lucaswiman

#!/bin/bash -e
# set -x

# References:
# * https://wiki.mozilla.org/Sandbox/OS_X_Rule_Set
# * https://reverse.put.as/wp-content/uploads/2011/09/Apple-Sandbox-Guide-v1.0.pdf
# * https://mybyways.com/blog/creating-a-macos-sandbox-to-run-kodi (sound)
# * See also existing rulesets in `/usr/share/sandbox`
# * https://github.com/devpi/devpi (pypi proxy)
echo args="$@"

lucaswiman

from typing import Callable
class AuditDescriptor:
    def __init__(self, field_name, audit_action):
        self.field_name = field_name
        self.audit_action = audit_action

    def __get__(self, instance, owner):
        if instance is None:
            return self
        return instance.__dict__[self.field_name]

lucaswiman

cat /usr/share/dict/words \
  | tr '[:upper:]' '[:lower:]' \
  | grep -E '^.....$' \
  | shuf | head -n 1

lucaswiman

#!/usr/bin/env python3
"""
Run a sqlite query on the given database and print the results using pandas.

Also adds user-defined confidence interval functions to the database.

Usage:
    sqlite-query.py database.db "SELECT * FROM table WHERE column = 'value'"
"""

lucaswiman

>>> import inspect, functools
>>>
>>> class Void:
...     pass
...
>>> def handle_defaults(f, undefined=Void):
...     sig = inspect.signature(f)
...     @functools.wraps(f)
...     def defaults_handled(*args, **kwargs):
...         bound = sig.bind(*args, **kwargs)

lucaswiman

>>> import dis
>>> from itertools import islice
>>> def first_two_islice(it):
...     return tuple(islice(it, 2))
...
>>> def first_two_destructuring(it):
...     x, y, *rest = it
...     return x, y
...
>>> dis.dis(first_two_islice)

lucaswiman

lucaswiman

from pdb import Pdb, set_trace
from contextlib import contextmanager

@contextmanager
def debug_at(filename, lineno, condition=None):
    p = Pdb()
    filename = p.canonic(filename)
    break_command = f"break {filename}:{lineno}" + (f', {condition}' if condition else '')
    p.rcLines.append(break_command)
    p.rcLines.append('continue')

lucaswiman

const tar = require("tar");

exports.unTar = (tarballStream) => {
    const results = {};
    return new Promise((resolve, reject) => {
        const parser = tarballStream.pipe(new tar.Parse());
        parser.on(
            "entry", async (entry) => {
                const chunks = []
                for await (let chunk of entry) {

lucaswiman

import numpy as np
import cv2


def sp_noise(image, prob):
    '''
    Add salt and pepper noise to image
    prob: Probability of the noise
    '''
    output = image.copy()