dsc / bunch Goto Github PK

... except if we merge !

see https://github.com/dsc/bunch/network

Maybe we should create an organization and try to consolidate our efforts

Hello,

it will be nice if Bunch could recursively build a bunch of bunch from dict of dict.

Example:

from bunch import Bunch

old_bunch = Bunch({"a": 0, "b": {"b1": 1, "b2": 2}})

returns

Bunch(a=0, b={"b1": 1, "b2": 2})

it will be nice if it could returns

new_bunch = Bunch(a=0, b=Bunch(b1=1, b2=2))

Because accessing b2 sub key can be done using:

old_bunch.b["b2"]

recursively contructed Bunch could give access to b2 sub key using:

new_bunch.b.b2

Kind regards

in setup.py line 11:

package_file = open(join(HERE, 'bunch/__init__.py'), 'rU')

"U" option for universal newline is no longer supported in python 3.11

Things look a bit strange at:

https://github.com/dsc/bunch/blob/master/bunch/__init__.py#L286-L290

I think the imports should be the other way around:

• try to import simplejson as json
• if it succeeds, you're fine
• if it fails, you'll fallback to the stdlib module json, which should be available on your Python install.

Hello,

I think it will be nice to add some tests (not with unittest package but using either nosetestsor py.test
Moreover continuous integration with Travis-CI will be a good idea
it will probably help to ensure Python 3 transition without regression on Python 2

Kind regards

Does this Bunch implementation support Python 3?

I get some test errors with Python 3.4:
https://gist.github.com/cdeil/5525c1ee193f1426ee8b

And Python 3 support is not listed via the setup.py classifiers:
https://pypi.python.org/pypi/bunch/

If it doesn't support Python 3, could you please state this in the README?

Hi @vmalloc

see this Travis build https://travis-ci.org/ig-python/ig-markets-api-python-library/jobs/83294568
(using Python 3)

    from infi.bunch import bunchify
  File "/home/travis/virtualenv/python3.3.5/lib/python3.3/site-packages/infi/bunch/__init__.py", line 31, in <module>
    from .python3_compat import *
  File "/home/travis/virtualenv/python3.3.5/lib/python3.3/site-packages/infi/bunch/python3_compat.py", line 20, in <module>
    iteritems = dict.iteritems
AttributeError: type object 'dict' has no attribute 'iteritems'

Any idea ?

I think your python3_compat.py is wrong and Python 3 is recognized as Python 2.

Kind regards

Hello,

With Python 2.7:

from bunch import Bunch
b=Bunch(foo=Bunch(lol=True), hello=42, ponies='are pretty!')
[ (k,b[k]) for k in b ]

returns

[('ponies', 'are pretty!'), ('foo', Bunch(lol=True)), ('hello', 42)]

but with Python 3.3

[ (k,b[k]) for k in b ]

returns

[('foo', Bunch(lol=True)), ('hello', 42), ('ponies', 'are pretty!')]

So some tests are failing.

Hello,

I wonder how to pretty print Bunch objects:

import pprint
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(b)

Any idea ?

I'm suspecting that the coverage for python 2 (which I use as CircuitPython) is broken. the 'if' and 'else' should be swapped:

because in Python 2, you can't say
iteritems = dict.iteritems
iterkeys = dict.iterkeys

as dict doesn't include them

Hello,

I see 2 README files

so the question is Markdown or reStructuredText ?

If you prefere Markdown you might be interested by

https://pypi.python.org/pypi/setuptools-markdown

Kind regards

It is not documented what happens if Bunch() is expanded using dictionary notation with an element, which key is invalid for property access?

I took most recent fork
https://github.com/redodo/lunch/
and fork it https://github.com/femtotrader/lunch/
to add CI

https://travis-ci.org/femtotrader/lunch

I saw this with Python 3.3:
AttributeError: 'Bunch' object attribute 'values' is read-only

Any idea ?

0.11s$ python tests/test_bunch.py

File "/home/travis/virtualenv/python3.3.5/lib/python3.3/site-packages/bunch/init.py", line 163, in bunch.Bunch.delattr
Failed example:
del b.values
Expected:
Traceback (most recent call last):
...
AttributeError: 'Bunch' object attribute 'values' is read-only
Got:
Traceback (most recent call last):
File "/opt/python/3.3.5/lib/python3.3/doctest.py", line 1313, in run
compileflags, 1), test.globs)
File "<doctest bunch.Bunch.__delattr[1]>", line 1, in
del b.values
File "/home/travis/virtualenv/python3.3.5/lib/python3.3/site-packages/bunch/init.py", line 182, in delattr
object.delattr(self, k)
AttributeError: values

1 items had failures:
1 of 4 in bunch.Bunch.delattr
_Test Failed_ 1 failures.
The command "python tests/test_bunch.py" exited with 1.

I liked AttrDict. Then AttrDict was too slow. I liked Bunch. Then Bunch was too slow. These two libraries ended up consuming 1/2 and 1/3 of my request time when using them frequently, for what I had assumed was a very simple use-case. The main problem comes from two things 1) Bunch inherits from dict, so it brings along the entire dict implementation, which isn't always necessary(rarely is in fact). 2)bunchify aggressively goes through an entire nested dictionary, and puts copies of Bunch everywhere. This results in attributes that may never get called, getting implanted with the Bunch object.

