)s
Full pathname of the source file where the logging call was issued (if available)%(filename)s
Filename portion of pathname%(module)s
Module (name portion of filename)%(lineno)d
Source line number where the logging call was issued (if available)%(funcName)s
Function name%(created)f
Time when the LogRecord was created (time.time() return value)%(asctime)s
Textual time when the LogRecord was created%(msecs)d
Millisecond portion of the creation time%(relativeCreated)d
Time in milliseconds when the LogRecord was created, relative to the time the logging module was loaded (typically at application startup time)%(thread)d
Thread ID (if available)%(threadName)s
Thread name (if available)%(process)d
Process ID (if available)%(message)s
The result of record.getMessage(), computed just as the record is emitted
- output format. default
- datefmt
- date format for first column of logs. default
%Y/%m/%d %H:%M:%S
- date format for first column of logs. default
- max_size
- max size of each log file in bytes. default
10MB
(10,485,760)
- max size of each log file in bytes. default
- max_files
- max file count. default
10
- max file count. default
- header
- header to prepend to csv files. default
None
- header to prepend to csv files. default
Getting started
Install with pip3 install csv_logger
Basic usage example below.
Since the example is set to only 1kB of data per file, the code results in 2 log files. log.csv
will always contain the most recent data, and the subsequent files (log_1.csv
and so on) will have older data.
#!/usr/bin/python3
from csv_logger import CsvLogger
import logging
from time import sleep
filename = 'logs/log.csv'
delimiter = ','
level = logging.INFO
custom_additional_levels = ['logs_a', 'logs_b', 'logs_c']
fmt = f'%(asctime)s{delimiter}%(levelname)s{delimiter}%(message)s'
datefmt = '%Y/%m/%d %H:%M:%S'
max_size = 1024 # 1 kilobyte
max_files = 4 # 4 rotating files
header = ['date', 'level', 'value_1', 'value_2']
# Creat logger with csv rotating handler
csvlogger = CsvLogger(filename=filename,
delimiter=delimiter,
level=level,
add_level_names=custom_additional_levels,
add_level_nums=None,
fmt=fmt,
datefmt=datefmt,
max_size=max_size,
max_files=max_files,
header=header)
# Log some records
for i in range(10):
csvlogger.logs_a([i, i * 2])
sleep(0.1)
# You can log list or string
csvlogger.logs_b([1000.1, 2000.2])
csvlogger.critical('3000,4000')
# Log some more records to trigger rollover
for i in range(50):
csvlogger.logs_c([i * 2, float(i**2)])
sleep(0.1)
# Read and print all of the logs from file after logging
all_logs = csvlogger.get_logs(evaluate=False)
for log in all_logs:
print(log)
log_2.csv
:
date,level,value_1,value_2
2022/01/31 15:49:53,logs_a,0,0
2022/01/31 15:49:53,logs_a,1,2
2022/01/31 15:49:53,logs_a,2,4
2022/01/31 15:49:53,logs_a,3,6
2022/01/31 15:49:53,logs_a,4,8
2022/01/31 15:49:53,logs_a,5,10
2022/01/31 15:49:53,logs_a,6,12
2022/01/31 15:49:53,logs_a,7,14
2022/01/31 15:49:53,logs_a,8,16
2022/01/31 15:49:54,logs_a,9,18
2022/01/31 15:49:54,logs_b,1000.1,2000.2
2022/01/31 15:49:54,CRITICAL,3000,4000
2022/01/31 15:49:54,logs_c,0,0.0
2022/01/31 15:49:54,logs_c,2,1.0
2022/01/31 15:49:54,logs_c,4,4.0
2022/01/31 15:49:54,logs_c,6,9.0
2022/01/31 15:49:54,logs_c,8,16.0
2022/01/31 15:49:54,logs_c,10,25.0
2022/01/31 15:49:54,logs_c,12,36.0
2022/01/31 15:49:54,logs_c,14,49.0
2022/01/31 15:49:54,logs_c,16,64.0
2022/01/31 15:49:55,logs_c,18,81.0
2022/01/31 15:49:55,logs_c,20,100.0
2022/01/31 15:49:55,logs_c,22,121.0
2022/01/31 15:49:55,logs_c,24,144.0
2022/01/31 15:49:55,logs_c,26,169.0
2022/01/31 15:49:55,logs_c,28,196.0
2022/01/31 15:49:55,logs_c,30,225.0
2022/01/31 15:49:55,logs_c,32,256.0
log_1.csv
:
date,level,value_1,value_2
2022/01/31 15:49:55,logs_c,34,289.0
2022/01/31 15:49:55,logs_c,36,324.0
2022/01/31 15:49:56,logs_c,38,361.0
2022/01/31 15:49:56,logs_c,40,400.0
2022/01/31 15:49:56,logs_c,42,441.0
2022/01/31 15:49:56,logs_c,44,484.0
2022/01/31 15:49:56,logs_c,46,529.0
2022/01/31 15:49:56,logs_c,48,576.0
2022/01/31 15:49:56,logs_c,50,625.0
2022/01/31 15:49:56,logs_c,52,676.0
2022/01/31 15:49:56,logs_c,54,729.0
2022/01/31 15:49:57,logs_c,56,784.0
2022/01/31 15:49:57,logs_c,58,841.0
2022/01/31 15:49:57,logs_c,60,900.0
2022/01/31 15:49:57,logs_c,62,961.0
2022/01/31 15:49:57,logs_c,64,1024.0
2022/01/31 15:49:57,logs_c,66,1089.0
2022/01/31 15:49:57,logs_c,68,1156.0
2022/01/31 15:49:57,logs_c,70,1225.0
2022/01/31 15:49:57,logs_c,72,1296.0
2022/01/31 15:49:57,logs_c,74,1369.0
2022/01/31 15:49:58,logs_c,76,1444.0
2022/01/31 15:49:58,logs_c,78,1521.0
2022/01/31 15:49:58,logs_c,80,1600.0
2022/01/31 15:49:58,logs_c,82,1681.0
2022/01/31 15:49:58,logs_c,84,1764.0
2022/01/31 15:49:58,logs_c,86,1849.0
log.csv
:
date,level,value_1,value_2
2022/01/31 15:49:58,logs_c,88,1936.0
2022/01/31 15:49:58,logs_c,90,2025.0
2022/01/31 15:49:58,logs_c,92,2116.0
2022/01/31 15:49:58,logs_c,94,2209.0
2022/01/31 15:49:59,logs_c,96,2304.0
2022/01/31 15:49:59,logs_c,98,2401.0
Author
- James Morris (https://james.pizza)
License
- Free software: MIT license
Credits
- Python CSV Rotating Logger gist as starting point
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