core: mark custom types as cacheable to prevent warnings during queries

also use sqlalchemy.JSON type for json -- sqlite supports json since 2015, so surely it's everywhere by now

README.md

@@ -120,10 +120,10 @@ Cachew gives the best of two worlds and makes it both **easy and efficient**. Th
 
 
 # How it works
-Basically, your data objects get [flattened out](src/cachew/__init__.py#L438)
-and python types are mapped [onto sqlite types and back](src/cachew/__init__.py#L510).
+Basically, your data objects get [flattened out](src/cachew/__init__.py#L426)
+and python types are mapped [onto sqlite types and back](src/cachew/__init__.py#L498).
 
-When the function is called, cachew [computes the hash of your function's arguments ](src/cachew/__init__.py:#L837)
+When the function is called, cachew [computes the hash of your function's arguments ](src/cachew/__init__.py:#L826)
 and compares it against the previously stored hash value.
 
 - If they match, it would deserialize and yield whatever is stored in the cache database
@@ -135,18 +135,18 @@ and compares it against the previously stored hash value.
 
 
 
-* automatic schema inference: [1](src/cachew/tests/test_cachew.py#L343), [2](src/cachew/tests/test_cachew.py#L357)
+* automatic schema inference: [1](src/cachew/tests/test_cachew.py#L352), [2](src/cachew/tests/test_cachew.py#L366)
 * supported types:    
 
     * primitive: `str`, `int`, `float`, `bool`, `datetime`, `date`, `dict`, `list`, `Exception`
 
-      See [tests.test_types](src/cachew/tests/test_cachew.py#L623), [tests.test_primitive](src/cachew/tests/test_cachew.py#L670), [tests.test_dates](src/cachew/tests/test_cachew.py#L583)
-    * [Optional](src/cachew/tests/test_cachew.py#L482) types
-    * [Union](src/cachew/tests/test_cachew.py#L740) types
-    * [nested datatypes](src/cachew/tests/test_cachew.py#L399)
-    * [Exceptions](src/cachew/tests/test_cachew.py#L997)
+      See [tests.test_types](src/cachew/tests/test_cachew.py#L632), [tests.test_primitive](src/cachew/tests/test_cachew.py#L679), [tests.test_dates](src/cachew/tests/test_cachew.py#L592)
+    * [Optional](src/cachew/tests/test_cachew.py#L491) types
+    * [Union](src/cachew/tests/test_cachew.py#L749) types
+    * [nested datatypes](src/cachew/tests/test_cachew.py#L408)
+    * [Exceptions](src/cachew/tests/test_cachew.py#L1006)
 
-* detects [datatype schema changes](src/cachew/tests/test_cachew.py#L429) and discards old data automatically
+* detects [datatype schema changes](src/cachew/tests/test_cachew.py#L438) and discards old data automatically
 
 
 # Performance
@@ -157,25 +157,25 @@ During reading cache all that happens is reading rows from sqlite and mapping th
 I haven't set up proper benchmarks/performance regressions yet, so don't want to make specific claims, however that would almost certainly make your programm faster if computations take more than several seconds.
 
 
-If you want to experiment for youself, check out [tests.test_many](src/cachew/tests/test_cachew.py#L288)
+If you want to experiment for youself, check out [tests.test_many](src/cachew/tests/test_cachew.py#L297)
 
 
 
 # Using
-See [docstring](src/cachew/__init__.py#L701) for up-to-date documentation on parameters and return types. 
+See [docstring](src/cachew/__init__.py#L690) for up-to-date documentation on parameters and return types. 
 You can also use [extensive unit tests](src/cachew/tests/test_cachew.py) as a reference.
 
 Some useful (but optional) arguments of `@cachew` decorator:
 
-* `cache_path` can be a directory, or a callable that [returns a path](src/cachew/tests/test_cachew.py#L379) and depends on function's arguments.
+* `cache_path` can be a directory, or a callable that [returns a path](src/cachew/tests/test_cachew.py#L388) and depends on function's arguments.
 
    By default, `settings.DEFAULT_CACHEW_DIR` is used.
 
 * `depends_on` is a function which determines whether your inputs have changed, and the cache needs to be invalidated.
 
