3.5 fps, Paperwhite 3
@adtac_
mobileread.com is your best resource here, follow the instructions from the LanguageBreak thread
I didn't really follow the LanguageBreak instructions because I didn't care about most of the features + I was curious to do it myself, but the LanguageBreak github repo was invaluable for debugging
| XZ Backdoor symbol deobfuscation. Updated as i make progress |
| // ==UserScript== | |
| // @name Disable Jira Click Edit | |
| // @namespace http://tampermonkey.net/ | |
| // @version 0.1 | |
| // @description Disable click edit in Jira issue descriptions | |
| // @author fanuch | |
| // @match https://*.atlassian.net/browse/* | |
| // @icon https://www.google.com/s2/favicons?sz=64&domain=atlassian.net | |
| // @grant none | |
| // ==/UserScript== |
| #!/usr/bin/env python3 | |
| import json | |
| import glob | |
| import argparse | |
| import pandas as pd | |
| ITEM_TYPE = "lineItem/LineItemType" |
⚠️ Note 2023-01-21
Some things have changed since I originally wrote this in 2016. I have updated a few minor details, and the advice is still broadly the same, but there are some new Cloudflare features you can (and should) take advantage of. In particular, pay attention to Trevor Stevens' comment here from 22 January 2022, and Matt Stenson's useful caching advice. In addition, Backblaze, with whom Cloudflare are a Bandwidth Alliance partner, have published their own guide detailing how to use Cloudflare's Web Workers to cache content from B2 private buckets. That is worth reading,
A curated list of arrrrrrrrr!
In response to this brief blog entry, @antirez tweeted for some documentation on high-performance techniques for Redis. What I present here are general high-performance computing (HPC) techniques. The examples are oriented to Redis. but they work well for any program designed to be single- or worker-threaded and asynchronous (e.g. uses epoll).
The motivation for using these techniques is to maximize performance of our system and services. By isolating work, controlling memory, and other tuning, you can achieve significant reduction in latency and increase in throughput.
My perspective comes from the microcosm of my own bare-metal (vs VM), on-premises deployment. It might not be suitable for all scenarios, especially cloud deployments, as I have little experience with HPC there. After some discussion, maybe this can be adapted as [redis.io documentation](https://redis.io/do
See how a minor change to your commit message style can make a difference.
git commit -m"<type>(<optional scope>): <description>" \ -m"<optional body>" \ -m"<optional footer>"
