RoR setup instructions: I guess you already have XCode on your machine.
In general: avoid sudo where you can, with this setup you can install and run everything without sudo
http://mxcl.github.com/homebrew/
here is a list of the packages on my machine
| Insert the following code into the *.VMX file: | |
| sched.mem.pshare.enable = "FALSE" | |
| mainMem.useNamedFile = "FALSE" | |
| prefvmx.minVmMemPct = "100" | |
| prefvmx.useRecommendedLockedMemSize = "TRUE" | |
| mainMem.partialLazySave = "FALSE" | |
| mainMem.partialLazyRestore = "FALSE" | |
| priority.grabbed = "high" | |
| priority.ungrabbed = "normal" |
| #!/usr/bin/env python | |
| # An example of decoding/encoding datetime values in JSON data in Python. | |
| # Code adapted from: http://broadcast.oreilly.com/2009/05/pymotw-json.html | |
| # Copyright (c) 2023, Abhinav Upadhyay | |
| # All rights reserved. | |
| # | |
| # Redistribution and use in source and binary forms, with or without | |
| # modification, are permitted provided that the following conditions are met: |
| <!doctype html> | |
| <html lang=en> | |
| <head> | |
| <meta charset=utf-8> | |
| <title>Copy To Clipboard Example</title> | |
| </head> | |
| <body> | |
| <input id="txtToCopy" type="text"> | |
| <button id="btnCopy">Copy!</button> |
Last Updated: March 2023
IMPORTANT: Ignore the out-of-date steps below for getting Chromium keys.
Instead, read this up-to-date guide (Jan 2023) written by @LearningToPi.
P.S. Thank you to every contributor below who provided tips over the years on what should be a straightforward process: setting up Chromium for local development.
Long live the web!
| #!/usr/bin/env bash | |
| PLUGIN_BASE='/opt/cisco/secureclient/bin/plugins' | |
| read -r -d '' USAGE << EGASU | |
| Usage: `basename $0` [-s|-e|-d|-h] | |
| -s, --status Print Umbrella Roaming Security module status | |
| -e, --enable Enable Umbrella Roaming Security module | |
| -d, --disable Disable Umbrella Roaming Security module |
| import perfplot | |
| import pandas as pd | |
| def vec(df): | |
| return df['A'] + df['B'] | |
| def vec_numpy(df): | |
| return df['A'].to_numpy() + df['B'].to_numpy() | |
| def list_comp(df): |