Python 2.7 create a dictionary from dotted values [duplicate] - python-2.7

I'm trying to programmatically set a value in a dictionary, potentially nested, given a list of indices and a value.
So for example, let's say my list of indices is:
['person', 'address', 'city']
and the value is
'New York'
I want as a result a dictionary object like:
{ 'Person': { 'address': { 'city': 'New York' } }
Basically, the list represents a 'path' into a nested dictionary.
I think I can construct the dictionary itself, but where I'm stumbling is how to set the value. Obviously if I was just writing code for this manually it would be:
dict['Person']['address']['city'] = 'New York'
But how do I index into the dictionary and set the value like that programmatically if I just have a list of the indices and the value?
Python

Something like this could help:
def nested_set(dic, keys, value):
for key in keys[:-1]:
dic = dic.setdefault(key, {})
dic[keys[-1]] = value
And you can use it like this:
>>> d = {}
>>> nested_set(d, ['person', 'address', 'city'], 'New York')
>>> d
{'person': {'address': {'city': 'New York'}}}

I took the freedom to extend the code from the answer of Bakuriu. Therefore upvotes on this are optional, as his code is in and of itself a witty solution, which I wouldn't have thought of.
def nested_set(dic, keys, value, create_missing=True):
d = dic
for key in keys[:-1]:
if key in d:
d = d[key]
elif create_missing:
d = d.setdefault(key, {})
else:
return dic
if keys[-1] in d or create_missing:
d[keys[-1]] = value
return dic
When setting create_missing to True, you're making sure to only set already existing values:
# Trying to set a value of a nonexistent key DOES NOT create a new value
print(nested_set({"A": {"B": 1}}, ["A", "8"], 2, False))
>>> {'A': {'B': 1}}
# Trying to set a value of an existent key DOES create a new value
print(nested_set({"A": {"B": 1}}, ["A", "8"], 2, True))
>>> {'A': {'B': 1, '8': 2}}
# Set the value of an existing key
print(nested_set({"A": {"B": 1}}, ["A", "B"], 2))
>>> {'A': {'B': 2}}

Here's another option:
from collections import defaultdict
recursivedict = lambda: defaultdict(recursivedict)
mydict = recursivedict()
I originally got this from here: Set nested dict value and create intermediate keys.
It is quite clever and elegant if you ask me.

First off, you probably want to look at setdefault.
As a function I'd write it as
def get_leaf_dict(dct, key_list):
res=dct
for key in key_list:
res=res.setdefault(key, {})
return res
This would be used as:
get_leaf_dict( dict, ['Person', 'address', 'city']) = 'New York'
This could be cleaned up with error handling and such. Also using *args rather than a single key-list argument might be nice; but the idea is that
you can iterate over the keys, pulling up the appropriate dictionary at each level.

Here is my simple solution: just write
terms = ['person', 'address', 'city']
result = nested_dict(3, str)
result[terms] = 'New York' # as easy as it can be
You can even do:
terms = ['John', 'Tinkoff', '1094535332'] # account in Tinkoff Bank
result = nested_dict(3, float)
result[terms] += 2375.30
Now the backstage:
from collections import defaultdict
class nesteddict(defaultdict):
def __getitem__(self, key):
if isinstance(key, list):
d = self
for i in key:
d = defaultdict.__getitem__(d, i)
return d
else:
return defaultdict.__getitem__(self, key)
def __setitem__(self, key, value):
if isinstance(key, list):
d = self[key[:-1]]
defaultdict.__setitem__(d, key[-1], value)
else:
defaultdict.__setitem__(self, key, value)
def nested_dict(n, type):
if n == 1:
return nesteddict(type)
else:
return nesteddict(lambda: nested_dict(n-1, type))

The dotty_dict library for Python 3 can do this. See documentation, Dotty Dict for more clarity.
from dotty_dict import dotty
dot = dotty()
string = '.'.join(['person', 'address', 'city'])
dot[string] = 'New York'
print(dot)
Output:
{'person': {'address': {'city': 'New York'}}}