    By default it just uses string representation of the arguments, you can also specify a custom callable.
 
-   For instance, it can be used to [discard cache](src/cachew/tests/test_cachew.py#L93) if the input file was modified.
+   For instance, it can be used to [discard cache](src/cachew/tests/test_cachew.py#L102) if the input file was modified.
 
 * `cls` is the type that would be serialized.
 
@@ -260,7 +260,7 @@ Now you can use `@mcachew` in place of `@cachew`, and be certain things don't br
 ## Settings
 
 
-[cachew.settings](src/cachew/__init__.py#L57) exposes some parameters that allow you to control `cachew` behaviour:
+[cachew.settings](src/cachew/__init__.py#L58) exposes some parameters that allow you to control `cachew` behaviour:
 - `ENABLE`: set to `False` if you want to disable caching for without removing the decorators (useful for testing and debugging).
    You can also use [cachew.extra.disabled_cachew](src/cachew/__init__.py#L18) context manager to do it temporarily.
 - `DEFAULT_CACHEW_DIR`: override to set a different base directory. The default is the "user cache directory" (see [appdirs docs](https://github.com/ActiveState/appdirs#some-example-output)).

src/cachew/__init__.py

@@ -18,6 +18,7 @@
 import logging
 from itertools import chain, islice
 import inspect
+import json
 from datetime import datetime, date
 import stat
 import tempfile
@@ -27,7 +28,7 @@
 import sys
 import typing
 from typing import (Any, Callable, Iterator, List, NamedTuple, Optional, Tuple,
-                    Type, Union, TypeVar, Generic, Sequence, Iterable, Set, cast)
+                    Type, Union, TypeVar, Generic, Sequence, Iterable, Set, Dict, cast)
 import dataclasses
 import warnings
 
@@ -79,6 +80,8 @@ class IsoDateTime(sqlalchemy.TypeDecorator):
     # but practically, the difference seems to be pretty small, so perhaps fine for now
     impl = sqlalchemy.String
 
+    cache_ok = True
+
     @property
     def python_type(self): return datetime
 
@@ -93,7 +96,7 @@ def process_bind_param(self, value: Optional[datetime], dialect) -> Optional[str
         if tz is None:
             return iso
         try:
-            import pytz # type: ignore
+            import pytz
         except ImportError:
             self.warn_pytz()
             return iso
@@ -132,6 +135,8 @@ def warn_pytz(self) -> None:
 class IsoDate(IsoDateTime):
     impl = sqlalchemy.String
 
+    cache_ok = True
+
     @property
     def python_type(self): return date
 
@@ -143,26 +148,6 @@ def process_result_value(self, value: Optional[str], dialect) -> Optional[date]:
             return None
         return res.date()
 
-import json
-from typing import Dict
-class Json(sqlalchemy.TypeDecorator):
-    impl = sqlalchemy.String
-
-    @property
-    def python_type(self): return Dict
-
-    def process_literal_param(self, value, dialect): raise NotImplementedError() # make pylint happy
-
-    def process_bind_param(self, value: Optional[Dict], dialect) -> Optional[str]:
-        if value is None:
-            return None
-        return json.dumps(value)
-
-    def process_result_value(self, value: Optional[str], dialect) -> Optional[datetime]:
-        if value is None:
-            return None
-        return json.loads(value)
-
 
 jtypes = (int, float, bool, type(None))
 class ExceptionAdapter(sqlalchemy.TypeDecorator):
@@ -173,7 +158,9 @@ class ExceptionAdapter(sqlalchemy.TypeDecorator):
 
     I elaborate on it here: [mypy-driven error handling](https://beepb00p.xyz/mypy-error-handling.html#kiss).
     '''
-    impl = Json
+    impl = sqlalchemy.JSON
+
+    cache_ok = True
 
     @property
     def python_type(self): return Exception
@@ -207,8 +194,8 @@ def process_result_value(self, value: Optional[str], dialect) -> Optional[Except
     bool     : sqlalchemy.Boolean,
     datetime : IsoDateTime,
     date     : IsoDate,
-    dict     : Json,
-    list     : Json,
+    dict     : sqlalchemy.JSON,
+    list     : sqlalchemy.JSON,
     Exception: ExceptionAdapter,
 }