mapping-kit

.. |package-name| replace:: mapping-kit

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mapping-kit ###########

|pypi-version| |pypi-downloads|

Description

Provides

• AttributeDict (keys accessible as dot-denoted attributes, remains subscriptable)
• GroupDict (groups keys based on prefix, makes it easy to write complex configuration in a single dictionary and access it easily)
• SuperDict (a dictionary that is defaultdict, OrderedDict, case-insensitive, and recursive, each customizable by user; also stores ancestry for each item)
• NestedDict (nests paremeters )
• VirtualIterable (iterate through multilpe objects without creating concrete objects)

Examples of AttributeDict:

.. code-block:: python

from mapping_kit import AttributeDict

All the standard ways that a Python dict can be created in, can be used to

create AttributeDict. It can also be used as a normal dictionary.

sample_dict = { "first_name": "Charlie", "last_name": "Brown", } ad_from_dict = AttributeDict(**sample_dict) print("Hello", ad_from_dict.first_name, ad_from_dict["last_name"])

Hello Charlie Brown

sample_tuples = [ ("model", "Hindustan Ambassador"), ("production", "1957-2014"), ] ad_from_tuples = AttributeDict(sample_tuples) print(ad_from_tuples.model, "- production years", ad_from_tuples["production"])

Hindustan Ambassador - production years 1957-2014

Examples of CartesianIterator:

.. code-block:: python

from mapping_kit import CartesianIterator

ci = CartesianIterator(["some", "no"], ["one", "two"], ["saw", "took", "did"], ["it"]) for cartesian in ci: print(cartesian)

['some', 'one', 'saw', 'it']

['some', 'one', 'took', 'it']

['some', 'one', 'did', 'it']

['some', 'two', 'saw', 'it']

['some', 'two', 'took', 'it']

['some', 'two', 'did', 'it']

['no', 'one', 'saw', 'it']

['no', 'one', 'took', 'it']

['no', 'one', 'did', 'it']

['no', 'two', 'saw', 'it']

['no', 'two', 'took', 'it']

['no', 'two', 'did', 'it']

Examples of GroupDict:

.. code-block:: python

from mapping_kit import GroupDict

sample = { "#Version": "1.4.9a1", "beverages": { "_lassi": "A yoghurt based beverage", "_aamras": "Thick mango pulp", "*jaljeera": "Spices mixed in water, out of stock", "*alcoholic_drinks": { "beer": "4-6% alcohol", "red_wine": "5.5-10% alcohol", }, }, "appetizers": { "_pani_puri": "Masala water filled crispy puffed bread", "!chicken_pakora": "Deep-fried chicken stuffing in Indian pakoras", "_aloo_chaat": "Potato with spicy gravy", "!prawn_toast": "Sesame and prawns rolled in bread", } }

gd = GroupDict(sample, grouping={"#": "comment", # arbitrary group names "_": "vegetarian", "!": "non_vegetarian", "*": "not_available"}, default_group_name="public", key_ignorecase=True)

Accessing group comment

print("The version is", gd.comment["version"])

The version is 1.4.9a1

for key, value in gd.comment.items(): print(f"{key}: {value}")

Version: 1.4.9a1

Chained groups

veg_appetizers = gd.public["appetizers"].vegetarian print("Vegetarian appetizers are:") for key in veg_appetizers.keys(): print(f" {key}")

Vegetarian appetizers are:

pani_puri

aloo_chaat

beverages_not_available = gd["beverages"].not_available print("Beverages not available are:") for bna, bna_desc in beverages_not_available.items(): if isinstance(bna_desc, dict): for bna_sub, bna_sub_desc in bna_desc.public.items(): print(f" {bna_sub} ({bna_sub_desc})") else: print(f" {bna} ({bna_desc})")

Beverages not available are:

jaljeera (Spices mixed in water, out of stock)

beer (4-6% alcohol)

red_wine (5.5-10% alcohol)

Examples of NestedDict:

.. code-block:: python

from mapping_kit import NestedDict

sample = { "in": { "support-conf": { "contact-email": "[e-mail]", "contact-call": "[phone]", }, "official-name": "Republic of India", "states": { "ka": { "support-conf": { "contact-email": "[e-mail]", }, "name": "Karnataka", "cities": { "blr": { "description": "Bengaluru Urban", "support-conf": { "contact-call": "[phone]", }, }, }, }, }, }, }

nd = NestedDict(sample, nest_keys=["support-conf"])

blr_conf = nd["in"]["states"]["ka"]["cities"]["blr"]["support-conf"] for key, value in blr_conf.items(): print(key, ": ", value, sep="")

contact-call: [phone]

contact-email: [e-mail]

ka_conf = nd["in"]["states"]["ka"]["support-conf"] for key, value in ka_conf.items(): print(key, ": ", value, sep="")

contact-email: [e-mail]

contact-call: [phone]

in_conf = nd["in"]["support-conf"] for key, value in in_conf.items(): print(key, ": ", value, sep="")

contact-email: [e-mail]

contact-call: [phone]

nd.disable_ancestry_lookup() # temporarily disable lookup nd.enable_ancestry_lookup() # enable back lookup

Examples of SuperDict:

.. code-block:: python

from mapping_kit import SuperDict

sample = { "mode": "read", "max-size": 1024 * 1024, "type": "csv", "files": { "mode": "append", "file-1": { "mode": "write", "Name": "FromMumbai.pdf", }, "file-2": { "max-size": 3 * 1024 * 1024, "Name": "FromTokyo.pdf", "worksheet": { "rates": "week-1", }, }, }, }

sd = SuperDict(sample, key_ignorecase=True, # ordereddict=True, # default_factory=list, )

ordereddict: makes order of keys important when comparing two SuperDicts

default_factory: same usage as in collections.defaultdict

file_1 = sd["files"]["file-1"] file_2 = sd["files"]["file-2"] worksheet = file_2["worksheet"]

for k, v in file_2.items(): print(f"file-2: {k}={v}")

file-2: max-size=3145728

file-2: name=FromTokyo.pdf (name instead of Name)

file-2: worksheet=SuperDict(...) (recursive SuperDict)

file-2: mode=append (inherited from nearest ancestry)

print(f"file-1: NAME={file_1["NAME"]}")

file-1: NAME=FromMumbai.pdf (case-insensitive key NAME)

print(f"file-1.parent: mode={file_1.parent["mode"]}")

file-1.parent: mode=append (access parent)

print(f"worksheet.parent.parent: mode={worksheet.parent.parent["mode"]}")

worksheet.parent.parent: mode=append (access parent hierarchy)

print(f"worksheet.root: mode={worksheet.root["mode"]}")

worksheet.root: mode=read (jump straight to root)

print(f"worksheet.root['files']: mode={worksheet.root["files"]["mode"]}")

worksheet.root['files']: mode=append (access keys within root)

Example of VirtualIterable:

.. code-block:: python

from mapping_kit import VirtualIterable

for item in VirtualIterable(["a", "b"], None, 4, "c" (1, 2)): print(item)

a

b

None

4

c

1

2

Note: This is an alpha version, and things may change quite a bit.