Apple MacBook Pro M1, 32 GB, Ventura 13.2
Documentation based on comments in this Github Elasticsearch issue.
Install Homebrew
Apple MacBook Pro M1, 32 GB, Ventura 13.2
Documentation based on comments in this Github Elasticsearch issue.
# Copyright (c) 2022, Hussain and contributors | |
# For license information, please see license.txt | |
from pymongo import MongoClient | |
from abc import ABC, abstractstaticmethod | |
from frappe.model.document import Document | |
class MongoDBDocument(Document, ABC): | |
@abstractstaticmethod |
#!/usr/bin/env bash | |
# | |
export MYPWD=""; # MySQL password | |
export ADMPWD=""; # Administrator password | |
export THESITE="my site"; # Site name | |
export USERCTX=".profile"; | |
source ${HOME}/${USERCTX}; | |
if [ "${BASH_SOURCE[0]}" -ef "$0" ] |
#!/usr/bin/python3 | |
# | |
# Simple Bloom filter implementation in Python 3 | |
# Copyright 2017 Hector Martin "marcan" <marcan@marcan.st> | |
# Licensed under the terms of the MIT license | |
# | |
# Written to be used with the Have I been pwned? password list: | |
# https://haveibeenpwned.com/passwords | |
# | |
# Download the pre-computed filter here (968MB, k=11, false positive p=0.0005): |
This text now lives at https://github.com/MarcDiethelm/contributing/blob/master/README.md. I turned it into a Github repo so you can, you know, contribute to it by making pull requests.
If you want to contribute to a project and make it better, your help is very welcome. Contributing is also a great way to learn more about social coding on Github, new technologies and and their ecosystems and how to make constructive, helpful bug reports, feature requests and the noblest of all contributions: a good, clean pull request.
/* | |
* I add this to html files generated with pandoc. | |
*/ | |
html { | |
font-size: 100%; | |
overflow-y: scroll; | |
-webkit-text-size-adjust: 100%; | |
-ms-text-size-adjust: 100%; | |
} |