A Python library to flatten a dictionary with nested dictionnaries and lists

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Project description

dictflat

A Python library to flatten a dictionary with nested dictionnaries and lists

Use cases

Transform a dictionary structure into a new organization ready to be inserted into a relational database.

Installation

poetry add dictflat

Quick start

>>> from dictflat import DictFlat
>>> import json
>>> r = DictFlat(
    root_key="root"
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "Phone_Numbers": [
            {"type": "home", "number": "555-1234"},
            {"type": "work", "number": "555-5678"},
        ],
    }
)
>>> print("%s" % json.dumps(r, indent=2))
{
  "root": [
    {
      "__id": "662783f7-b1a0-4e8c-9de9-f3a72a896d4c",
      "name": "John",
      "pers_id": 12
    }
  ],
  "root.birth": [
    {
      "__id": "e72d549a-89f5-4208-99c0-4ce3493cbf9e",
      "__ref__root": "662783f7-b1a0-4e8c-9de9-f3a72a896d4c",
      "date": "10/06/1976 01:10:35"
    }
  ],
  "root.birth.address": [
    {
      "__id": "cc489c03-82ca-4b6e-a620-32c9c4be236c",
      "__ref__root.birth": "e72d549a-89f5-4208-99c0-4ce3493cbf9e",
      "street": "123 Main St",
      "city": "Anytown",
      "state": "CA"
    }
  ],
  "root.Phone_Numbers": [
    {
      "__id": "ba1560de-9c4c-4886-b4ca-684e0a7e5df0",
      "__ref__root": "662783f7-b1a0-4e8c-9de9-f3a72a896d4c",
      "type": "home",
      "number": "555-1234"
    },
    {
      "__id": "f1032025-6c7d-4341-8e6a-f0dce2374388",
      "__ref__root": "662783f7-b1a0-4e8c-9de9-f3a72a896d4c",
      "type": "work",
      "number": "555-5678"
    }
  ]
}

The result is always a dictionary where each key is a reference to the original dictionary.

In this example, the original root document is identified by the token “root” (the root key) and the "address" sub-dictionary is identified by “root.address”.

Each dictionary value is always a list. See below for more examples with more than one element in lists.

Each sub-dictionnary have:

an unique field named "__id" (like a primary key)
except for root, a "__ref__root" who contains the "__id" value of parent dictionnary;
- the "root" token in "__ref__root" field name is directly a reference to the global result dictionnary.

Documentation

Basic usages

Empty dictionnary

>>> DictFlat().flat({})

Result:

{}

Simple dictionnary

How: Use init function "root_key" parameter.

root_key parameter signature:

str

Example:

DictFlat(
    root_key="rk"
).flat(
    {
        "a": 1
    }
)

Result:

{
    "rk": [
        {
            "__id": "i_1",
            "a": 1
        }
    ]
}

Nested dictionnaries

2 levels

Example:

DictFlat(
    root_key="rk"
).flat(
    d={
        "name": "John",
        "address": {
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        },
        "birthdate": "10/06/1976 01:10:35"
    }
)

Result:

{
    "rk": [
        {
            "__id": "i_1",
            "birthdate": "10/06/1976 01:10:35",
            "name": "John"
        }
    ],
    "rk.address": [
        {
            "__id": "i_2",
            "__ref__rk": "r_3",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

3 levels

Example:

DictFlat(
    root_key="rk"
).flat(
    d={
        "name": "John",
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "i_1",
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "i_2",
            "__ref__rk": "r_3",
            "date": "10/06/1976 01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "i_4",
            "__ref__rk.birth": "r_5",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Use your own function to generate ids

How: Use init function "fct_build_id" parameter.

fct_build_id parameter signature:

def fct_name(d: Dict, path: str) -> str

By default, the "uuid4" function from "uuid" Python standard module is used.

In this example the function fct_build_id is used to generate ids.

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
            "date": "10/06/1976 01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Change/Replace value

How: Use init function "change" parameter.

change parameter signature:

Optional[Dict[str, Callable]]

By default, no values are modified.

The dictionnary key is the future field name.

The Callable dictionnary value signature is:

def fct_name(fieldname: str, value: Any) -> Any:

Change a string by another string

Example with a date in a string to another string:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date": fix_date,
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
            "date": "1976-06-10T01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Change a string by a dictionnary

Example with a date in a string to a dictionnary where date and time are separated:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date": date2dict,
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

assert df == {
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Drop fields (by name)

How: Use init function "drop" parameter.

drop parameter signature:

Optional[List[str]]

By default, no values are dropped.

Elements list are the future field names.