Use these pair of methods
def gattr(d, *attrs):
"""
This method receives a dict and list of attributes to return the innermost value of the give dict
"""
try:
for at in attrs:
d = d[at]
return d
except:
return None
def sattr(d, *attrs):
"""
Adds "val" to dict in the hierarchy mentioned via *attrs
For ex:
sattr(animals, "cat", "leg","fingers", 4) is equivalent to animals["cat"]["leg"]["fingers"]=4
This method creates necessary objects until it reaches the final depth
This behaviour is also known as autovivification and plenty of implementation are around
This implementation addresses the corner case of replacing existing primitives
https://gist.github.com/hrldcpr/2012250#gistcomment-1779319
"""
for attr in attrs[:-2]:
# If such key is not found or the value is primitive supply an empty dict
if d.get(attr) is None or isinstance(d.get(attr), dict):
d[attr] = {}
d = d[attr]
d[attrs[-2]] = attrs[-1]

Here's a variant of Bakuriu's answer that doesn't rely on a separate function:
keys = ['Person', 'address', 'city']
value = 'New York'
nested_dict = {}
# Build nested dictionary up until 2nd to last key
# (Effectively nested_dict['Person']['address'] = {})
sub_dict = nested_dict
for key_ind, key in enumerate(keys[:-1]):
if not key_ind:
# Point to newly added piece of dictionary
sub_dict = nested_dict.setdefault(key, {})
else:
# Point to newly added piece of sub-dictionary
# that is also added to original dictionary
sub_dict = sub_dict.setdefault(key, {})
# Add value to last key of nested structure of keys
# (Effectively nested_dict['Person']['address']['city'] = value)
sub_dict[keys[-1]] = value
print(nested_dict)
>>> {'Person': {'address': {'city': 'New York'}}}

This is a pretty good use case for a recursive function. So you can do something like this:
def parse(l: list, v: str) -> dict:
copy = dict()
k, *s = l
if len(s) > 0:
copy[k] = parse(s, v)
else:
copy[k] = v
return copy
This effectively pops off the first value of the passed list l as a key for the dict copy that we initialize, then runs the remaining list through the same function, creating a new key under that key until there's nothing left in the list, whereupon it assigns the last value to the v param.

This is much easier in Perl:
my %hash;
$hash{"aaa"}{"bbb"}{"ccc"}=1; # auto creates each of the intermediate levels
# of the hash (aka: dict or associated array)

Related

Django: Filter & function

I have currently these to utils functions.
The only difference between unique_account_link_generator and unique_order_id is what they filter within qs_exists. It's either .filter(slug=new_id) or .filter(order_id=new_id)
I now wonder is there a way to combine them and then being able to define the filter method when I call the function: unique_id_generator(instance, _filter = "order_id")
import random
import string
def random_string_generator(size=10, chars=string.ascii_lowercase + string.digits):
return ''.join(random.choice(chars) for _ in range(size))
def unique_account_link_generator(instance):
"""
1. Generates random string
2. Check if string unique in database
3. If already exists, generate new string
"""
new_id = random_string_generator()
myClass = instance.__class__
qs_exists = myClass.objects.filter(slug=new_id).exists()
if qs_exists:
return unique_account_link_generator(instance)
return new_id
# How to send field_name via function?
def unique_id_generator(instance):
"""
1. Generates random string
2. Check if string unique in database
3. If already exists, generate new string
"""
new_id = random_string_generator()
myClass = instance.__class__
qs_exists = myClass.objects.filter(order_id=new_id).exists()
if qs_exists:
return unique_id_generator(instance)
return new_id
Not sure I understood the question, as the answer is very simple:
def unique_id_generator(instance, _filter="order_id"):
new_id = random_string_generator()
myClass = instance.__class__
qs_exists = myClass.objects.filter(**{_filter:new_id}).exists()
if qs_exists:
return unique_id_generator(instance, _filter)
return new_id
I want to give you an answer to your question in the comments. Since the comment section doesn't allow much text I would like to attach this as an addition to the accepted answer.
It's actually correct that **{_filter:new_id} will unpack what's inside the _filter parameter
If you call the function with (instance, _filter="order_id")
this part **{_filter:new_id} will look like this **{"order_id":"randomGeneratedCode123"}
Now you have a dictionary with the key "order_id" and the value "randomGeneratedCode123"
You goal is to transform the key "order_id" to a parameter name and the value of the "order_id" key to the value of the parameter order_id
order_id = "randomGeneratedCode123"
As you already said you can unpack a dictionary with the double stars **
After unpacking it, the keys in the dictionary will be your parameter names and the values of the keys the parameter values
Here is a small example for better understanding:
Let's say you have a dictionary and a function
dict = {'a': 1, 'b': 2}
def example(a, b):
print("Variable a is {}, b is {}".format(a, b))
example(**dict)
**dict is converted to:
a = 1, b = 2 so the function will be called with
example(a = 1, b = 2)
It's important that the keys in your dictionary have the same name as your function parameter names
So this wouldn't work:
dict = {'a': 1, 'c': 2}
example(**dict)
because it's "translated " as
example(a = 1, c = 2)
and the function doesn't have a parameter with the name c

