python-benedict is a dict subclass with keylist/keypath support, I/O shortcuts (base64, csv, json, pickle, plist, query-string, toml, xml, yaml) and many utilities... for humans, obviously.
Project description
python-benedict
python-benedict is a dict subclass with keylist/keypath support, I/O shortcuts (base64
, csv
, json
, pickle
, plist
, query-string
, toml
, xml
, yaml
.) and many utilities... for humans, obviously.
Features
- 100% backward-compatible, you can safely wrap existing dictionaries.
- Keylist support using list of keys as key.
- Keypath support using keypath-separator (dot syntax by default).
- Keypath list-index support (also negative) using the standard
[n]
suffix. - Easy I/O operations with most common formats:
base64
,csv
,json
,pickle
,plist
,query-string
,toml
,xml
,yaml
. - Many utility and parse methods to retrieve data as needed (check the API section).
- Well tested. ;)
Index
Installation
- Run
pip install python-benedict
Usage
Basics
benedict
is a dict
subclass, so it is possible to use it as a normal dictionary (you can just cast an existing dict).
from benedict import benedict
# create a new empty instance
d = benedict()
# or cast an existing dict
d = benedict(existing_dict)
# or create from data source (filepath, url or data-string) in a supported format:
# Base64, CSV, JSON, TOML, XML, YAML, query-string
d = benedict('https://localhost:8000/data.json', format='json')
# or in a Django view
params = benedict(request.GET.items())
page = params.get_int('page', 1)
Keylist
Wherever a key is used, it is possible to use also a list (or a tuple) of keys.
d = benedict()
# set values by keys list
d['profile', 'firstname'] = 'Fabio'
d['profile', 'lastname'] = 'Caccamo'
print(d) # -> { 'profile':{ 'firstname':'Fabio', 'lastname':'Caccamo' } }
print(d['profile']) # -> { 'firstname':'Fabio', 'lastname':'Caccamo' }
# check if keypath exists in dict
print(['profile', 'lastname'] in d) # -> True
# delete value by keys list
del d['profile', 'lastname']
print(d['profile']) # -> { 'firstname':'Fabio' }
Keypath
.
is the default keypath separator.
If you cast an existing dict and its keys contain the keypath separator a ValueError
will be raised.
In this case you should use a custom keypath separator or disable keypath functionality.
d = benedict()
# set values by keypath
d['profile.firstname'] = 'Fabio'
d['profile.lastname'] = 'Caccamo'
print(d) # -> { 'profile':{ 'firstname':'Fabio', 'lastname':'Caccamo' } }
print(d['profile']) # -> { 'firstname':'Fabio', 'lastname':'Caccamo' }
# check if keypath exists in dict
print('profile.lastname' in d) # -> True
# delete value by keypath
del d['profile.lastname']
Custom keypath separator
You can customize the keypath separator passing the keypath_separator
argument in the constructor.
If you pass an existing dict to the constructor and its keys contain the keypath separator an Exception
will be raised.
d = benedict(existing_dict, keypath_separator='/')
Change keypath separator
You can change the keypath_separator
at any time using the getter/setter
property.
If any existing key contains the new keypath_separator
an Exception
will be raised.
d.keypath_separator = '/'
Disable keypath functionality
You can disable the keypath functionality passing keypath_separator=None
in the constructor.
d = benedict(existing_dict, keypath_separator=None)
You can disable the keypath functionality using the getter/setter
property.
d.keypath_separator = None
List index support
List index are supported, keypaths can include indexes (also negative) using [n]
, to perform any operation very fast:
# Eg. get last location cordinates of the first result:
loc = d['results[0].locations[-1].coordinates']
lat = loc.get_decimal('latitude')
lng = loc.get_decimal('longitude')
API
-
Utility methods
-
I/O methods
-
Parse methods
Utility methods
These methods are common utilities that will speed up your everyday work.
Utilities that accept key argument(s) also support keypath(s).
Utilities that return a dictionary always return a new benedict
instance.
-
clean
# Clean the current dict instance removing all empty values: None, '', {}, [], ().
# If strings or collections (dict, list, set, tuple) flags are False,
# related empty values will not be deleted.
d.clean(strings=True, collections=True)
-
clone
# Return a clone (deepcopy) of the dict.
c = d.clone()
-
dump
# Return a readable representation of any dict/list.
# This method can be used both as static method or instance method.
s = benedict.dump(d.keypaths())
print(s)
# or
d = benedict()
print(d.dump())
-
filter
# Return a filtered dict using the given predicate function.
# Predicate function receives key, value arguments and should return a bool value.
predicate = lambda k, v: v is not None
f = d.filter(predicate)
