co3/examples/mapper.ipynb

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{
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"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": [
"from co3 import Mapper\n",
"\n",
"import vegetables"
]
},
{
"cell_type": "markdown",
"id": "c0914069-7f3c-4213-8d34-f7566033e054",
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"## Development notes\n",
"- No registry actually needs to take place if there's a default type2component map or one supplied on creation. Can just collect right out of the gate\n",
"- Need connective function (type to collation) and attribute map. Do we need to this with a subclass? If a func is passed in on init, I can type it appropriately I guess `Callable[[type[CO3],str,str|None],dict]`"
]
},
{
"cell_type": "code",
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"id": "7d80f7b9-7458-4ad4-8c1a-3ea56e796b4e",
"metadata": {},
"outputs": [],
"source": [
"vegetable_mapper = Mapper(\n",
" vegetables.Vegetable,\n",
" vegetables.vegetable_schema\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d24d31b4-c4a6-4a1e-8bea-c44378aadfdd",
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"source": [
"# not valid; tables need to be wrapped in CO3 Components\n",
"vegetable_mapper.attach(\n",
" vegetables.Vegetable,\n",
" vegetables.vegetable_table,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "f9408562-bf50-4522-909c-318557f85948",
"metadata": {},
"outputs": [],
"source": [
"# manually attach component\n",
"vegetable_mapper.attach(\n",
" vegetables.Tomato,\n",
" vegetables.vegetable_schema.get_component('tomato'),\n",
" coll_groups={\n",
" 'aging': vegetables.vegetable_schema.get_component('tomato_aging_states'),\n",
" 'cooking': vegetables.vegetable_schema.get_component('tomato_cooking_states'),\n",
" },\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "05fdd404-87ee-4187-832f-2305272758ae",
"metadata": {},
"outputs": [],
"source": [
"# attach by name in schema\n",
"vegetable_mapper.attach(\n",
" vegetables.Tomato,\n",
" 'tomato',\n",
" coll_groups={\n",
" 'aging': 'tomato_aging_states',\n",
" 'cooking': 'tomato_cooking_states',\n",
" },\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e9b6af49-a69d-41cc-beae-1b6f171cd2f5",
"metadata": {},
"outputs": [],
"source": [
"# attach entire type hierarchy w/ type->name map\n",
"vegetable_mapper.attach_hierarchy(\n",
"# this might make more sense during init\n",
" lambda x:x.__name__.lower())\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "2e4336ab-5b5f-484d-815d-164d4b6f40a0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'co3_root': vegetables.Vegetable,\n",
" 'schema': <co3.schemas.SQLSchema at 0x74ac03f5c8c0>,\n",
" 'collector': <co3.collector.Collector at 0x74ac0357ae70>,\n",
" 'composer': <co3.composer.Composer at 0x74ac0357a4b0>,\n",
" 'attribute_comps': {vegetables.Tomato: <co3.components.SQLTable at 0x74ac09d4a720>},\n",
" 'collation_groups': defaultdict(dict,\n",
" {vegetables.Tomato: {'aging': <co3.components.SQLTable at 0x74ac03f5cad0>,\n",
" 'cooking': <co3.components.SQLTable at 0x74ac03f5cb00>}})}"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vars(vegetable_mapper)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c16786d4-0b71-42d9-97f7-7893c542104e",
"metadata": {},
"outputs": [],
"source": [
"tomato = vegetables.Tomato('t1', 5)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "884d6753-c763-4e71-824a-711436e203e1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<vegetables.Tomato at 0x74ac082bacc0>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tomato"
]
},
{
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"metadata": {},
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"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "co3",
"language": "python",
"name": "co3"
},
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"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"version": "3.12.2"
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