Turning weekly to monthly data in Python dictionary

I'm trying to turn this dictionary:
dic = {'2007-10-21': '53', '2007-10-28': '50', '2007-11-05': '100','2007-11-06': '99'}
Into something like this:
dic = {'2007-10': '103', '2007-11': '199'}
Since I need to do that in scale, pythonly speaking I need to sum all the values which its keys start with the same 7 characters.
Try this,
__author__ = 'Fawzan'
dic = {'2007-10-21': '53', '2007-10-28': '50', '2007-11-05': '100', '2007-11-06': '99'}
# create a new dictionary
newDic = {}
# iterate the old dictionary
for key in dic:
# get the desiresd string for comparision
k = key[0:7]
# for debug
print(k)
# if the key is already in the new dictionary, then add the value to existing key
if (k in newDic):
newDic[k] += float(dic[key])
# else append the key, value
else:
newDic[k] = float(dic[key])
# print and check the answer :)
print(newDic)

How do I put docstrings on Enums?

Python 3.4 has a new enum module and Enum data type. If you are unable to switch to 3.4 yet, Enum has been backported.
Since Enum members support docstrings, as pretty much all python objects do, I would like to set them. Is there an easy way to do that?
Yes there is, and it's my favorite recipe so far. As a bonus, one does not have to specify the integer value either. Here's an example:
class AddressSegment(AutoEnum):
misc = "not currently tracked"
ordinal = "N S E W NE NW SE SW"
secondary = "apt bldg floor etc"
street = "st ave blvd etc"
You might ask why I don't just have "N S E W NE NW SE SW" be the value of ordinal? Because when I get its repr seeing <AddressSegment.ordinal: 'N S E W NE NW SE SW'> gets a bit clunky, but having that information readily available in the docstring is a good compromise.
Here's the recipe for the Enum:
class AutoEnum(enum.Enum):
"""
Automatically numbers enum members starting from 1.
Includes support for a custom docstring per member.
"""
#
def __new__(cls, *args):
"""Ignores arguments (will be handled in __init__."""
value = len(cls) + 1
obj = object.__new__(cls)
obj._value_ = value
return obj
#
def __init__(self, *args):
"""Can handle 0 or 1 argument; more requires a custom __init__.
0 = auto-number w/o docstring
1 = auto-number w/ docstring
2+ = needs custom __init__
"""
if len(args) == 1 and isinstance(args[0], (str, unicode)):
self.__doc__ = args[0]
elif args:
raise TypeError('%s not dealt with -- need custom __init__' % (args,))
And in use:
>>> list(AddressSegment)
[<AddressSegment.ordinal: 1>, <AddressSegment.secondary: 2>, <AddressSegment.misc: 3>, <AddressSegment.street: 4>]
>>> AddressSegment.secondary
<AddressSegment.secondary: 2>
>>> AddressSegment.secondary.__doc__
'apt bldg floor etc'
The reason I handle the arguments in __init__ instead of in __new__ is to make subclassing AutoEnum easier should I want to extend it further.
Anyone arriving here as a google search:
For many IDE's now in 2022, the following will populate intellisense:
class MyEnum(Enum):
"""
MyEnum purpose and general doc string
"""
VALUE = "Value"
"""
This is the Value selection. Use this for Values
"""
BUILD = "Build"
"""
This is the Build selection. Use this for Buildings
"""
Example in VSCode:
This does not directly answer the question, but I wanted to add a more robust version of #Ethan Furman's AutoEnum class which uses the auto enum function.
The implementation below works with Pydantic and does fuzzy-matching of values to the corresponding enum type.
Usage:
In [2]: class Weekday(AutoEnum): ## Assume AutoEnum class has been defined.
...: Monday = auto()
...: Tuesday = auto()
...: Wednesday = auto()
...: Thursday = auto()
...: Friday = auto()
...: Saturday = auto()
...: Sunday = auto()
...:
In [3]: Weekday('MONDAY') ## Fuzzy matching: case-insensitive
Out[3]: Monday
In [4]: Weekday(' MO NDAY') ## Fuzzy matching: ignores extra spaces
Out[4]: Monday
In [5]: Weekday('_M_onDa y') ## Fuzzy matching: ignores underscores
Out[5]: Monday
In [6]: %timeit Weekday('_M_onDay') ## Fuzzy matching takes ~1 microsecond.
1.15 µs ± 10.9 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)
In [7]: %timeit Weekday.from_str('_M_onDay') ## You can further speedup matching using from_str (this is because _missing_ is not called)
