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()
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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)
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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'])
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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')
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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.
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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)
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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=',')
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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=[])
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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=',')
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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=[])
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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=',')
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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=[])
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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=',')
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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={})
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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)
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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=[])
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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=',')
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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=[])
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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=',')
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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=',')
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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=',')
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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)
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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=[])
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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=',')
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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=[])
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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=',')
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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=[])
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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. 🧟♂️
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