| <!DOCTYPE html> | |
| <html><head> | |
| <style> | |
| python { display: none; } | |
| </style> | |
| <script src="https://cdn.jsdelivr.net/pyodide/v0.20.0/full/pyodide.js"></script> | |
| <script> | |
| // https://pyodide.org/en/stable/usage/quickstart.html | |
| pyscripts = document.getElementsByTagName("python"); | |
| let pyodide = null |
| # ... add this to your bashrc to turn off those pesky warnings when running Groovy | |
| # From https://github.com/apache/groovy/commit/a7f7cdd352a40dd7acd2def999eb560c2b76904e | |
| # Via https://dev.to/erichelgeson/removing-illegal-reflective-access-warnings-in-grails-4-393o | |
| _java_opens=( | |
| --add-opens=java.base/java.io=ALL-UNNAMED | |
| --add-opens=java.base/java.lang=ALL-UNNAMED | |
| --add-opens=java.base/java.lang.annotation=ALL-UNNAMED | |
| --add-opens=java.base/java.lang.invoke=ALL-UNNAMED | |
| --add-opens=java.base/java.lang.module=ALL-UNNAMED |
The default setup for the logging utility is a little unwieldy to set up for every project - though once done, it is likely to seldom change.
This snippet provides a pre-configured global logging utility allowing for a log level to be set via environment variable,
as well as a pretty-print dump() log function that writes when level is set to DEBUG.
By default, logging goes to stdout, but can be redirected to a file.
| """ | |
| A Python decorator is a special function that can be added above a | |
| callable definition (function, class, anything that implements the | |
| `__call__()` method) | |
| When a decorated function is called, it is in fact the decorator | |
| itself that is called, and the wrapped callable is then normally | |
| called by the implementing handler of the decorator. | |
| A Python decorator is comprised of 3 parts: |
The Love2D wiki is a great starting resource. Mostly I do small-time game development for fun, on long flights or train journeys, or out in remote places. Frankly, it's the only time when I am guaranteed time to not be disturbed for sufficiently long periods.
And so, I need the main wiki in local, offline, usable format.
This script is a considereate slurper which shouldn't DoS the server in the slightest.
As a network behaviour demonstration, I did a repeated clone-out of a Git repository, writing its timestamp data with date '+%F %T' in columns one and two (start and end times) of a CSV
This Python script processes that CSV to produce a plot of the durations:
datetimematplotlib.pyplot
| """ Rename files | |
| rename-tracks.py TRACKFILE [apply] | |
| TRACKFILE is a basic text file, each line containing a track name. | |
| This script naively looks for the track name in each file name. | |
| If found, the old file name and new file name are printed. | |
| If a title matches multiple files, an error is raised. |
| import sys | |
| from collections import namedtuple | |
| # A friendlier named object for working with each output line | |
| Analysis = namedtuple("Analysis", [ | |
| "NLOC", # Count of number of active LOC (excl whitespace) | |
| "CCN", # Cyclomatic Complexity Number | |
| "token", # token count: how many syntactic tokens ("if", "[", "5", etc) are used in the functions | |
| "PARAM", # number of parameters to the function |
I was curious to know what level of precision I could get when using time.sleep(x),
like, if it made any sense to try and sleep for say 0.0132 seconds.
It turns out, it does. On a Windows machine with a 1.6GHz processor, I get a sample rate such:
$ python3 time_sampling.py 6
Average step over 1000000 (100.0%) iterations: 2.77e-07