736 ns ± 8.89 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)
In [8]: list(Weekday) ## Get all the enums
Out[8]: [Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]
In [9]: Weekday.Monday.matches('Tuesday') ## Check if a string matches a particular enum value
Out[9]: False
In [10]: Weekday.matches_any('__TUESDAY__') ## Check if a string matches any enum
Out[10]: True
In [11]: Weekday.Tuesday is Weekday(' Tuesday') and Weekday.Tuesday == Weekday('_Tuesday_') ## `is` and `==` work as expected
Out[11]: True
In [12]: Weekday.Tuesday == 'Tuesday' ## Strings don't match enum values, because strings aren't enums!
Out[12]: False
In [13]: Weekday.convert_keys({ ## Convert matching dict keys to an enum. Similar: .convert_list, .convert_set
'monday': 'alice',
'tuesday': 'bob',
'not_wednesday': 'charles',
'THURSDAY ': 'denise',
})
Out[13]:
{Monday: 'alice',
Tuesday: 'bob',
'not_wednesday': 'charles',
Thursday: 'denise'}
The code for AutoEnum can be found below.
If you want to change the fuzzy-matching logic, then override the classmethod _normalize (e.g. returning the input unchanged in _normalize, will perform exact matching).
from typing import *
from enum import Enum, auto
class AutoEnum(str, Enum):
"""
Utility class which can be subclassed to create enums using auto().
Also provides utility methods for common enum operations.
"""
#classmethod
def _missing_(cls, enum_value: Any):
## Ref: https://stackoverflow.com/a/60174274/4900327
## This is needed to allow Pydantic to perform case-insensitive conversion to AutoEnum.
return cls.from_str(enum_value=enum_value, raise_error=True)
def _generate_next_value_(name, start, count, last_values):
return name
#property
def str(self) -> str:
return self.__str__()
def __repr__(self):
return self.__str__()
def __str__(self):
return self.name
def __hash__(self):
return hash(self.__class__.__name__ + '.' + self.name)
def __eq__(self, other):
return self is other
def __ne__(self, other):
return self is not other
def matches(self, enum_value: str) -> bool:
return self is self.from_str(enum_value, raise_error=False)
#classmethod
def matches_any(cls, enum_value: str) -> bool:
return cls.from_str(enum_value, raise_error=False) is not None
#classmethod
def does_not_match_any(cls, enum_value: str) -> bool:
return not cls.matches_any(enum_value)
#classmethod
def _initialize_lookup(cls):
if '_value2member_map_normalized_' not in cls.__dict__: ## Caching values for fast retrieval.
cls._value2member_map_normalized_ = {}
for e in list(cls):
normalized_e_name: str = cls._normalize(e.value)
if normalized_e_name in cls._value2member_map_normalized_:
raise ValueError(
f'Cannot register enum "{e.value}"; '
f'another enum with the same normalized name "{normalized_e_name}" already exists.'
)
cls._value2member_map_normalized_[normalized_e_name] = e
#classmethod
def from_str(cls, enum_value: str, raise_error: bool = True) -> Optional:
"""
Performs a case-insensitive lookup of the enum value string among the members of the current AutoEnum subclass.
:param enum_value: enum value string
:param raise_error: whether to raise an error if the string is not found in the enum
:return: an enum value which matches the string
:raises: ValueError if raise_error is True and no enum value matches the string
"""
if isinstance(enum_value, cls):
return enum_value
if enum_value is None and raise_error is False:
return None
if not isinstance(enum_value, str) and raise_error is True:
raise ValueError(f'Input should be a string; found type {type(enum_value)}')
cls._initialize_lookup()
enum_obj: Optional[AutoEnum] = cls._value2member_map_normalized_.get(cls._normalize(enum_value))
if enum_obj is None and raise_error is True:
raise ValueError(f'Could not find enum with value {enum_value}; available values are: {list(cls)}.')
return enum_obj
#classmethod
def _normalize(cls, x: str) -> str:
## Found to be faster than .translate() and re.sub() on Python 3.10.6
return str(x).replace(' ', '').replace('-', '').replace('_', '').lower()
#classmethod
def convert_keys(cls, d: Dict) -> Dict:
"""
Converts string dict keys to the matching members of the current AutoEnum subclass.