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date": fix_date,
    },
    drop=[
        "rk.birth.address.state",
    ]
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
            "date": "1976-06-10T01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown"
        }
    ]
}

Rename/Change field names

How: Use init function "rename" parameter.

rename parameter signature:

Optional[Dict[str, Union[str, Callable]]]

By default, no field names values are modified.

The dictionnary key is the first version of the future field name. The dictionnary value is the final field name or a function to genrate the new field name.

If the dictionnary key is a "Callable", the signature is:

def fct_name(s: str) -> str

IMPORTANT If you use "change" parameter and "rename" parameter, use the final field name in "rename" dictionnary value as "change" dictionnary key.

Rename field name by name

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        "rk.birth.date": "rk.birth.date_dict",
        "PersId": "pers_id",
    }
).flat(
    d={
        "name": "John",
        "PersId": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Rename ALL field names

You could rename all fields using the "RENAME_ALL" special key and un function to do this.

The "Callable" dictionnary key function signature is:

def fct_name(s: str) -> str

IMPORTANT You could use "RENAME_ALL" key and field name keys. "RENAME_ALL" key is allway use BEFORE field name keys

In this example, the function "str_2_snakecase" is called before the other rename key.

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        RENAME_ALL: str_2_snakecase,
        "rk.birth.date": "rk.birth.date_dict",
    }
).flat(
    d={
        "Name": "John",
        "PersId": 12,
        "Birth": {
            "Address": {
                "Street": "123 Main St",
                "City": "Anytown",
                "State": "CA"
            },
            "Date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ]
}

Lists

Each element of a list a transformed as a dictionnary of a same type.

List of dictionaries

By default, no element are added in each dictionnary.

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        "rk.birth.date": "rk.birth.date_dict",
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "Phone_Numbers": [
            {"type": "home", "number": "555-1234"},
            {"type": "work", "number": "555-5678"},
        ],
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "rk.Phone_Numbers": [
        {
            "__id": "5d1765d47e80b6d3",
            "__ref__rk": "2a02485bc672ee47",
            "type": "home",
            "number": "555-1234"
        },
        {
            "__id": "87d897df197fbdc7",
            "__ref__rk": "2a02485bc672ee47",
            "type": "work",
            "number": "555-5678"
        },
    ],
}

Add counter field in each list element

How: Use init function "list_2_object" parameter.

list_2_object parameter signature:

Optional[Dict[str, Dict]]

By default, no fields are added.

The dictionnary key is the first version of the future field name. The dictionnary value is sub-dictionnary for parametrize the job:

The key "counter_field" contains the field name (a "str") for the counter;
- Default value is "idx".
The key "starts_at" contains the counter start value (a "int").
- Default value is 1.

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        "rk.birth.date": "rk.birth.date_dict",
    },
    list_2_object={
        "rk.Phone_Numbers": {
            "counter_field": "count",
            "starts_at": 0
        }
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "Phone_Numbers": [
            {"type": "home", "number": "555-1234"},
            {"type": "work", "number": "555-5678"},
        ],
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "rk.Phone_Numbers": [
        {
            "__id": "30fb5bc71274e531",
            "__ref__rk": "2a02485bc672ee47",
            "count": 0,
            "type": "home",
            "number": "555-1234"
        },
        {
            "__id": "6b74835b56e08367",
            "__ref__rk": "2a02485bc672ee47",
            "count": 1,
            "type": "work",
            "number": "555-5678"
        },
    ],
}

List of non-dictionary elements

If the list do not contains dictionnary elements, you could specify the name of the future key with the suffix ".__inner".

Example:

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        RENAME_ALL: str_2_snakecase,
        "rk.birth.date": "rk.birth.date_dict",
        "rk.phone_numbers.__inner": "number",
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "Phone_Numbers": [
            "555-1234",
            "555-5678",
        ],
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "rk.phone_numbers": [
        {
            "__id": "24886b1e9942f612",
            "__ref__rk": "2a02485bc672ee47",
            "number": "555-1234"
        },
        {
            "__id": "a98b1c4fa2e2a2b5",
            "__ref__rk": "2a02485bc672ee47",
            "number": "555-5678"
        },
    ],
}

Squash dictionnaries

When you have a dictionary of dictionaries and want to have just one.