Speeding this up proved to not take a lot of code. Check out this gist from @mmerickel, which I've copied below. It uses a light-weight DictProxy object to mediate access to the object, and it also lazy-loads each attribute. This decreased the amount of time that my app spend "Bunching" objects to relatively nothing, from 1/3 of my request time using Bunch master.

class DictProxy(object):
    """
    A proxy for a dictionary that allows attribute access to underlying keys.

    You may pass a custom ``wrapper`` to override the logic for wrapping
    various custom types.

    """
    def __init__(self, obj, wrapper=wrap):
        self.obj = obj

    def __getitem__(self, key):
        return self.wrapper(self.obj[key])

    def __getattr__(self, key):
        try:
            return self.wrapper(getattr(self.obj, key))
        except AttributeError:
            try:
                return self[key]
            except KeyError:
                raise AttributeError(key)

    # you probably also want to proxy important list properties along like
    # items(), iteritems() and __len__

class ListProxy(object):
    """
    A proxy for a list that allows for wrapping items.

    You may pass a custom ``wrapper`` to override the logic for wrapping
    various custom types.

    """
    def __init__(self, obj, wrapper=wrap):
        self.obj = obj

    def __getitem__(self, key):
        return self.wrapper(self.obj[key])

    # you probably also want to proxy important list properties along like
    # __iter__ and __len__

def wrap(value):
    """
    The top-level API for wrapping an arbitrary object.

    This only works for ``dict``, ``list`` and ``tuple`` types. If you want
    to wrap other types you may write your own wrap and pass ``wrapper=`` to
    ``DictProxy`` and ``ListProxy``.

    """
    if isinstance(value, dict):
        return DictProxy(value)
    if isinstance(value, (tuple, list)):
        return ListProxy(value)
    return value

Hello,

I did this

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from flufl.enum import Enum
from bunch import Bunch

class MyEnum(Enum):
    VAL1 = 1
    VAL2 = 2
    VAL3  = 3

b = Bunch()
b.x = 1
b.e = MyEnum.VAL1

print(b)

It raises

Traceback (most recent call last):
  File "bug_bunch_enum.py", line 16, in <module>
    print(b)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/bunch/__init__.py", line 384, in toYAML
    return yaml.safe_dump(self, **opts)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/__init__.py", line 218, in safe_dump
    return dump_all([data], stream, Dumper=SafeDumper, **kwds)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/__init__.py", line 190, in dump_all
    dumper.represent(data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 28, in represent
    node = self.represent_data(data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 57, in represent_data
    node = self.yaml_representers[data_types[0]](self, data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/bunch/__init__.py", line 342, in to_yaml_safe
    return dumper.represent_dict(data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 223, in represent_dict
    return self.represent_mapping(u'tag:yaml.org,2002:map', data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 123, in represent_mapping
    node_value = self.represent_data(item_value)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 67, in represent_data
    node = self.yaml_representers[None](self, data)
  File "/Users/scls/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/yaml/representer.py", line 247, in represent_undefined
    raise RepresenterError("cannot represent an object: %s" % data)
yaml.representer.RepresenterError: cannot represent an object: MyEnum.VAL1

Any idea how to fix this ?

Kind regards

Sébastien

In the file python3_compat.py this line:

_IS_PYTHON_3 = (platform.version() >= '3')

is not a sufficient method for determing if python 3 is being used. For example on my machine this returns #86-Ubuntu SMP Mon May 4 04:32:59 UTC 2015 and I'm running python 3.4.

Ideally we should use something like 2to3, but we might be able to use sys.version.

I want to use Sourcegraph code search and code review with bunch. A project maintainer needs to enable it to set up a webhook so the code is up-to-date there.

Could you please enable bunch on @sourcegraph by going to https://sourcegraph.com/github.com/dsc/bunch and clicking on Settings? (It should only take 15 seconds.)

Thank you!

Sometimes is useful to keep parsing a large json object even when some properties are not present right now any key that's not found rises an error. My suggestion is that we could have an optional init parameter to define if we want strict rules or just returning None in case the key is not present.

My friend thanks for this amazing library , but please would be possible add support to python 3.
I think that is only change iteritems by items() , return Bunch( (k, bunchify(v)) for k,v in items(x) ) .
thanks

Test using dictionary:

>>> d={}
>>> d[u'r\xf6k']="smoke"
>>> u'r\xf6k' in d
True
>>> print repr(d)
{u'r\xf6k': 'smoke'}

Test using bunch:

>>> b=Bunch()
>>> b[u'r\xf6k']="smoke"
>>> u'r\xf6k' in b
False
>>> print repr(b)
Traceback (most recent call last):
  File "", line 1, in 
UnicodeEncodeError: 'ascii' codec can't encode character u'\xf6' in position 7: ordinal not in range(128)

If PyYAML is installed (even if unwittingly by the user), the following code crashes, for instance:

from uuid import uuid1

b = Bunch(id=uuid1())
str(b)

This breaks a lot of cases using Bunch for data container, rather than a YAML/json intermediate format...

Hello,

I try this fork of Bunch which seems interesting
https://github.com/Infinidat/munch

but Doctests don't run (never failed)

For example I changed:

    >>> [ (k,b[k]) for k in b ]
    [('ponies', 'are pretty!'), ('foo', Munch(lol=True)), ('hello', 42)]

to

    >>> [ (k,b[k]) for k in b ]
    [('ponies', 'are prettyERROR!'), ('foo', Munch(lol=True)), ('hello', 42)]

and no error raised (which is a problem as it should raise an error)