1. We need logging to tell us what's happening in our code 2. Python has an inbuilt logging module which can be imported 3. DEBUG, INFO, WARNING, ERROR & CRITICAL are the level of logging available. 4. WARNING is the default logging level #100DaysOfCode
Having a config file with all components of the logging file is ideal.
It offers:
>> Single point to configure logs, their handlers & their format
>> Ability for non-coders to change the log formats
Day 7:
Since Python 3.2 the config file format has been moved to a YAML which we will see in the coming days
Day 8: A dive into various log handlers which with the help of 1. Have a format in which the log is displayed 2. The level of logs to be displayed decide where the log is written
✅StreamHandler >> Writes to the console
✅FileHandler >> Writes to a file on the disk
are the most common types of handlers used.
Below code snippet shows usage of both.
>> Error logs & above are written to a file
>> All logs are written to the console
>> the logging.debug(), info(), etc signature shows a **kwargs parameter.
It can take in 3 arguments
1⃣ exc_info to display traceback data
2⃣ stack_info to display traceback data
3⃣ extra to display use custom formatter attribute
Since Python 3.8 there is a 4th argument available
4⃣ stacklevel which defaults to 1. If greater than 1, the corresponding number of stack frames are skipped when computing the line number and function name set in the LogRecord created for the logging event
Day 11:
Looking to add more information to your logs like traceback ? Here is how we can do it.
> Python logs are largely meant for humans but sometimes we may need to pass it to log analytics platforms as SPLUNK, Logstash, etc. These platforms consume data in JSON format
> We can use the python-json-logger module to output logs in JSON format
Day 16: LoggerAdapter for adding more info to logs
>> The logging module comes with a number of formatters but often you might need to pass additional context info to the logs & display it. This can be done using the LoggerAdapter class
2⃣ Specify an additional attribute in the formatter
3⃣ We then pass the logger from step #1 & contextual info to LoggerAdapter class
4⃣ The info(), error() & other methods are then called on instance of LoggerAdapter
Day17:
>> We can override the process method in the LoggerAdapter class pass contextual/additional information with each log
>> Overriding the process method gives us the ability to pass a unique contextual info with each log
Day 18: Filtering Python Logs
>> Filters allow you to
> Reject records based on certain criteria
> Add custom info to logs
>> We need to override the logging.Filter & then attach it to handler using .addFilter()
Day 19 Of Python Logging: Filtering
>> Yesterday we saw how we can add filters to logs to prevent certain logs from showing up
>> But what if you need to log to show up but just a part of the log message to be hidden ? Just pass the LogRecord.msg to a new function to do the job
Day 20 Of Python Logging:
>> Logging module is actually implemented in a thread-safe way.
>> Under the hood the logging module uses threading.RLock()
Day24: RotatingFileHandler() To Create Log Files Of Specified Size
✅ maxBytes controls the file size
✅ backCount controls the number of file of size maxBytes. Default is 0 meaning only 1 file
✅ filename attribute is the filename
>> Rotate log files after certain time interval
>> Rotated files are automatically appended with a timestamp
>> Has a rich set of arguments to control the behaviour & output if the Handler.
Python provides a powerful platform for working with data. This talk presents an overview of how to effectively approach optimization of numerical code in Python, touching on tools like numpy, pandas, scipy, cython, numba, & more.
Presentation on how you can write faster Python in your daily work. Briefly explain ways of profiling the code, discuss different code structures and show how they can be improved.
Creating quality content is hard & the only way to do it consistently is to have a solid process/framework.
Without it, you are lost & will quickly feel overwhelmed.
Here's is a small guide to how I manage everything
🧵🧵🧵🧵
1. { Generating Ideas }
✅ My primary source is my job where I get to learn & implement new things.
✅ Secondary sources are Twitter, Reddit, YouTube & Instagram
✅ I also try to take udemy or pluralsight courses to learn & upskill
2. { Documenting Ideas }
✅ The key is to write down and idea as soon as it hits you, so your mobile memo, a whatsapp group or notion mobile app is the best place
✅ Pen & paper also works if you are old school
✅ Responsible for converting requirements into working software
💰Highly Paid
👩💻 Frontend, Backend, Databse, Full stack developers are specific development roles
2. Software Testing
✅ Responsible for verifying if the developed software satisfies the requirements & has required performance levels
💰 Slightly lower paid than Devs
👩💻 Automation & Manual testing are specific roles