


Simple Python Logging - and a digression on dependencies, trust, and Copy/pasting code
Header Image (C) Tai Kedzierski
Goto Snippet
This post is opinionated.
Python's default log setup is unhelpful; it works against the "batteries included" approach we have come to expect.
From a useful log message, I want to know when, what level, and what information. I may want it on console, I may want it in a file.
This should be simple - but in Python I end up every time having to look up how to create a full logging utility with custom file handling and string formatting.
It should be as simple as logger = getLogger(), but the default behaviour for some unknown reason is to provide a completely useless formatting, and no shorthand for a sensible default.
That or I need to download some pip package of unknown provenance, trust that it hasn't been name-hijacked, or doing some obfuscated exfilration. The leftpad incident from 2016 comes to mind, as well as the Revival hijack attack from 2024 which was essentially the same problem in a different repo system.
In fact, any user-repo without namespacing is vulnerable to this: Node's npm, Python's pip, Arch's AUR, Canonical's snap ... to name a handful who just let users upload whatever. Even namespacing isn't a guarantee of trust - I've come across projects that distribute their software through these channels not through the project's name, but via some arbitrary dev's monicker, raising doubt as to the authenticity of the package. I gave my thought process on how to decide on whether to trust a source in a previous post on using syncthing in a work environment.
External dependencies in user-controlled repos are the devil, and should only be considered when the solution to a problem is complex. And in general, simple solutions should just exist directly in the code base - ideally self-written, but sometimes the problem just strafes into the "cumbersome enough" space to make a dependency feel both reasonable and icky.
The answer: write it once, stash it away in a Github gist or in a "useful snippets" repo of your own. Copy and paste.
Copy Paste? Ew!
"Copy and paste" of code probably sends alarm bells ringing for any seasoned coder. "Don't repeat yourself," "use a package manager," "write once, update everywhere." These are good instincts to have, but case-by-case, it is also good to know when copy-paste is preferable.
In this case, the requirement is to avoid unnecessary external dependencies for a simple solution to a simple need . In leftpad as with this mini-logger, the required code snippet is short and easy to understand ; it is no loss to reimplement if needed. It is also appropriately licensed (yes, it may be just a snippet; it remains however recommendable to ensure that what you are copying is indeed allowable. Be wary of copying random blobs of code.)
Mini Logger Snippet
I include below a code snippet for a mini-logger utility which allows for a single call with minimal configuration:
from minilog import SimpleLogger LOG = SimpleLogger(name="mylog", level=SimpleLogger.INFO) LOG.info("this is useful")
Which prints to console:
2024-11-20 10:43:44,567 | INFO | mylog : this is useful
The mini-logger code
Copy this into a minilogger.py file in your project. Tada - no external dependency needed. Left untouched, it will remain the same forever. No name hijacking. No supply-chain injection.
# For completeness: # (C) Tai Kedzierski - Provided under MIT license. Go wild. import logging class SimpleLogger(logging.Logger): FORMAT_STRING = '%(asctime)s | %(levelname)s | %(name)s : %(message)s' ERROR = logging.ERROR WARN = logging.WARN INFO = logging.INFO DEBUG = logging.DEBUG def __init__(self, name="main", fmt_string=FORMAT_STRING, level=logging.WARNING, console=True, files=None): logging.Logger.__init__(self, name, level) formatter_obj = logging.Formatter(fmt_string) if files is None: files = [] elif isinstance(files, str): files = [files] def _add_stream(handler:logging.Handler, **kwargs): handler = handler(**kwargs) handler.setLevel(level) handler.setFormatter(formatter_obj) self.addHandler(handler) if console is True: _add_stream(logging.StreamHandler, stream=sys.stdout) for filepath in files: _add_stream(logging.FileHandler, filename=filepath)
The MIT license essentially allows you to "do whatever you want with this." No strings attached.
There we are. A simple log ?
The above is the detailed content of Simple Python Logging - and a digression on dependencies, trust, and Copy/pasting code. For more information, please follow other related articles on the PHP Chinese website!

The reasons why Python scripts cannot run on Unix systems include: 1) Insufficient permissions, using chmod xyour_script.py to grant execution permissions; 2) Shebang line is incorrect or missing, you should use #!/usr/bin/envpython; 3) The environment variables are not set properly, and you can print os.environ debugging; 4) Using the wrong Python version, you can specify the version on the Shebang line or the command line; 5) Dependency problems, using virtual environment to isolate dependencies; 6) Syntax errors, using python-mpy_compileyour_script.py to detect.

Using Python arrays is more suitable for processing large amounts of numerical data than lists. 1) Arrays save more memory, 2) Arrays are faster to operate by numerical values, 3) Arrays force type consistency, 4) Arrays are compatible with C arrays, but are not as flexible and convenient as lists.

Listsare Better ForeflexibilityandMixdatatatypes, Whilearraysares Superior Sumerical Computation Sand Larged Datasets.1) Unselable List Xibility, MixedDatatypes, andfrequent elementchanges.2) Usarray's sensory -sensical operations, Largedatasets, AndwhenMemoryEfficiency

NumPymanagesmemoryforlargearraysefficientlyusingviews,copies,andmemory-mappedfiles.1)Viewsallowslicingwithoutcopying,directlymodifyingtheoriginalarray.2)Copiescanbecreatedwiththecopy()methodforpreservingdata.3)Memory-mappedfileshandlemassivedatasetsb

ListsinPythondonotrequireimportingamodule,whilearraysfromthearraymoduledoneedanimport.1)Listsarebuilt-in,versatile,andcanholdmixeddatatypes.2)Arraysaremorememory-efficientfornumericdatabutlessflexible,requiringallelementstobeofthesametype.

Pythonlistscanstoreanydatatype,arraymodulearraysstoreonetype,andNumPyarraysarefornumericalcomputations.1)Listsareversatilebutlessmemory-efficient.2)Arraymodulearraysarememory-efficientforhomogeneousdata.3)NumPyarraysareoptimizedforperformanceinscient

WhenyouattempttostoreavalueofthewrongdatatypeinaPythonarray,you'llencounteraTypeError.Thisisduetothearraymodule'sstricttypeenforcement,whichrequiresallelementstobeofthesametypeasspecifiedbythetypecode.Forperformancereasons,arraysaremoreefficientthanl

Pythonlistsarepartofthestandardlibrary,whilearraysarenot.Listsarebuilt-in,versatile,andusedforstoringcollections,whereasarraysareprovidedbythearraymoduleandlesscommonlyusedduetolimitedfunctionality.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Zend Studio 13.0.1
Powerful PHP integrated development environment

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

SublimeText3 Chinese version
Chinese version, very easy to use

Atom editor mac version download
The most popular open source editor
