Favor logging
for detailed analysis; fallback to pprint
for clarity, and print
for simplicity.
← this item is applicable for step 1 of debugging
Let's break down the scenarios and discuss the appropriate usage of
print
statements, pprint
, and logging
.Using print
Statements
Print statements are straightforward to use. You can simply use the
print()
function to output messages to the console. TheTechCruise.com Pyodide Terminal
print("My awesome blog!")
They are useful for -
- quick debugging and understanding the flow of the program.
- providing immediate feedback during development.
They can be preferred -
- For small scripts or quick debugging purposes.
- When all we need is simple, ad-hoc logging without much formatting.
Should not be preferred -
- In large-scale applications where you need more structured logging and better control over log levels.
- In production code where you need to log errors, warnings, and informational messages systematically.
- When you need more standardization and customization options in a broader way
Using pprint
instead of print
pprint
is particularly useful when you want to print complex data structures like dictionaries or lists in a more readable format. To use
pprint
though, we need to import the pprint
module and use pprint()
function to print the data structures.TheTechCruise.com Pyodide Terminal
from pprint import pprint
# Example usage:
pprint(my_complex_data_structure)
The prime reasons as to why we would prefer
pprint
over print
is - Provides more readable output for complex data structures.
- Helpful in understanding nested structures at a glance.
However we don’t need to use
pprint
if we have something easy to print, like a simple string or a value that can be represented in a string. Also incases Using logging
instead of print
or pprint
logging
is a more robust and flexible way of handling logging compared to print
statements.While print statements are useful for basic debugging, logging provides a more robust solution for detailed analysis. Python's built-in
logging
module allows you to log messages at various levels (e.g., DEBUG, INFO, WARNING, ERROR, CRITICAL), enabling you to control the verbosity of your logs.It can be preferred for the below reasons -
- Provides better control over log levels (debug, info, warning, error, etc.).
- Enables logging to various destinations (file, console, etc.).
- Allows customization of log message formatting.
- In large-scale applications or production code where structured logging is essential.
- When you need to log messages with different log levels.
If we want to use logging here is an example -
- Import the
logging
module and configure loggers, handlers, and formatters as needed. Then uselogging.info()
,logging.error()
, etc., to log messages.
TheTechCruise.com Pyodide Terminal
import logging
# Configure logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
# Example usage:
logging.info("This is an informational message")
The only cons in this however can be that - it requires additional setup and configuration compared to
print
, and that it may add complexity to simple scripts.Conclusion:
ㅤ | print | pprint | logging |
Pros | Quick and easy to use | Improved readability for complex data structures | Better control over log levels and formatting |
Cons | Lack of control over log levels and formatting | Additional overhead for formatting | Requires additional setup and configuration |
When to Use | Quick debugging, small scripts | Debugging complex data structures | Large-scale applications, production code |
When not to Use | Large-scale applications, production code | Simple data structures | Small scripts, quick debugging |
Choose the appropriate method based on the requirements of your project, considering factors like simplicity, readability, and scalability.