Leaves non-string keys untouched.
:param d: dict to transform
:return: dict with matching string keys transformed to enum values
"""
out_dict = {}
for k, v in d.items():
if isinstance(k, str) and cls.from_str(k, raise_error=False) is not None:
out_dict[cls.from_str(k, raise_error=False)] = v
else:
out_dict[k] = v
return out_dict
#classmethod
def convert_keys_to_str(cls, d: Dict) -> Dict:
"""
Converts dict keys of the current AutoEnum subclass to the matching string key.
Leaves other keys untouched.
:param d: dict to transform
:return: dict with matching keys of the current AutoEnum transformed to strings.
"""
out_dict = {}
for k, v in d.items():
if isinstance(k, cls):
out_dict[str(k)] = v
else:
out_dict[k] = v
return out_dict
#classmethod
def convert_values(
cls,
d: Union[Dict, Set, List, Tuple],
raise_error: bool = False
) -> Union[Dict, Set, List, Tuple]:
"""
Converts string values to the matching members of the current AutoEnum subclass.
Leaves non-string values untouched.
:param d: dict, set, list or tuple to transform.
:param raise_error: raise an error if unsupported type.
:return: data structure with matching string values transformed to enum values.
"""
if isinstance(d, dict):
return cls.convert_dict_values(d)
if isinstance(d, list):
return cls.convert_list(d)
if isinstance(d, tuple):
return tuple(cls.convert_list(d))
if isinstance(d, set):
return cls.convert_set(d)
if raise_error:
raise ValueError(f'Unrecognized data structure of type {type(d)}')
return d
#classmethod
def convert_dict_values(cls, d: Dict) -> Dict:
"""
Converts string dict values to the matching members of the current AutoEnum subclass.
Leaves non-string values untouched.
:param d: dict to transform
:return: dict with matching string values transformed to enum values
"""
out_dict = {}
for k, v in d.items():
if isinstance(v, str) and cls.from_str(v, raise_error=False) is not None:
out_dict[k] = cls.from_str(v, raise_error=False)
else:
out_dict[k] = v
return out_dict
#classmethod
def convert_list(cls, l: List) -> List:
"""
Converts string list itmes to the matching members of the current AutoEnum subclass.
Leaves non-string items untouched.
:param l: list to transform
:return: list with matching string items transformed to enum values
"""
out_list = []
for item in l:
if isinstance(item, str) and cls.matches_any(item):
out_list.append(cls.from_str(item))
else:
out_list.append(item)
return out_list
#classmethod
def convert_set(cls, s: Set) -> Set:
"""
Converts string list itmes to the matching members of the current AutoEnum subclass.
Leaves non-string items untouched.
:param s: set to transform
:return: set with matching string items transformed to enum values
"""
out_set = set()
for item in s:
if isinstance(item, str) and cls.matches_any(item):
out_set.add(cls.from_str(item))
else:
out_set.add(item)
return out_set
#classmethod
def convert_values_to_str(cls, d: Dict) -> Dict:
"""
Converts dict values of the current AutoEnum subclass to the matching string value.
Leaves other values untouched.
:param d: dict to transform
:return: dict with matching values of the current AutoEnum transformed to strings.
"""
out_dict = {}
for k, v in d.items():
if isinstance(v, cls):
out_dict[k] = str(v)
else:
out_dict[k] = v
return out_dict
Functions and classes have docstrings, but most objects don't and do not even need them at all. There is no native docstring syntax for instance attributes, as they can be described exhaustively in the classes' docstring, which is also what I recommend you to do. Instances of classes normally also don't have their own docstrings, and enum members are nothing more than that.
Sure enough you could add a docstring to almost anything. Actually you can, indeed, add anything to almost anything, as this is the way python was designed. But it is neither useful nor clean, and even what #Ethan Furman posted seems like way to much overhead just for adding a docstring to a static property.
Long story short, even though you might not like it at first:
Just don't do it and go with your enum's docstring. It is more than enough to explain the meaning of its members.

