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.

License: MIT License (MIT)

Author: Fabio Caccamo

Tags python, dictionary, dictionaries, dict, benedict, subclass, extended, keylist, keypath, utility, io, data, file, url, read, write, parse, base64, csv, json, query-string, toml, xml, yaml, clean, clone, deepclone, deepupdate, dump, filter, flatten, groupby, invert, merge, move, nest, remove, rename, search, standardize, subset, swap, traverse, unflatten, unique

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. ;)

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
- clean
- clone
- dump
- filter
- find
- flatten
- groupby
- invert
- items_sorted_by_keys
- items_sorted_by_values
- keypaths
- match
- merge
- move
- nest
- remove
- rename
- search
- standardize
- subset
- swap
- traverse
- unflatten
- unique
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 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.

Project details

License: MIT License (MIT)

Author: Fabio Caccamo

Release history Release notifications | RSS feed

This version

0.23.2

Jan 19, 2021

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Jan 14, 2021

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Dec 22, 2020

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Dec 22, 2020

0.22.2

Nov 30, 2020

0.22.1

Nov 27, 2020

0.22.0

Oct 15, 2020

0.21.1

Sep 30, 2020

0.21.0

Sep 22, 2020

0.20.0

Sep 20, 2020

0.19.0

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Sep 4, 2020

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python-benedict 0.23.2

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Project description

python-benedict

Features

Index

Installation

Usage

Basics

Keylist

Keypath

Custom keypath separator

Change keypath separator

Disable keypath functionality

List index support

API

Utility methods

clean

clone

dump

filter

find

flatten

groupby

invert

items_sorted_by_keys

items_sorted_by_values

keypaths

match

merge

move

nest

remove

rename

search

standardize

subset

swap

traverse

unflatten

unique

I/O methods

from_base64

from_csv

from_json

from_pickle

from_plist

from_query_string

from_toml

from_xml

from_yaml

to_base64

to_csv

to_json

to_pickle

to_plist

to_query_string

to_toml

to_xml

to_yaml

Parse methods

get_bool

get_bool_list

get_date

get_date_list

get_datetime

get_datetime_list

get_decimal

get_decimal_list

get_dict

get_email

get_float

get_float_list

get_int

get_int_list