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)

d = benedict(keyattr_dynamic=True) # default False
d.profile.firstname = "Fabio"
d.profile.lastname = "Caccamo"
print(d) # -> { "profile":{ "firstname":"Fabio", "lastname":"Caccamo" } }

d = benedict(existing_dict, keyattr_enabled=False) # default True

d.keyattr_enabled = False

d = benedict(existing_dict, keyattr_dynamic=True) # default False

d.keyattr_dynamic = True

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" }

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"]

d = benedict(existing_dict, keypath_separator="/")

d.keypath_separator = "/"

d = benedict(existing_dict, keypath_separator=None)

d.keypath_separator = None

# 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")

# 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)

# Return a clone (deepcopy) of the dict.
c = d.clone()

# 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())

# 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)

# 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)

# Return a new flattened dict using the given separator to join nested dict keys to flatten keypaths.
f = d.flatten(separator="_")

# 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")

# 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)

# 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)

# 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)

# 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)

# 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 one or more dictionary objects into current instance (deepupdate).
# Sub-dictionaries keys will be merged together.
# If overwrite is False, existing values will not be overwritten.
# If concat is True, list values will be concatenated together.
d.merge(a, b, c, overwrite=True, concat=False)

# 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 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 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 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 all dict keys, e.g. "Location Latitude" -> "location_latitude".
d.standardize()

# 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 items values at the given keys.
d.swap("firstname", "lastname")

# Traverse a dict passing each item (dict, key, value) to the given callback function.
def f(d, key, value):
    print(f"dict: {d} - key: {key} - value: {value}")
d.traverse(f)

# Return a new unflattened dict using the given separator to split dict keys to nested keypaths.
u = d.unflatten(separator="_")

# Remove duplicated values from the dict.
d.unique()

# filepath
d = benedict("/root/data.yml", format="yaml")

# url
d = benedict("https://localhost:8000/data.xml", format="xml")

# s3
d = benedict("s3://my-bucket/data.xml", s3_options={"aws_access_key_id": "...", "aws_secret_access_key": "..."})

# data-string
d = benedict('{"a": 1, "b": 2, "c": 3, "x": 7, "y": 8, "z": 9}')

# 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)

# 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)

# Try to load/decode a ini 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/configparser.html
# A ValueError is raised in case of failure.
d = benedict.from_ini(s, **kwargs)

# 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)

# 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)

# 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)

# 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)

# 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)

# Try to load/decode a xls file (".xls", ".xlsx", ".xlsm") from url, filepath or data-string.
# Accept as first argument: url, filepath or data-string.
# It's possible to pass decoder specific options using kwargs:
# - https://openpyxl.readthedocs.io/ (for .xlsx and .xlsm files)
# - https://pypi.org/project/xlrd/ (for .xls files)
# A ValueError is raised in case of failure.
d = benedict.from_xls(s, sheet=0, columns=None, columns_row=True, **kwargs)

# 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)

# 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)

# 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)

# Return a list of dicts in the current dict 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.
s = d.to_csv(key="values", columns=None, columns_row=True, **kwargs)

# Return the dict instance encoded in ini 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/configparser.html
# A ValueError is raised in case of failure.
s = d.to_ini(**kwargs)

# 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)

# 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)

# 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)

# 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)

# 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)

# 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)

# 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)

# 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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=",")