Knitr beats the socks off of an iPython notebook. Both tools do the same job, but knitr doesn't require you to leave your established text editor workflow.
Tested specifically on OS X 10.9, with R 3.1.2 and Anaconda python distribution.
PATH. If you need to specify a python 3.x or python 2.x environment, make your life easier and do it from the command line before you do anything else.
| { | |
| "cmd": ["vcvars32.bat", "&", "cl", "/EHsc", "${file}"], | |
| "file_regex": "^(..[^:]*):([0-9]+):?([0-9]+)?:? (.*)$", | |
| "working_dir": "${file_path}", | |
| "selector": "source.c, source.cpp, source.c++", | |
| // By default cl is not in your PATH, so add it to your path (preferably) | |
| // or uncomment "path" and check that it has correct value | |
| //"path": "path:/to/folder/where/cl.exe/located", | |
| // this also will set path for vcvars32.bat | |
| "shell": true, // Without this sublime has hard times to parse "&" in out command line |
| sudo openvpn --config *.opvn | |
| apt-get update | |
| apt-get install vim | |
| wget http://d3kbcqa49mib13.cloudfront.net/spark-1.3.0-bin-hadoop2.4.tgz | tar zxf | |
| hadoop fs -mkdir /spark | |
| hadoop fs -put spark-1.3.0-bin-hadoop2.4.tgz /spark | |
| hadoop fs -du -h /spark | |
| cp spark-env.sh.template spark-env.sh | |
| MAX32 = uint32(0xffffffff) | |
| @cuda.jit("(uint64[::1], uint64)", device=True) | |
| def cuda_xorshift(states, id): | |
| x = states[id] | |
| x ^= x >> 12 | |
| x ^= x << 25 | |
| x ^= x >> 27 | |
| states[id] = x |
| from pyparsing import * | |
| stack = { | |
| "my_number": 4, | |
| "my_list": [] | |
| } | |
| script = \ | |
| """ | |
| push 5 to my_list. |