0 purchases
Description:
Scripy 0.9.3
The beginning
The shell scripting gets to be non-maintainable code; its sintaxis is very
cryptic and it’s very hard to debug. Aside all these negative point increase
at the same time as the size of the program grows.
Here is where Python comes.
Whatever administrator without great knowledge about programming can built basic
scripts fastly after of read the tutorial. Its sintaxis is as pseudo-code so
it’s very easy to code. The basic errors –as syntax errors and exceptions–
help to debug together to the error logging system implemented in logging
module. In addition Python comes with an extensive standard library of useful
modules which will help to speed up the development of scripts, and if you need
some another module could be searched in the PyPi repository.
I had forked the Fabric project to add the files editing and something other
thing but my goal is very different to that project, aside of that my changes
were not added until that I deleted my forked repository (after many months).
Scripy
The main tool of this package is the shell.Run() class which lets to run
system commands in the same shell. It works well with pipes and pass the shell
variables. It doesn’t makes pattern expansion (* ?) as in the shell but could be
used shell.expand() instead.
Commands path
The absolute path of the commands used by Scripy are in the _path module so
it’s avoid some possible trojan. The path is right for Debian/Ubuntu systems
since it’s where I can check them.
Without the command expansion, there would be to use:
import scripy
from scripy import _path
run = scripy.Run()
run("{sudo} {ls} /dev/null".format(sudo=_path.Bin.sudo,
ls=_path.Bin.ls))
But with the command expansion, if any command is prepended with ! then get
its absolute path:
run("!sudo !ls /dev/null")
Edit
Something that is very important in the shell script is the files editing, and
Scripy makes it very easy using the edit.Edit() class. It only creates
backups to files that are going to be modified, lets modify files owned by
another users (since that uses sudo when the class is instancied), and has
methods for append text, comment or comment out lines that start with a
determined chracter, and a wrapper to sed which lets backup the file.
Logging
Yamlog manages the error catching code and error reporting.
New scripts
To build scripts based on Scripy, it is advised that been created a module
(_path) with the new commands to use (that are not in Scripy._path), and
another one (_config) where to instantiate scripy.Run().
_path:
class Bin(object):
new_command = '/path/to/new/command'
_config:
import scripy
from . import _path
run = scripy.Run(bin=_path.Bin)
Change history
v0.9.3, 2010-02-16
Use the platform module to get information related to the system.
The logger has been moved to a separated project called Yamlog.
Scripts based on Scripy can add more command paths at instantiating
scripy.Run().
Fixed edit.Edit() to can edit files owned by another user.
v0.9.2, 2010-02-04
Path expansion for commands.
shell.Run() returns a named tuple with returncode and stdout.
Nose was capturing all log output so it was not being written to the log file.
Renamed class shell.Code() to shell.ReturnCode(). It manages now the valid
exit status codes (mainly from commands run in the shell).
Better error catching code and error reporting.
Changed the logging handler to have rotation of disk log files.
PyYAML is optional to install.
v0.9, 2010-01-28
Initial release.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Files:
Customer Reviews
There are no reviews.
