- http://stackoverflow.com/questions/804115 (
rebasevsmerge). - https://www.atlassian.com/git/tutorials/merging-vs-rebasing (
rebasevsmerge) - https://www.atlassian.com/git/tutorials/undoing-changes/ (
resetvscheckoutvsrevert) - http://stackoverflow.com/questions/2221658 (HEAD^ vs HEAD~) (See
git rev-parse) - http://stackoverflow.com/questions/292357 (
pullvsfetch) - http://stackoverflow.com/questions/39651 (
stashvsbranch) - http://stackoverflow.com/questions/8358035 (
resetvscheckoutvsrevert)
Visit my blog.
git init
or
| #!/bin/bash | |
| ##################################################### | |
| # Name: Bash CheatSheet for Mac OSX | |
| # | |
| # A little overlook of the Bash basics | |
| # | |
| # Usage: | |
| # | |
| # Author: J. Le Coupanec | |
| # Date: 2014/11/04 |
Moved to git repository: https://github.com/denji/nginx-tuning
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
Magic words:
psql -U postgresSome interesting flags (to see all, use -h or --help depending on your psql version):
-E: will describe the underlaying queries of the\commands (cool for learning!)-l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)