clean up Database/Accessor/Manager interaction, refine Mapper group maps

examples/.ipynb_checkpoints/database-checkpoint.ipynb

@@ -1,6 +1,204 @@
 {
- "cells": [],
- "metadata": {},
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6f6fbc7e-4fb9-4353-b2ee-9ea819a3c896",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/smgr/.pyenv/versions/co4/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import vegetables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "88fd0ea8-9c94-4569-a51b-823a04f32f55",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'age': 3}"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tomato = vegetables.Tomato('t1', 5)\n",
+    "\n",
+    "# test a register collation action\n",
+    "tomato.collate('ripe')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "348926d9-7137-4eff-a919-508788553dd2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['afff61ec-e0b0-44bb-9f0d-06008a82f6a5',\n",
+       " '5edfa13c-0eb1-4bbc-b55e-1550ff7df3d2',\n",
+       " '4568a2d4-eb41-4b15-9a29-e3e22906c661']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vegetables.vegetable_mapper.collect(tomato, ['ripe'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "4e5e7319-11bf-4051-951b-08c84e9f3874",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Component (SQLTable)> vegetable+tomato+tomato_aging_states+tomato_cooking_states"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vegetables.vegetable_mapper.compose(tomato, action_groups=['aging', 'cooking'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "aa290686-8074-4038-a3cc-ce6817844653",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Column('id', Integer(), table=<vegetable>, primary_key=True, nullable=False),\n",
+       " Column('name', String(), table=<vegetable>),\n",
+       " Column('color', String(), table=<vegetable>),\n",
+       " Column('id', Integer(), table=<tomato>, primary_key=True, nullable=False),\n",
+       " Column('name', String(), ForeignKey('vegetable.name'), table=<tomato>),\n",
+       " Column('radius', Integer(), table=<tomato>),\n",
+       " Column('id', Integer(), table=<tomato_aging_states>, primary_key=True, nullable=False),\n",
+       " Column('name', String(), ForeignKey('tomato.name'), table=<tomato_aging_states>),\n",
+       " Column('state', String(), table=<tomato_aging_states>),\n",
+       " Column('age', Integer(), table=<tomato_aging_states>)]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(vegetables.vegetable_mapper.compose(tomato, action_groups=['aging']).obj.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "f3c7e37d-ba9e-4bae-ae44-adc922bf5f4c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(vegetables.Tomato, vegetables.Vegetable, co3.co3.CO3, object)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tomato.__class__.__mro__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c21d2c54-39e2-4de3-93bc-763896ed348e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from co3.databases import SQLDatabase\n",
+    "\n",
+    "db = SQLDatabase('sqlite://', echo=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a785d202-99d3-4ae7-859e-ee22b481f8df",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<contextlib._GeneratorContextManager at 0x7dd5c619be60>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "db.recreate(vegetable_schema) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cda01cb0-1666-4cb1-aa64-bcdca871aff5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "co3",
+   "language": "python",
+   "name": "co3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }

examples/.ipynb_checkpoints/vegetables-checkpoint.py

@@ -6,7 +6,7 @@ import random
 import sqlalchemy as sa
 
 from co3.schemas import SQLSchema
-from co3 import CO3, collate, Mapper
+from co3 import CO3, collate, Mapper, ComposableMapper
 from co3 import util
 
 
@@ -101,5 +101,35 @@ tomato_cooking_table = sa.Table(
     sa.Column('pieces', sa.Integer),
 )
 vegetable_schema = SQLSchema.from_metadata(metadata)
-vegetable_mapper = Mapper(vegetable_schema)
+
+def general_compose_map(c1, c2):
+    return c1.obj.c.name == c2.obj.c.name
+    
+vegetable_mapper = ComposableMapper(
+    vegetable_schema,
+    attr_compose_map=general_compose_map,
+    coll_compose_map=general_compose_map,
+)
+
+def attr_name_map(cls):
+    return f'{cls.__name__.lower()}'
+
+def coll_name_map(cls, action_group):
+    return f'{cls.__name__.lower()}_{action_group}_states'
+
+vegetable_mapper.attach_many(
+    type_list,
+    attr_name_map,
+    coll_name_map,
+)
+
+'''
+new mapping type for Mapper attachment:
+
+Callable[ [type[CO3], str|None], tuple[str, tuple[str], tuple[str]]]
+
+tail tuples to associate column names from central table to collation
+
+this should complete the auto-compose horizontally
+'''