-
find
# Return the first match searching for the given keys/keypaths.
# If no result found, default value is returned.
keys = ['a.b.c', 'm.n.o', 'x.y.z']
f = d.find(keys, default=0)
-
flatten
# Return a new flattened dict using the given separator to join nested dict keys to flatten keypaths.
f = d.flatten(separator='_')
-
groupby
# Group a list of dicts at key by the value of the given by_key and return a new dict.
g = d.groupby('cities', by_key='country_code')
-
invert
# Return an inverted dict where values become keys and keys become values.
# Since multiple keys could have the same value, each value will be a list of keys.
# If flat is True each value will be a single value (use this only if values are unique).
i = d.invert(flat=False)
-
items_sorted_by_keys
# Return items (key/value list) sorted by keys.
# If reverse is True, the list will be reversed.
items = d.items_sorted_by_keys(reverse=False)
-
items_sorted_by_values
# Return items (key/value list) sorted by values.
# If reverse is True, the list will be reversed.
items = d.items_sorted_by_values(reverse=False)
-
keypaths
# Return a list of all keypaths in the dict.
# If indexes is True, the output will include list values indexes.
k = d.keypaths(indexes=False)
-
match
# Return a list of all values whose keypath matches the given pattern (a regex or string).
# If pattern is string, wildcard can be used (eg. [*] can be used to match all list indexes).
# If indexes is True, the pattern will be matched also against list values.
m = d.match(pattern, indexes=True)
-
merge
# Merge one or more dictionary objects into current instance (deepupdate).
# Sub-dictionaries keys will be merged toghether.
# If overwrite is False, existing values will not be overwritten.
# If concat is True, list values will be concatenated toghether.
d.merge(a, b, c, overwrite=True, concat=False)
-
move
# Move an item from key_src to key_dst.
# It can be used to rename a key.
# If key_dst exists, its value will be overwritten.
d.move('a', 'b', overwrite=True)
-
nest
# Nest a list of dicts at the given key and return a new nested list
# using the specified keys to establish the correct items hierarchy.
d.nest('values', id_key='id', parent_id_key='parent_id', children_key='children')
-
remove
# Remove multiple keys from the dict.
# It is possible to pass a single key or more keys (as list or *args).
d.remove(['firstname', 'lastname', 'email'])
-
rename
# Rename a dict item key from 'key' to 'key_new'.
# If key_new exists, a KeyError will be raised.
d.rename('first_name', 'firstname')
-
search
# Search and return a list of items (dict, key, value, ) matching the given query.
r = d.search('hello', in_keys=True, in_values=True, exact=False, case_sensitive=False)
-
standardize
# Standardize all dict keys, e.g. "Location Latitude" -> "location_latitude".
d.standardize()
-
subset
# Return a dict subset for the given keys.
# It is possible to pass a single key or more keys (as list or *args).
s = d.subset(['firstname', 'lastname', 'email'])
-
swap
# Swap items values at the given keys.
d.swap('firstname', 'lastname')
-
traverse
# Traverse a dict passing each item (dict, key, value) to the given callback function.
def f(d, key, value):
print('dict: {} - key: {} - value: {}'.format(d, key, value))
d.traverse(f)
-
unflatten
# Return a new unflattened dict using the given separator to split dict keys to nested keypaths.
u = d.unflatten(separator='_')
-
unique
# Remove duplicated values from the dict.
d.unique()
I/O methods
It is possible to create a benedict
instance directly from data source (filepath, url or data-string) by passing the data source and the data format (default 'json') in the constructor.
# filepath
d = benedict('/root/data.yml', format='yaml')
# url
d = benedict('https://localhost:8000/data.xml', format='xml')
# data-string
d = benedict('{"a": 1, "b": 2, "c": 3, "x": 7, "y": 8, "z": 9}')
These methods simplify I/O operations with most common formats: base64
, csv
, json
, pickle
, plist
, query-string
, toml
, xml
, yaml
.
In all from_*
methods, the first argument can be: url, filepath or data-string.
In all to_*
methods, if filepath='...'
kwarg is specified, the output will be also saved at the specified filepath.
-
from_base64
# Try to load/decode a base64 encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to choose the subformat used under the hood:
# (`csv`, `json`, `query-string`, `toml`, `xml`, `yaml`), default: 'json'.
# It's possible to choose the encoding, default 'utf-8'.
# A ValueError is raised in case of failure.
d = benedict.from_base64(s, subformat='json', encoding='utf-8', **kwargs)
-
from_csv
# Try to load/decode a csv encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to specify the columns list, default: None (in this case the first row values will be used as keys).
