11–20 of 124 posts
What happens if the dictionary has the keys 'John Doe' and 'John_Doe'? Can you use 'self' as a key? Ive used a class to provide this kind of dot notation fererencing of hierarchical data. If you could enclose the keys in quotes I might feel better about it but that's probably not possible.
Without looking at the code: yes. `self` in python is just convention.
I've since learned to love the distinction between object attributes and items in a mapping and happily implement ['this style'] accessors without complaint now.
That being said, if the library just did difflib.get_close_matches() on the key lookup that would be neat for some use cases where you want fuzzy keep lookup.
box.might_exist.might_exist.might_exist.desired_key
I find the bulk of my dict code is checking for keys before access, or using .get('', default) recursively. Gets really hairy for deeply nested dicts.
A single class that: * De/serializes JSON and YAML * De/mangles, de/encodes keys * Provides automatic, expensive hashcode * Blacklists/transforms a bunch of likely keys because they conflict with reserved words * Overlays attrs (__box_heritage) * All in pretty complex code that obfuscates what you're really doing (especially to a maintainer) For the ability to avoid importing json/PyYAML and use clear key lookups? Th…
I like Python a lot, and I don't write much Javascript, but one thing I wish I could do in Python is the dot notation from a dictionary. I sometimes used namedtuple as a cheap (but "immutable") class, so I can simply use dot notation when I am passing my object around my functions, instead of always stuffing the data into a dictionary.
A single class that: * De/serializes JSON and YAML * De/mangles, de/encodes keys * Provides automatic, expensive hashcode * Blacklists/transforms a bunch of likely keys because they conflict with reserved words * Overlays attrs (__box_heritage) * All in pretty complex code that obfuscates what you're really doing (especially to a maintainer) For the ability to avoid importing json/PyYAML and use clear key lookups? Th…
Why so negative here? I like Python a lot, and I don't write much Javascript, but one thing I wish I could do in Python is the dot notation from a dictionary. I sometimes used namedtuple as a cheap (but "immutable") class, so I can simply use dot notation when I am passing my object around my functions, instead of always stuffing the data into a dictionary.
For those who just want a simple a.b instead of a['b'], use this: class Obj(): def __init__(self, d): self.__dict__ = d d = Obj({ 'a': 1, 'b': 2, }) print(d.a)
Although there is this PyCon talk from 2012 advocating not to write classes if there is only one or two methods. [1]
A single class that: * De/serializes JSON and YAML * De/mangles, de/encodes keys * Provides automatic, expensive hashcode * Blacklists/transforms a bunch of likely keys because they conflict with reserved words * Overlays attrs (__box_heritage) * All in pretty complex code that obfuscates what you're really doing (especially to a maintainer) For the ability to avoid importing json/PyYAML and use clear key lookups? Th…
Why so negative here? I like Python a lot, and I don't write much Javascript, but one thing I wish I could do in Python is the dot notation from a dictionary. I sometimes used namedtuple as a cheap (but "immutable") class, so I can simply use dot notation when I am passing my object around my functions, instead of always stuffing the data into a dictionary.
Why though?
Pandas must use something similar under the hood to provide dot notation access to columns. I wish h5py did the same for hdf5 objects. In py3, I find myself needing to type list(X.items()) and then list(X['Y'].items()) and so on when I'm exploring a new dataset... fairly awkward for interactive use.
This looks really nice. I might be reading the DefaultBox docs wrong, but does it support this: box.might_exist.might_exist.might_exist.desired_key where desired_key would return a default value if one of the keys doesn't exist? I find the bulk of my dict code is checking for keys before access, or using .get('', default) recursively. Gets really hairy for deeply nested dicts.
def nget(d, *ks, **kwargs):
for k in ks:
d = d.get(k)
if d is None:
return kwargs.get('default')
return d
>>> d = {'a': {'b': {'c': 12 }}}
>>> nget(d, 'a', 'd', 'c', default='Not Found!')
'Not Found!'
>>> nget(d, 'a', 'b', 'c')
12