Develop Reference

waitForObject returns the first object matching the pattern. Is there a way I can get list of all objects?

I need a list of all objects with same property/type. Is there a way or an API(just like waitForObject) where I give the type/property and get list of all objects.
I am using Python script for Squish.

You can findAllObjects(objectName):
This function finds and returns a list of object references identified by the symbolic or real (multi-property) name objectName. Because it can return multiple object references, the name must not contain the occurrence property. The given name can also be a native script dictionary (resp. hash) value.

An other (more complicated but more generic) way might be using the object.children() to the container of the objects you are looking for. The list of children needs to be filtered afterwards.

I have single-element arrays. How do I change them into the elements themselves?

Importing a JSON document into a pandas dataframe using records = pandas.read_json(path), where path was a pre-defined path to the JSON document, I discovered that the content of certain columns of the resulting dataframe "records" are not simply strings as expected. Instead, each "cell" in such a column is an array, containing one single element -- the string of interest. This makes selecting columns using boolean indexing difficult. For example, records[records['category']=='Python Books'] in Ipython outputs an empty dataframe; had the "cells" contained strings instead of arrays of strings, the output would have been nonempty, containing rows that correspond to python books.
I could modify the JSON document, so that "records" reads the strings in properly. But is there a way to modify "records" directly, to somehow strip the single-element arrays into the elements themselves?

Update: After clarification, I believe this might accomplish what you want while limiting it to a single iteration over the data:
nested_column_1 = records["column_name_1"]
nested_column_2 = records["column_name_2"]
clean_column_1 = []
clean_column_2 = []
for i in range(0, len(records.index):
clean_column_1.append(nested_column_1[i][0])
clean_column_2.append(nested_column_2[i][0])
Then you convert the clean_column lists to Series like you mentioned in your comment. Obviously, you make as many nested_column and clean_column lists as you need, and update them all in the loop.
You could generalize this pretty easily by keeping a record of "problem" columns and using that to create a data structure to manage the nested/clean lists, rather than declaring them explicitly as I did in my example. But I thought this might illustrate the approach more clearly.
Obviously, this assumes that all columns have the same number of elements, which maybe isn't a a valid assertion in your case.
Original Answer:
Sorry if I'm oversimplifying or misunderstanding the problem, but could you just do something like this?
simplified_list = [element[0] for element in my_array_of_arrays]
Or if you don't need the whole thing at once, just a generator instead:
simplifying_generator = (element[0] for element in my_array_of_arrays)

Retrieving a specific set element in Python

Essentially this is what I'm trying to do:
I have a set that I add objects to. These objects have their own equality method, and a set should never have an element equal to another element in the set. However, when attempting to insert an element, if it is equal to another element, I'd like to record a merged version of the two elements. That is, the objects have an "aux" field that is not considered in its equality method. When I'm done adding things, I would like an element's "aux" field to contain a combination of all of the "aux" fields of equal elements I've tried to add.
My thinking was, okay, before adding an element to the set, check to see if it's already in the set. If so, pull it out of the set, combine the two elements, then put it back in. However, the remove method in Python sets doesn't return anything and the pop method returns an arbitrary element.
Can I do what I'm trying to do with sets in Python, or am I barking up the wrong tree (what is the right tree?)

Sounds like you want a defaultdict
from collections import defaultdict
D = defaultdict(list)
D[somekey].append(auxfield)
Edit:
To use your merge function, you can combine the code people have given in the comments
D = {}
for something in yourthings:
if something.key in D:
D[something.key] = something.auxfield
else:
D[something.key] = merge(D[something.key], something.auxfield)

How to set multiple items into a GtkSelection for Treeview drag and drop

My current project uses a Gtk.TreeView to display the contents of a ListView with four fields per row, two strings, an int and a boolean. I'm trying to implement drag and drop rearrangement of rows in the TreeView. I don't want simply to use TreeView.set_reorderable(True) for the built-in drag and drop because I want to have some control over the insertion and deletion of data from the model as well as to be able to implement undo/redo of drag and drop operations. I'm using Python 3.2 and PyGObject 3.
The problem I'm now having is figuring out how in my drag_data_get method to set the selection data object with the two strings, one int and one bool that make up the row to be dragged and dropped. All the example code I've been able to find involves treeviews with a single column with string values that get set into the selection with something like this:
def drag_data_get_data(self, treeview, context, selection, target_id, etime):
treeselection = treeview.get_selection()
model, iter = treeselection.get_selected()
data = bytes(model.get_value(iter, 0), "utf-8")
selection.set(selection.get_target(), 8, data)
All my efforts to set the selection object with the data from one of my TreeView rows have failed. The int and bool values in my model can't be encoded like string values and I can't find any examples of how to set all the values for a multi-column TreeView row into a single selection object. Can anyone point me to some relevant examples or docs?

You could encode your tuple of 4 values into a single string. An easy way is to use json for that:
import json
data = ["string", "string2", True, 20]
string_variable = json.dumps(data)
#
# now pass string_variable through drag and drop
#
returned = json.loads(string_variable)
You could also use your own encoding scheme if importing json is not an option for you.
Please do a careful sanity check on the data you get this way. If you don't, some specially crafted string (passed from another program, say) might crash you program or worse.

How to access a specific class instance by attribute in python?

Say I have a class Box with two attributes, self.contents and self.number. I have instances of box in a list called Boxes. Is there anyway to access/modify a specific instance by its attribute rather than iterating through Boxes? For example, if I want a box with box.number = 40 (and the list is not sorted) what would be the best way to modify its contents.

If you need to do it more frequently and you have unique numbers, then create a dictionary:
numberedBox = dict((b.number, b) for b in Boxes)
you can then access your boxes directly with numbers:
numberedBox[40]
but if you want to change their number, you will have to modify the numberedBox dictionary too...
Otherwise yes, you have to iterate over the list.

The most straightforward way is to use a list comprehension:
answer=[box for box in boxes if box.number==40]
Be warned though. This actually does iterate over the whole list. Since the list is not sorted, there is no faster method than to iterate over it (and thus do a linear search), unless you want to copy all the data into some other data structure (e.g. dict, set or sort the list).

Use the filter builtin:
wanted_boxes = filter(lambda box: box.number == 40, boxes)

Although not as flexible as using a dictionary, you might be able to get by using a simple lookup table to the map box numbers to a particular box in boxes. For example if you knew the box numbers could range 0...MAX_BOX_NUMBER, then the following would be very fast. It requires only one full scan of the Boxes list to setup the table.
MAX_BOX_NUMBER = ...
# setup lookup table
box_number = [None for i in xrange(MAX_BOX_NUMBER+1)]
for i in xrange(len(Boxes)):
box_number[Boxes[i].number] = Boxes[i]
box_number[42] # box in Boxes with given number (or None)
If the box numbers are in some other arbitrary range, some minor arithmetic would have to be applied to them before their use as indices. If the range is very large, but sparsely populated, dictionaries would be the way to go to save memory but would require more computation -- the usual trade-off.