A simple tool to take a json payload and convert it into Python TypedDict class definitions
A web version is available on https://pytyper.dev/
When dealing with API responses, you're very likely to be using JSON responses, and you might have deeply nested dictionaries, lists of items and it can be slightly hard to wrap your head around the structure of the responess you are working with. The first thing I usually do it try to create some data structure around it so that I can benefit from linting and typing information in my code.
Now this tends to be time consuming and error prone, so I thought it might be a good idea to automate this process with a tool for the future. Just as an example, if we take the output generated from the Example section below and imagine it's a response we get from an api. We can plug it in like this:
from project.types import Root
def get_from_api() -> Root:
pass
def run() -> None:
response = get_from_api()
test1 = response["nested_dict"]["number"] + 1
test2 = response["nested_dict"]["string"] + 1
test3 = response["nested_dict"]["non_existant"] + 1
for item in response["optional_items"]:
print(item + 1)and if we run mypy on this
-> % poetry run mypy test.py
test.py:43: error: Unsupported operand types for + ("str" and "int")
test.py:44: error: TypedDict "NestedDict" has no key 'non_existant'
test.py:46: error: Unsupported operand types for + ("None" and "int")
test.py:46: error: Unsupported operand types for + ("str" and "int")
test.py:46: note: Left operand is of type "Union[None, int, str]"
Found 4 errors in 1 file (checked 1 source file)it will immediately detect four issues!
I also want to use this project to learn more about analysing code, making sure the project is well tested so that it's easy to experiment and try different approaches.
Either supply a path to a file or pipe json output to dict-typer
-> % dict-typer --help
Usage: dict-typer [OPTIONS] [FILE]...
Options:
--imports / --no-imports Show imports at the top, default: True
-r, --rich Show rich output.
-l, --line-numbers Show line numbers if rich.
--version Show the version and exit.
--help Show this message and exit.
-> % dict-typer ./.example.json
...
-> % curl example.com/test.json | dict-typer
...There are two ways to define a TypedDict, the primary one that uses the class based structure, as seen in the examples here. It's easier to read, but it has a limitation that the each key has to be avalid identifier and not a reserved keyword. Normally that's not an issue, but if you have for example, the following data
{
"numeric-id": 123,
"from": "far away",
}which is valid json, but has the invalid identifier numeric-id and reserved
keyword from, meaning the definition
class Root(TypedDict):
numeric-id: int
from: stris invalid. In detected cases, dict-typer will use an alternative way to define those types, looking like this
Root = TypedDict('Root', {'numeric-id': int, 'from': str'})which is not as readable, but valid.
dict-typer by default only uses the alternative definition for the types with invalid keys.
If the root of the payload is a list, it will be treated just like a list
within a dictionary, where each item is parsed and definitions created for sub
items. In these cases, a type alias is added as well to the output to capture
the type of the list. For example, the list [1, "2", 3.0, { "id": 123 }, { "id": 456 }] will generate the following definitions:
from typing_extensions import TypedDict
class RootItem(TypedDict):
id: int
Root = List[Union[RootItem, float, int, str]]-> % cat .example.json
{
"number_int": 123,
"number_float": 3.0,
"string": "string",
"list_single_type": ["a", "b", "c"],
"list_mixed_type": ["1", 2, 3.0],
"nested_dict": {
"number": 1,
"string": "value"
},
"same_nested_dict": {
"number": 2,
"string": "different value"
},
"multipe_levels": {
"level2": {
"level3": {
"number": 3,
"string": "more values"
}
}
},
"nested_invalid": { "numeric-id": 123, "from": "far away" },
"optional_items": [1, 2, "3", "4", null, 5, 6, null]
}
-> % cat .example.json | dict-typer
from typing import List, Union
from typing_extensions import TypedDict
class NestedDict(TypedDict):
number: int
string: str
class Level2(TypedDict):
level3: NestedDict
class MultipeLevels(TypedDict):
level2: Level2
NestedInvalid = TypedDict("NestedInvalid", {
"numeric-id": int,
"from": str,
})
class Root(TypedDict):
number_int: int
number_float: float
string: str
list_single_type: List[str]
list_mixed_type: List[Union[float, int, str]]
nested_dict: NestedDict
same_nested_dict: NestedDict
multipe_levels: MultipeLevels
nested_invalid: NestedInvalid
optional_items: List[Union[None, int, str]]In [1]: source = {
...: "number_int": 123,
...: "number_float": 3.0,
...: "string": "string",
...: "list_single_type": ["a", "b", "c"],
...: "list_mixed_type": ["1", 2, 3.0],
...: "nested_dict": {
...: "number": 1,
...: "string": "value"
...: },
...: "same_nested_dict": {
...: "number": 2,
...: "string": "different value"
...: },
...: "multipe_levels": {
...: "level2": {
...: "level3": {
...: "number": 3,
...: "string": "more values"
...: }
...: }
...: },
...: "nested_invalid": { "numeric-id": 123, "from": "far away" },
...: "optional_items": [1, 2, "3", "4", None, 5, 6, None]
...: }
...:
In [2]: from dict_typer import get_type_definitions
In [3]: print(get_type_definitions(source, show_imports=True))
from typing import List, Union
from typing_extensions import TypedDict
class NestedDict(TypedDict):
number: int
string: str
class Level2(TypedDict):
level3: NestedDict
class MultipeLevels(TypedDict):
level2: Level2
NestedInvalid = TypedDict("NestedInvalid", {
"numeric-id": int,
"from": str,
})
class Root(TypedDict):
number_int: int
number_float: float
string: str
list_single_type: List[str]
list_mixed_type: List[Union[float, int, str]]
nested_dict: NestedDict
same_nested_dict: NestedDict
multipe_levels: MultipeLevels
nested_invalid: NestedInvalid
optional_items: List[Union[None, int, str]]