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#!/bin/bash

function encrypt {
    input=$1
    echo "Encrypting $input..."
    openssl enc -aes-256-cbc -pbkdf2 -iter 800000 -in "$input" -out cipher.bin
    echo "Encrypted file saved to: $(pwd)/cypher.bin"
}

function decrypt {

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Strong Opinions weakly held

Orginally posted on 07.26.02008 by Paul Saffo, at https://saffo.com

The point of forecasting is not to attempt illusory certainty, but to identify the full range of possible outcomes. Try as one might, when one looks into the future, there is no such thing as “complete” information, much less a “complete” forecast. As a consequence, I have found that the fastest way to an effective forecast is often through a sequence of lousy forecasts. Instead of withholding judgment until an exhaustive search for data is complete, I will force myself to make a tentative forecast based on the information available, and then systematically tear it apart, using the insights gained to guide my search for further indicators and information. Iterate the process a few times, and it is surprising how quickly one can get to a useful forecast.

Since the mid-1980s, my mantra for this process is “strong opinions, weakly held.” Allow your intuition to guide you to a conclusion, no matter how imperfec

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(ns util.redis
  (:refer-clojure :exclude [memoize])
  (:require [taoensso.carmine :as car]))

;; boilerplate stuff that is not in Carmine

(def ^:dynamic ^:private *pool*)
(def ^:dynamic ^:private *spec*)

(defmacro with-redis

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# Taken from https://docs.github.com/en/github/authenticating-to-github/removing-sensitive-data-from-a-repository

# Warning:
# --------
# All stashes may be lost!

PATH_TO_REMOVE=big-folder/commited/by/error

# 1. Force Git to process, but not check out, the entire history of every branch and tag
# 2. Remove the specified file, as well as any empty commits generated as a result

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# Usage: ./pw.sh Github.com

op get item $1 | jq -r '.details.fields[] | select(.designation=="password").value' | xclip -selection c

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# Inspired by https://blog.codinghorror.com/sorting-for-humans-natural-sort-order/
# Adding a `key` argument so we can expect the same behaviour as the builtin `sorted`
import re


def humansorted(seq, key=None):
    """Return the sequence in the order that a human being expects.
    
    If `key` is provided, as per the built-in `sorted` function, it must be a
    callable that accepts a single argument.

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# Following https://stackoverflow.com/questions/34028219/how-to-execute-commands-on-aws-instance-using-boto3
import boto3

ssm = boto3.client('ssm')

response = ssm.send_command(
    InstanceIds=['i-abcde12345...'],
    DocumentName='AWS-RunShellScript',
    Parameters={'commands': ['echo "This command ran on $(date)"']
)

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Say we have a database A hosted at my.first.database.com loaded with data, and we want to replicate this data over database B, located at my.second.database.com. We suppose database A and B have identical schemas, and both databases are accessible via port 5432.

Dump content from database A

 pg_dump --data-only \
 -h my.first.database.com \
 -U {database_user} \
 -f /tmp/dump.sql \
 -T={table pattern to exclude [optional]} \

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"""
https://aws.amazon.com/blogs/aws/manage-instances-at-scale-without-ssh-access-using-ec2-run-command/
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ssm.html
https://stackoverflow.com/questions/34028219/how-to-execute-commands-on-aws-instance-using-boto3
"""
import boto3

# Need AWS credentials in ~/.aws...
ssm = boto3.client('ssm')