Getting next and previous objects in Django

I'm trying to get the next and previous objects of a comic book issue. Simply changing the id number or filtering through date added is not going to work because I don't add the issues sequentially.
This is how my views are setup and it WORKS for prev_issue and does return the previous object, but it returns the last object for next_issue and I do not know why.
def issue(request, issue_id):
issue = get_object_or_404(Issue, pk=issue_id)
title = Title.objects.filter(issue=issue)
prev_issue = Issue.objects.filter(title=title).filter(number__lt=issue.number)[0:1]
next_issue = Issue.objects.filter(title=title).filter(number__gt=issue.number)[0:1]
Add an order_by clause to ensure it orders by number.
next_issue = Issue.objects.filter(title=title, number__gt=issue.number).order_by('number').first()
I know this is a bit late, but for anyone else, django does have a nicer way to do this, see https://docs.djangoproject.com/en/1.7/ref/models/instances/#django.db.models.Model.get_previous_by_FOO
So the answer here would be something something like
next_issue = Issue.get_next_by_number(issue, title=title)
Django managers to do that with a bit of meta class cleaverness.
If it's required to find next and previous objects ordered by field values that can be equal and those fields are not of Date* type, the query gets slightly complex, because:
ordering on objects with same values limiting by [:1] will always produce same result for several objects;
object can itself be included in resulting set.
Here's are querysets that also take into account the primary keys to produce a correct result (assuming that number parameter from OP is not unique and omitting the title parameter as it's irrelevant for the example):
Previous:
prev_issue = (Issue.objects
.filter(number__lte=issue.number, id__lt=instance.id)
.exclude(id=issue.id)
.order_by('-number', '-id')
.first())
Next:
next_issue = (Issue.objects
.filter(number__gte=issue.number, id__gt=instance.id)
.exclude(id=issue.id)
.order_by('number', 'id')
.first())
from functools import partial, reduce
from django.db import models
def next_or_prev_instance(instance, qs=None, prev=False, loop=False):
if not qs:
qs = instance.__class__.objects.all()
if prev:
qs = qs.reverse()
lookup = 'lt'
else:
lookup = 'gt'
q_list = []
prev_fields = []
if qs.query.extra_order_by:
ordering = qs.query.extra_order_by
elif qs.query.order_by:
ordering = qs.query.order_by
elif qs.query.get_meta().ordering:
ordering = qs.query.get_meta().ordering
else:
ordering = []
ordering = list(ordering)
if 'pk' not in ordering and '-pk' not in ordering:
ordering.append('pk')
qs = qs.order_by(*ordering)
for field in ordering:
if field[0] == '-':
this_lookup = (lookup == 'gt' and 'lt' or 'gt')
field = field[1:]
else:
this_lookup = lookup
q_kwargs = dict([(f, get_model_attr(instance, f))
for f in prev_fields])
key = "%s__%s" % (field, this_lookup)
q_kwargs[key] = get_model_attr(instance, field)
q_list.append(models.Q(**q_kwargs))
prev_fields.append(field)
try:
return qs.filter(reduce(models.Q.__or__, q_list))[0]
except IndexError:
length = qs.count()
if loop and length > 1:
return qs[0]
return None
next_instance = partial(next_or_prev_instance, prev=False)
prev_instance = partial(next_or_prev_instance, prev=True)
note that do not use object.get(pk=object.pk + 1) these sorts of things, IntegrityError occurs if object at that pk is deleted, hence always use a query set
for visitors:
''' Useage '''
"""
# Declare our item
store = Store.objects.get(pk=pk)
# Define our models
stores = Store.objects.all()
# Ask for the next item
new_store = get_next_or_prev(stores, store, 'next')
# If there is a next item
if new_store:
# Replace our item with the next one
store = new_store
"""
''' Function '''
def get_next_or_prev(models, item, direction):
'''
Returns the next or previous item of
a query-set for 'item'.
'models' is a query-set containing all
items of which 'item' is a part of.
direction is 'next' or 'prev'
'''
getit = False
if direction == 'prev':
models = models.reverse()
for m in models:
if getit:
return m
if item == m:
getit = True
if getit:
# This would happen when the last
# item made getit True
return models[0]
return False
original author
Usage
# you MUST call order by to pass in an order, otherwise QuerySet.reverse will not work
qs = Model.objects.all().order_by('pk')
q = qs[0]
prev = get_next_or_prev(qs, q, 'prev')
next = get_next_or_prev(qs, q, 'next')
next_obj_id = int(current_obj_id) + 1
next_obj = Model.objects.filter(id=next_obj_id).first()
prev_obj_id= int(current_obj_id) - 1
prev_obj = Model.objects.filter(id=prev_obj_id).first()
#You have nothing to loose here... This works for me

