How to set up multiple accounts with Mutt E-mail Client
Thanks to this article by Christoph Berg
Directories and files
~/Thanks to this article by Christoph Berg
Directories and files
~/| # | |
| # Working with branches | |
| # | |
| # Get the current branch name (not so useful in itself, but used in | |
| # other aliases) | |
| branch-name = "!git rev-parse --abbrev-ref HEAD" | |
| # Push the current branch to the remote "origin", and set it to track | |
| # the upstream branch | |
| publish = "!git push -u origin $(git branch-name)" |
| /* | |
| * 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%; | |
| } |
Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000Locate the section for your github remote in the .git/config file. It looks like this:
[remote "origin"]
fetch = +refs/heads/*:refs/remotes/origin/*
url = [email protected]:joyent/node.git
Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:
| # -*- mode: conf; -*- | |
| # | |
| # NOTE: Settings generally support python interpolation. This means | |
| # values can contain python format strings which refer to other values | |
| # in the same section, or values in a special DEFAULT section. This | |
| # allows you for example to use common settings for multiple accounts: | |
| # | |
| # [Repository Gmail1] | |
| # trashfolder: %(gmailtrashfolder)s | |
| # |
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
| (ns bootcamp.factorial) | |
| (defn fast-factorial [number] | |
| (loop [n number factorial 1] | |
| (if (zero? n) | |
| factorial | |
| (recur (- n 1) (* factorial n))))) | |
| (defn fast-no-loop-factorial | |
| ([number] (fast-no-loop-factorial number 1)) |