How: Use init function "dict_of_dicts_2_dict" parameter.

dict_of_dicts_2_dict parameter signature:

Optional[Dict[str, Dict]]

The key is the future dictionnary name The value is the definition of treatment:

"sep": The separator between the key of first data dictionnary and the key of second data dictionnary (default value is a dot ".")
- You could change the default value for all separators with "sep" init function.
"reverse": To change the order of the keys on each side of the separator (default value is False)

Example:

From:

{
    "miracles": {
        "first": {
            "k": "one",
            "e": "e-one"
        },
        "second": {
            "k": "two"
        },
        "third": "three"
    }
}

To:

{
    "rk.miracles": [
        {
            "__id": "041102055056a3a8",
            "__ref__rk": "2a02485bc672ee47",
            "first/k": "one",
            "first/e": "e-one",
            "second/k": "two",
            "third": "three",
        },
    ]
}

DictFlat(
    root_key="rk",
    fct_build_id=fct_build_id,
    change={
        "rk.birth.date_dict": date2dict,
    },
    rename={
        "rk.birth.date": "rk.birth.date_dict",
    },
    dict_of_dicts_2_dict={
        "rk.miracles": {
            "reverse": False,
            "sep": "/"
        }
    }
).flat(
    d={
        "name": "John",
        "pers_id": 12,
        "birth": {
            "address": {
                "street": "123 Main St",
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "miracles": {
            "first": {
                "k": "one",
                "e": "e-one"
            },
            "second": {
                "k": "two"
            },
            "third": "three"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "2a02485bc672ee47",
            "pers_id": 12,
            "name": "John"
        }
    ],
    "rk.birth": [
        {
            "__id": "034b3cd2487b9d17",
            "__ref__rk": "2a02485bc672ee47",
        }
    ],
    "rk.birth.date_dict": [
        {
            "__id": "71d9d6cb90bcd168",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "date": "1976-06-10",
            "time": "01:10:35",
        }
    ],
    "rk.birth.address": [
        {
            "__id": "4f49da4f0b4df789",
            "__ref__rk.birth": "034b3cd2487b9d17",
            "street": "123 Main St",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "rk.miracles": [
        {
            "__id": "041102055056a3a8",
            "__ref__rk": "2a02485bc672ee47",
            "first/k": "one",
            "first/e": "e-one",
            "second/k": "two",
            "third": "three",
        },
    ],
}

Nested dictionnaries with simple key names

When you don't want long key names.

How: Use init function "simple_keys" parameter.

simple_keys parameter signature:

bool

Default value is False.

!Warning! If you use this parameter with True value. The result may contains some unexpected values. If you have input with two or more sub-dictionnaries with the same name but in different paths, the output contains only one general key. See second example

Simple

Example:

DictFlat(
    root_key="rk",
    simple_keys=True
).flat(
    d={
        "name": "John",
        "birth": {
            "address": {
                "street": {
                    "number": "123",
                    "road": "Main St"
                },
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "i_1",
            "name": "John"
        }
    ],
    "birth": [
        {
            "__id": "i_2",
            "__ref__rk": "r_3",
            "date": "10/06/1976 01:10:35",
        }
    ],
    "address": [
        {
            "__id": "i_4",
            "__ref__birth": "r_5",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "street": [
        {
            "__id": "i_6",
            "__ref__address": "r_7",
            "number": "123",
            "road": "Main St",
        },
    ]
}

Unexpected result

Example:

DictFlat(
    root_key="rk",
    simple_keys=True
).flat(
    d={
        "name": "John",
        "birth": {
            "address": {
                "street": {
                    "number": "123",
                    "road": "Main St"
                },
                "city": "Anytown",
                "state": "CA"
            },
            "date": "10/06/1976 01:10:35"
        },
        "street": {
            "other": "abc"
        }
    }
)

Result:

{
    "rk": [
        {
            "__id": "i_1",
            "name": "John"
        }
    ],
    "birth": [
        {
            "__id": "i_2",
            "__ref__rk": "r_3",
            "date": "10/06/1976 01:10:35",
        }
    ],
    "address": [
        {
            "__id": "i_4",
            "__ref__birth": "r_5",
            "city": "Anytown",
            "state": "CA"
        }
    ],
    "street": [
        {
            "__id": "i_6",
            "__ref__address": "r_7",
            "number": "123",
            "road": "Main St",
        },
        {
            "__id": "i_8",
            "__ref__rk": "r_9",
            "other": "abc",
        },

    ]
}

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0.2.3

Nov 13, 2025

0.2.1

Oct 13, 2025

0.2.0

Oct 12, 2025

0.1.10

Oct 6, 2025

0.1.9

Sep 2, 2025

0.1.8

Jun 27, 2025

0.1.7 yanked

Jun 27, 2025

Reason this release was yanked:

Bad value for special dict keys

0.1.6

Jun 18, 2025

This version

0.1.5

Jun 16, 2025

0.1.4

Jun 7, 2025

0.1.3

Jun 6, 2025

0.1.2

May 31, 2025

0.1.1

May 26, 2025

0.1.0

May 25, 2025

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dictflat 0.1.5

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dictflat

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Empty dictionnary

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2 levels

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Use your own function to generate ids

Change/Replace value

Change a string by another string

Change a string by a dictionnary

Drop fields (by name)

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Rename field name by name

Rename ALL field names

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