Django: Generating a queryset from a GET request

I have a Django form setup using GET method. Each value corresponds to attributes of a Django model. What would be the most elegant way to generate the query? Currently this is what I do in the view:
def search_items(request):
if 'search_name' in request.GET:
query_attributes = {}
query_attributes['color'] = request.GET.get('color', '')
if not query_attributes['color']: del query_attributes['color']
query_attributes['shape'] = request.GET.get('shape', '')
if not query_attributes['shape']: del query_attributes['shape']
items = Items.objects.filter(**query_attributes)
But I'm pretty sure there's a better way to go about it.
You could do it with a list comp and and "interested params" set:
def search_items(request):
if 'search_name' in request.GET:
interested_params = ('color', 'shape')
query_attrs = dict([(param, val) for param, val in request.GET.iteritems()
if param in interested_params and val])
items = Items.objects.filter(**query_attrs)
Just for fun (aka don't actually do this) you could do it in one line:
def search_items(request):
items = Items.objects.filter(
**dict([(param, val) for param, val in request.GET.iteritems()
if param in ('color', 'shape') and val])
) if 'search_name' in request.GET else None
well, the basic way you are approaching the problem seems sound, but the way you wrote it out looks a little funny. I'd probably do it this way:
def search_items(request):
if 'search_name' in request.GET:
query_attributes = {}
color = request.GET.get('color', '')
if color:
query_attributes['color'] = color
shape = request.GET.get('shape', '')
if shape:
query_attributes['shape'] = shape
items = Items.objects.filter(**query_attributes)
If you want it to be fully dynamic, you can use a little bit of model introspection to find out what fields you can actually query, and filter only using those.
Though, this solution won't allow you to use __lookups in GET parameters, don't know if you need it.
def search_items(request):
if 'search_name' in request.GET:
all_fields = Items._meta.get_all_field_names()
filters = [(k, v) for k, v in request.GET.items() if k in all_fields]
items = Items.objects.filter(*filters)
def search_items(request):
try:
items = Items.objects.filter(**dict([
(F, request.GET[F]) for F in ('color', 'shape')
]))
except KeyError:
raise Http404
Suppose 'color' and 'shape' are required GET params. Predefined tuple of filtering params is prefered because of security reasons.