redg25/tasklogger

loggertask

loggertask is a module which allows:

• Handling of logs on 4 different file types:csv, json, sqlite, txt.
• Logs retrieval with predefined queries.

Author

Regis Corblin

Handler classes

class CsvHandler(filename:str)
class JsonHandler(filename:str)
class SqlHandler(filename:str)
class FileHandler(filename:str)

Parameter
- filename: name of the file where the logs are saved

Ex:

myhandler = CsvHandler('logs.csv')

Logger class

ProfilLogger(handlers: List[Handler])

Parameter
- handlers: List of handlers that will be responsible for saving and reading log entries

Ex:

logger = ProfilLogger([myhandler,anotherhandler])

Methods

Method signature	Description
debug(msg: str)	Logs a message with level DEBUG
info(msg: str)	Logs a message with level INFO
warning(msg: str)	Logs a message with level WARNING
error(msg: str)	Logs a message with level ERROR
critical(msg: str)	Logs a message with level CRITICAL
set_log_level(level: str)	Set minimal log level to be saved

Order of criticality as above

Ex:

logger.set_log_level('INFO')
logger.warning('This is a warning')

Log reader class

ProfilLoggerReader(handler: Handler)`

Parameter
- handler: Handler from which entries will be extracted

Methods

Method signature	Description
find_by_text(text: str, start_date: Optional[str] = None, end_date: Optional[str] = None) -> List[LogEntry]	Find log entries that contain given text. If any datetime is given, filter logs according to that datetime.
find_by_regex(regex: str, start_date: Optional[str] = None, end_date: Optional[str] = None) -> List[LogEntry]	Finds logs by a given regexp. If any datetime is given, filter logs according to that datetime.
group_by_level(start_date: Optional[str] = None, end_date: Optional[str] = None) -> Dict[str, List[LogEntry]]	Group logs by level. If any datetime is given, filter logs according to that datetime.
group_by_month(start_date: Optional[str] = None, end_date: Optional[str] = None) -> Dict[str, List[LogEntry]]	Group logs by month. If any datetime is given, filter logs according to that datetime.

All dates to be given with the following format:'YYYY/MM/DD HH:MM:SS'

#USAGE

json_handler = JsonHandler("logs.json")
csv_handler = CsvHandler("logs.csv")
sql_handler = SqlHandler("logs.sqlite")
file_handler = FileHandler("logs.txt")

logger = ProfilLogger(handlers=[json_handler, csv_handler, sql_handler, file_handler])
logger.set_log_level("WARNING")
logger.debug("You reach this debug line of code")
logger.info("FYI, this an info message")
logger.warning("Attention, something doesn't look good")
logger.error("There is definitely something wrong")
logger.critical("Nothing can be done, the application is down")

# The logs are stores in logs.json, logs.csv, logs.sqlite and logs.txt

# Logs are being read from the logs.csv file
log_reader = ProfilLoggerReader(handler=csv_handler)
log_reader.find_by_text("something") # returns list of LogEntry that contains the messages: "Attention, something doesn't look good","There is definitely something wrong"
log_reader.find_by_regex(r'[p]{2,}') # returns list of logEntry that contains: "Nothing can be done, the application is down"
log_reader.group_by_level(start_date='2015/01/01 01:01:01',end_date='2021/01/01 01:01:01') #returns dictionary of LogEntry grouped by level that were logged between the specified time frame.
log_reader.group_by_month(start_date='2015/01/01 01:01:01') #returns dictionary of LogEntry grouped by month that were logged after the specified start date.

Testing

You can use the sample of logs sample_test_csv_handler.csv (available on this repository) to run tests on log reader methods
The file Usage_example.py runs all methods of logs creation for all types of handlers and all log reader methods for the csv test file.