Type checker for Pydnatic

Warning

Experimental feature

Info

In version 0.1.1, This feature is broken. Please use it in 0.1.2 or later.

Tips

**This plugin supports type-checking to pydantic with a built-in type checker. Plus, this type-checker supplies a special feature to Pydnatic. **

This plugin provides a type-checker for pydantic.

You can use the type-checker on PyCharm's Settings (Preference -> Editor -> Inspections -> Type checker compatible with Pydantic)

This type-checker inherits from PyCharm's built-in type checker (aka Type checker).

Please disable Type checker when you enable Type checker compatible with Pydantic.

Don't use this type checker with a builtin type checker same time.

Parsable Type

Pydantic has lots of support for coercing types. However, PyCharm gives a message saying only Expected type "x," got "y" instead: When you set parsable-type on a type, then the message will be changed to Field is of type "x", "y" may not be parsable to "x"

Set parsable-type in pyproject.toml

You should create pyproject.toml in your project root. And, you define parsable-type like a example.

exapmle: pyproject.toml

[tool.pydantic-pycharm-plugin.parsable-types]

# str field may parse int and float
str = ["int", "float"]

# datetime.datetime field may parse int
"datetime.datetime" = [ "int" ]

# your_module.your_type field may parse str
"your_module.your_type" = [ "str" ]

[tool.pydantic-pycharm-plugin]
# You can set higlith level (default is "warning")
# You can select it from "warning",  "weak_warning", "disable" 
parsable-type-highlight = "warning" 

## If you set acceptable-type-highlight then, you have to set it at same depth.
acceptable-type-highlight = "disable" 

Acceptable Type

Info

This feature is in version 0.1.3 or later.

Pydantic can always parse a few types to other types. For example, int to str. It always succeeds. You can set it as an acceptable type. The message is Field is of type 'x', 'y' is set as an acceptable type in pyproject.toml. Also,You may want to disable the message.You can do it, by setting "disable" on acceptable-type-highlight.

Set acceptable-type in pyproject.toml

You should create pyproject.toml in your project root. And, you define acceptable-type like a example.

exapmle: pyproject.toml

[tool.pydantic-pycharm-plugin.acceptable-types]

# str field accepts to parse int and float
str = ["int", "float"]

# datetime.datetime field may parse int
"datetime.datetime" = [ "int" ]

[tool.pydantic-pycharm-plugin]
# You can set higlith level (default is "weak_warning")
# You can select it from "warning",  "weak_warning", "disable" 
acceptable-type-highlight = "disable" 

# If you set parsable-type-highlight then, you have to set it at same depth.
parsable-type-highlight = "warning"