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a python refactoring IDE and library...

Project description

Overview

rope is a python refactoring IDE and library. The IDE uses the library to provide features like refactoring, code assist, and auto-completion. It is written in python. The IDE uses Tkinter library.

New Features

  • Adding custom source folders in project config.py
  • A simple UI for performing restructurings; C-c r x
  • Restructurings

From this release rope will no longer support Python 2.4 and rope 0.5 was the last version that supported it.

Custom Source Folders

By default rope searches the project for finding source folders (folders that should be searched for finding modules). You can add paths to that list using source_folders config. Note that rope guesses project source folders correctly most of the time. You can also extend python path using python_path config.

Restructurings

Restructuring support is one of the main goals of the 0.6 release of rope. rope.refactor.restructure can be used for performing restructurings. Currently a simple dialog has been added for performing them, but you cannot add checks to your restructuring in that dialog, yet. But the full functionality is available if you’re using rope as a library.

A restructuring is a program transformation; not as well defined as other refactorings like rename. Let’s see some examples.

Example 1

In its basic form we have a pattern and a goal. Consider we were not aware of the ** operator and wrote our own

def pow(x, y):
    result = 1
    for i in range(y):
        result *= x
    return result

print pow(2, 3)

Now that we know ** exists we want to use it wherever pow is used (There might be hundreds of them!). We can use a pattern like:

pattern = 'pow(${?param1}, ${?param2})'

Goal can be some thing like:

goal = '${?param1} ** ${?param2}'

Note that ${...} is used to match something in the pattern. If names that appear in ${...} start with a leading ? every expression at that point will match, otherwise only the specified name will match (This form is not useful if you’re not using checks that is described later).

You can use the matched names in goal and they will be replaced with the string that was matched in each occurrence. So the outcome of our restructuring will be:

def pow(x, y):
    result = 1
    for i in range(y):
        result *= x
    return result

print 2 ** 3

It seems to be working but what if pow is imported in some module or we have some other function defined in some other module that uses the same name and we don’t want to change it. Checks come to rescue. Each restructuring gets a checks parameter in its constructor. It can be a dictionary. Its keys are pattern names that appear in the pattern (the names in ${...}) or it can be pattern names plus any of .object or .type. The values can be rope rope.base.pyobject.PyObject or rope.base.pynames.PyNames objects.

For solving the above problem we change our pattern. But goal remains the same:

pattern = '${?pow_func}(${?param1}, ${?param2})'
goal = '${?param1} ** ${?param2}'

Consider the name of the module containing our pow function is mod. checks can be:

checks = {}
mod = project.get_pycore().get_module('mod')
pow_pyname = mod.get_attribute('pow')
checks['?pow_func'] = pow_pyname

Note that project is an instance of rope.base.project.Project. We can perform the restructuring now:

from rope.refactor import restructure

restructuring = restructure.Restructure(project, pattern, goal, checks)
project.do(restructuring.get_changes())

PyNames and PyObjects are used to describe names and objects in rope. Each name in a program (a PyName) might reference an object (a PyObject) that has a type (a PyObject).

Example 2

As another example consider:

class A(object):

    def f(self, p1, p2):
        print p1
        print p2


a = A()
a.f(1, 2)

Later we decide that A.f() is doing too much and we want to divide it to A.f1() and A.f2():

class A(object):

    def f(self, p1, p2):
        print p1
        print p2

    def f1(self, p):
        print p

    def f2(self, p):
        print p2


a = A()
a.f(1, 2)

But who’s going to fix all those nasty occurrences (Actually this situation can be handled using inline method refactoring but this is just an example; Consider inline refactoring is not implemented yet!). Restructurings come to rescue:

pattern = '${?inst}.f(${?p1}, ${?p2})'
goal = '${?inst}.f1(${?p1}); ${?inst}.f2(${?p2})\n'

mod = project.get_pycore().get_module('my.mod')
a_class_pyname = mod.get_attribute('A')
a_class_pyobject = a_pyname.get_object()
checks = {}
checks['?inst.type'] = a_class_pyobject

We can perform the restructuring using Restructure class as shown above. We will have:

class A(object):

    def f(self, p1, p2):
        print p1
        print p2

    def f1(self, p):
        print p

    def f2(self, p):
        print p2


a = A()
a.f1(1); a.f2(2)

Issues

Adding checks is not available in the restructuring dialog, yet. The main reason is that I couldn’t find a user-friendly way for specifying them (though I have something in mind for the next release). If you have any idea I’ll be glad to hear.

The other constraint that restructurings have is that pattern names can only appear in at the start of an expression. For instance var.${name} is invalid. These situations can usually be fixed by specifying good checks, for example on the type of var and using a ${var}.name pattern.

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