A simple tool / library for rendering a huge python dict

Question

I have a huge dict structure like this:

my_data = { 'key1': { '_': 'value1': 'aaa' }, 'key2': { '_': 'value2': 'bbb', 'key2.1': { '_': 'ccc', 'key2.1.1': { '_': 'ddd' } } 'key2.2': { '_': 'eee', 'key2.2.1': { '_': 'fff' } 'key2.2.2': { '_': 'ggg' } } } } 

etc.

I want to display it to the user as a tree view using GTK, TK, or whatever, to be able to view it, collapse and expand branches and, possibly, search keys and values.

Maybe I don’t need to develop such a tool with my hands, and is there already something that can visualize such data out of the box?

Answer 1

I finally finished converting my data to json , as @PavelAnossov suggested, and using d3 Tree Layout .

Answer 2

I don’t know the finished tool, but you can use Traits UI to quickly develop your own

 from enthought.traits.api \ import HasTraits, Instance from enthought.traits.ui.api \ import View, VGroup, Item, ValueEditor class DictEditor(HasTraits): Object = Instance( object ) def __init__(self, obj, **traits): super(DictEditor, self).__init__(**traits) self.Object = obj def trait_view(self, name=None, view_elements=None): return View( VGroup( Item( 'Object', label = 'Debug', id = 'debug', editor = ValueEditor(), style = 'custom', dock = 'horizontal', show_label = False ), ), title = 'Dictionary Editor', width = 800, height = 600, resizable = True, ) def build_sample_data(): my_data = dict(zip(range(10),range(10,20))) my_data[11] = dict(zip(range(10),range(10,20))) my_data[11][11] = dict(zip(range(10),range(10,20))) return my_data # Test if __name__ == '__main__': my_data = build_sample_data() b = DictEditor(my_data) b.configure_traits() 

What is it. You will have a graphical interface like this:

The user interface with samples uses the Model-View-Controller approach to create a graphical interface without requiring each widget to be programmatically created. Here I use the predefined ValueEditor to display arbitrary types. Now you can expand it to support search, filtering, etc.

EDIT

Simple extension to support filtering:

 # -*- coding: utf-8 -*- """ Created on Fri Feb 22 12:52:28 2013 @author: kranzth """ from enthought.traits.api \ import HasTraits, Instance, Str, on_trait_change from enthought.traits.ui.api \ import View, VGroup, Item, ValueEditor, TextEditor from copy import deepcopy class DictEditor(HasTraits): SearchTerm = Str() Object = Instance( object ) def __init__(self, obj, **traits): super(DictEditor, self).__init__(**traits) self._original_object = obj self.Object = self._filter(obj) def trait_view(self, name=None, view_elements=None): return View( VGroup( Item( 'SearchTerm', label = 'Search:', id = 'search', editor = TextEditor(), #style = 'custom', dock = 'horizontal', show_label = True ), Item( 'Object', label = 'Debug', id = 'debug', editor = ValueEditor(), style = 'custom', dock = 'horizontal', show_label = False ), ), title = 'Dictionary Editor', width = 800, height = 600, resizable = True, ) @on_trait_change("SearchTerm") def search(self): self.Object = self._filter(self._original_object, self.SearchTerm) def _filter(self, object_, search_term=None): def has_matching_leaf(obj): if isinstance(obj, list): return any( map(has_matching_leaf, obj)) if isinstance(obj, dict): return any( map(has_matching_leaf, obj.values())) else: try: if not str(obj) == search_term: return False return True except ValueError: False obj = deepcopy(object_) if search_term is None: return obj if isinstance(obj, dict): for k in obj.keys(): if not has_matching_leaf(obj[k]): del obj[k] for k in obj.keys(): if isinstance(obj, dict): obj[k] = self._filter(obj[k], search_term) elif isinstance(obj, list): filter(has_matching_leaf,obj[k]) return obj def build_sample_data(): def make_one_level_dict(): return dict(zip(range(100), range(100,150) + map(str,range(150,200)))) my_data = make_one_level_dict() my_data[11] = make_one_level_dict() my_data[11][11] = make_one_level_dict() return my_data # Test if __name__ == '__main__': my_data = build_sample_data() b = DictEditor(my_data) b.configure_traits() 

will provide you with a text box called "filter-as-you-type". The search is not entirely correct for all cases, but you can understand this idea.

Note that in this example, the data in the dict is partly integer and partly strings, and both types will be found.