# It's possible to pass decoder specific options using kwargs:
# https://docs.python.org/3/library/csv.html
# A ValueError is raised in case of failure.
d = benedict.from_csv(s, columns=None, columns_row=True, **kwargs)
-
from_json
# Try to load/decode a json encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://docs.python.org/3/library/json.html
# A ValueError is raised in case of failure.
d = benedict.from_json(s, **kwargs)
-
from_pickle
# Try to load/decode a pickle encoded in Base64 format and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://docs.python.org/3/library/pickle.html
# A ValueError is raised in case of failure.
d = benedict.from_pickle(s, **kwargs)
-
from_plist
# Try to load/decode a p-list encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://docs.python.org/3/library/plistlib.html
# A ValueError is raised in case of failure.
d = benedict.from_plist(s, **kwargs)
-
from_query_string
# Try to load/decode a query-string and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# A ValueError is raised in case of failure.
d = benedict.from_query_string(s, **kwargs)
-
from_toml
# Try to load/decode a toml encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://pypi.org/project/toml/
# A ValueError is raised in case of failure.
d = benedict.from_toml(s, **kwargs)
-
from_xml
# Try to load/decode a xml encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://github.com/martinblech/xmltodict
# A ValueError is raised in case of failure.
d = benedict.from_xml(s, **kwargs)
-
from_yaml
# Try to load/decode a yaml encoded data and return it as benedict instance.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# https://pyyaml.org/wiki/PyYAMLDocumentation
# A ValueError is raised in case of failure.
d = benedict.from_yaml(s, **kwargs)
-
to_base64
# Return the dict instance encoded in base64 format and optionally save it at the specified 'filepath'.
# It's possible to choose the subformat used under the hood:
# ('csv', json', `query-string`, 'toml', 'xml', 'yaml'), default: 'json'.
# It's possible to choose the encoding, default 'utf-8'.
# It's possible to pass decoder specific options using kwargs.
# A ValueError is raised in case of failure.
s = d.to_base64(subformat='json', encoding='utf-8', **kwargs)
-
to_csv
# Return a list of dicts encoded in csv format and optionally save it at the specified filepath.
# It's possible to specify the key of the item (list of dicts) to encode, default: 'values'.
# It's possible to specify the columns list, default: None (in this case the keys of the first item will be used).
# A ValueError is raised in case of failure.
d = benedict.to_csv(key='values', columns=None, columns_row=True, **kwargs)
-
to_json
# Return the dict instance encoded in json format and optionally save it at the specified filepath.
# It's possible to pass encoder specific options using kwargs:
# https://docs.python.org/3/library/json.html
# A ValueError is raised in case of failure.
s = d.to_json(**kwargs)
-
to_pickle
# Return the dict instance as pickle encoded in Base64 format and optionally save it at the specified filepath.
# The pickle protocol used by default is 2.
# It's possible to pass encoder specific options using kwargs:
# https://docs.python.org/3/library/pickle.html
# A ValueError is raised in case of failure.
s = d.to_pickle(**kwargs)
-
to_plist
# Return the dict instance encoded in p-list format and optionally save it at the specified filepath.
# It's possible to pass encoder specific options using kwargs:
# https://docs.python.org/3/library/plistlib.html
# A ValueError is raised in case of failure.
s = d.to_plist(**kwargs)
-
to_query_string
# Return the dict instance as query-string and optionally save it at the specified filepath.
# A ValueError is raised in case of failure.
s = d.to_query_string(**kwargs)
-
to_toml
# Return the dict instance encoded in toml format and optionally save it at the specified filepath.
# It's possible to pass encoder specific options using kwargs:
# https://pypi.org/project/toml/
# A ValueError is raised in case of failure.
s = d.to_toml(**kwargs)
-
to_xml
# Return the dict instance encoded in xml format and optionally save it at the specified filepath.
# It's possible to pass encoder specific options using kwargs:
# https://github.com/martinblech/xmltodict
# A ValueError is raised in case of failure.
s = d.to_xml(**kwargs)
-
to_yaml
# Return the dict instance encoded in yaml format.
# If filepath option is passed the output will be saved ath
# It's possible to pass encoder specific options using kwargs:
# https://pyyaml.org/wiki/PyYAMLDocumentation
# A ValueError is raised in case of failure.
s = d.to_yaml(**kwargs)
Parse methods
These methods are wrappers of the get
method, they parse data trying to return it in the expected type.
-
get_bool
# Get value by key or keypath trying to return it as bool.
# Values like `1`, `true`, `yes`, `on`, `ok` will be returned as `True`.
d.get_bool(key, default=False)
-
get_bool_list
# Get value by key or keypath trying to return it as list of bool values.
# If separator is specified and value is a string it will be splitted.
d.get_bool_list(key, default=[], separator=',')
-
get_date
# Get value by key or keypath trying to return it as date.
# If format is not specified it will be autodetected.
# If choices and value is in choices return value otherwise default.
d.get_date(key, default=None, format=None, choices=[])
-
get_date_list
# Get value by key or keypath trying to return it as list of date values.
# If separator is specified and value is a string it will be splitted.
d.get_date_list(key, default=[], format=None, separator=',')
-
get_datetime
# Get value by key or keypath trying to return it as datetime.
# If format is not specified it will be autodetected.
# If choices and value is in choices return value otherwise default.
d.get_datetime(key, default=None, format=None, choices=[])
-
get_datetime_list
# Get value by key or keypath trying to return it as list of datetime values.
# If separator is specified and value is a string it will be splitted.
d.get_datetime_list(key, default=[], format=None, separator=',')
-
get_decimal
# Get value by key or keypath trying to return it as Decimal.
# If choices and value is in choices return value otherwise default.
d.get_decimal(key, default=Decimal('0.0'), choices=[])
-
get_decimal_list
# Get value by key or keypath trying to return it as list of Decimal values.
# If separator is specified and value is a string it will be splitted.
d.get_decimal_list(key, default=[], separator=',')
-
get_dict
# Get value by key or keypath trying to return it as dict.
# If value is a json string it will be automatically decoded.
d.get_dict(key, default={})
-
get_email
# Get email by key or keypath and return it.
# If value is blacklisted it will be automatically ignored.
# If check_blacklist is False, it will be not ignored even if blacklisted.
d.get_email(key, default='', choices=None, check_blacklist=True)
-
get_float
# Get value by key or keypath trying to return it as float.
# If choices and value is in choices return value otherwise default.
d.get_float(key, default=0.0, choices=[])
-
get_float_list
# Get value by key or keypath trying to return it as list of float values.
# If separator is specified and value is a string it will be splitted.
d.get_float_list(key, default=[], separator=',')
-
get_int
# Get value by key or keypath trying to return it as int.
# If choices and value is in choices return value otherwise default.
d.get_int(key, default=0, choices=[])
-
get_int_list
# Get value by key or keypath trying to return it as list of int values.
# If separator is specified and value is a string it will be splitted.
d.get_int_list(key, default=[], separator=',')
-
get_list
# Get value by key or keypath trying to return it as list.
# If separator is specified and value is a string it will be splitted.
d.get_list(key, default=[], separator=',')
-
get_list_item
# Get list by key or keypath and return value at the specified index.
# If separator is specified and list value is a string it will be splitted.
d.get_list_item(key, index=0, default=None, separator=',')
-
get_phonenumber
# Get phone number by key or keypath and return a dict with different formats (e164, international, national).
# If country code is specified (alpha 2 code), it will be used to parse phone number correctly.
d.get_phonenumber(key, country_code=None, default=None)
-
get_slug
# Get value by key or keypath trying to return it as slug.
# If choices and value is in choices return value otherwise default.
d.get_slug(key, default='', choices=[])
-
get_slug_list
# Get value by key or keypath trying to return it as list of slug values.
# If separator is specified and value is a string it will be splitted.
d.get_slug_list(key, default=[], separator=',')
-
get_str
# Get value by key or keypath trying to return it as string.
# Encoding issues will be automatically fixed.
# If choices and value is in choices return value otherwise default.
d.get_str(key, default='', choices=[])
-
get_str_list
# Get value by key or keypath trying to return it as list of str values.
# If separator is specified and value is a string it will be splitted.
d.get_str_list(key, default=[], separator=',')
-
get_uuid
# Get value by key or keypath trying to return it as valid uuid.
# If choices and value is in choices return value otherwise default.
d.get_uuid(key, default='', choices=[])
-
get_uuid_list
# Get value by key or keypath trying to return it as list of valid uuid values.
# If separator is specified and value is a string it will be splitted.
d.get_uuid_list(key, default=[], separator=',')
Testing
# create python virtual environment
virtualenv testing_benedict
# activate virtualenv
cd testing_benedict && . bin/activate
# clone repo
git clone https://github.com/fabiocaccamo/python-benedict.git src && cd src
# install requirements
pip install --upgrade pip
pip install -r requirements.txt
# run tests using tox
tox
# or run tests using unittest
python -m unittest
# or run tests using setuptools
python setup.py test
License
Released under MIT License.
See also
python-fsutil
- file-system utilities for lazy devs. 🧟♂️
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for python_benedict-0.23.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b484901d94eb5b8aabd3e612cf1c504b42a92b6f17506428c60dbf93c3a88c6e |
|
MD5 | d23f0022020dcc9d9b7d28e93123e8d1 |
|
BLAKE2b-256 | 87c8ae31902c3e6f671580e14472ca23d4b19831085999ff34ee00a22f648e84 |