Answer 3

This simple function prints a dictionary in a table format. It can also handle nested dictionaries.

 def visualise_dict(d,lvl=0): # go through the dictionary alphabetically for k in sorted(d): # print the table header if we're at the beginning if lvl == 0 and k == sorted(d)[0]: print('{:<25} {:<15} {:<10}'.format('KEY','LEVEL','TYPE')) print('-'*79) indent = ' '*lvl # indent the table to visualise hierarchy t = str(type(d[k])) # print details of each entry print("{:<25} {:<15} {:<10}".format(indent+str(k),lvl,t)) # if the entry is a dictionary if type(d[k])==dict: # visualise THAT dictionary with +1 indent visualise_dict(d[k],lvl+1) 

With a sample dictionary:

 d = {} d.update({1:{},2:{}}) d[1]['foo'] = {} d[1]['foo']['bar'] = 1 d[2]['bar'] = 5.2 visualise_dict(d) 

returns

 In [1]: visualise_dict(d) KEY LEVEL TYPE ------------------------------------------------------------------------------- 1 0 <class 'dict'> foo 1 <class 'dict'> bar 2 <class 'int'> 2 0 <class 'dict'> bar 1 <class 'float'> 

Answer 4

There are already some excellent answers here, but I think this class can be called "simple" (it uses only the python bult-in tkinter and uuid libraries).

It is based on John Gaines Jr.'s answer in another question modified by Will Ware to support lists I modified to support tuples (works on python 3).

I also reorganized it so that you could call the viewer with something as simple as tk_tree_view(data) , passing in a dictionary (as in the example at the end).

 import uuid import tkinter as tk from tkinter import ttk def j_tree(tree, parent, dic): for key in sorted(dic.keys()): uid = uuid.uuid4() if isinstance(dic[key], dict): tree.insert(parent, 'end', uid, text=key) j_tree(tree, uid, dic[key]) elif isinstance(dic[key], tuple): tree.insert(parent, 'end', uid, text=str(key) + '()') j_tree(tree, uid, dict([(i, x) for i, x in enumerate(dic[key])])) elif isinstance(dic[key], list): tree.insert(parent, 'end', uid, text=str(key) + '[]') j_tree(tree, uid, dict([(i, x) for i, x in enumerate(dic[key])])) else: value = dic[key] if isinstance(value, str): value = value.replace(' ', '_') tree.insert(parent, 'end', uid, text=key, value=value) def tk_tree_view(data): # Setup the root UI root = tk.Tk() root.title("tk_tree_view") root.columnconfigure(0, weight=1) root.rowconfigure(0, weight=1) # Setup the Frames tree_frame = ttk.Frame(root, padding="3") tree_frame.grid(row=0, column=0, sticky=tk.NSEW) # Setup the Tree tree = ttk.Treeview(tree_frame, columns=('Values')) tree.column('Values', width=100, anchor='center') tree.heading('Values', text='Values') j_tree(tree, '', data) tree.pack(fill=tk.BOTH, expand=1) # Limit windows minimum dimensions root.update_idletasks() root.minsize(root.winfo_reqwidth(), root.winfo_reqheight()) root.mainloop() if __name__ == "__main__": # Setup some test data data = { "firstName": "John", "lastName": "Smith", "gender": "male", "age": 32, "address": { "streetAddress": "21 2nd Street", "city": "New York", "state": "NY", "postalCode": "10021"}, "phoneNumbers": [ {"type": "home", "number": "212 555-1234"}, {"type": "fax", "number": "646 555-4567", "alphabet": [ "abc", "def", "ghi"] } ]} # call it with tk_tree_view(data) 

It looks like this:

Answer 5

If you are using an IDE, set a breakpoint after initializing the dictionary and the data you want to examine, then run in debug mode. There should be a “Variables” view in debug mode, where you can expand and collapse the dictionary, as you mentioned.

Answer 6

Just add @Thorsten answer. The traits package has been reorganized since ancient times. The correct way to run Thorsten code is:

• install feature module: sudo apt-get install python-traitsui

• change the import lines of the module in its code to:

   from traits.api \ import HasTraits, Instance, Str, on_trait_change from traitsui.api \ import View, VGroup, Item, ValueEditor, TextEditor 

Answer 7

If you use a browser with the JSONViewer extension, this may work for you:

 import json import tempfile import os import subprocess def view_obj(obj): (f, filepath)= tempfile.mkstemp() os.close(f) with open(filepath, 'w') as f: json.dump(obj, f) subprocess.call(["google-chrome", filepath]) view_obj({'key':'value'}) # Opens Chrome and renders JSON nicely