Mod: db improved
This commit is contained in:
parent
64a5cf1a6d
commit
c35d5cfe3c
@ -65,8 +65,6 @@ class UltimateRunner(object):
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def start(self, queue: list = None, nprocs: int = None):
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nprocs = nprocs or self.config["nprocs"]
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runners = [ runner.pipeline for runner in self.queue ]
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args = [[self.config["stage"]]] * len(self.queue)
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parallel = ParallelRunner(nprocs = nprocs)
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parallel.start()
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@ -1,4 +1,7 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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from .database import *
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from .models import __database__, __models__
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database = __database__
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tables = __models__
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@ -3,38 +3,42 @@
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# License: GNU GPL version 3, see the file "LICENSE" for details.
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import os
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from .models import (
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sqliteDB,
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Execution,
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Shape,
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Mesh,
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FlowOnephase
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)
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from peewee import SqliteDatabase
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class Database(SqliteDatabase):
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def __init__(self, *args, **kwargs):
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self.filepath = None
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self.pragmas_ = kwargs.get("pragmas", { "foreign_keys": 1 })
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self.field_types_ = kwargs.get("field_types", { "list": "text" })
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self.autoconnect_ = kwargs.get("autoconnect", False)
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class Database(object):
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def __init__(self, filename: str):
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self.filename = filename
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self.database = sqliteDB
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def setup(self):
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path = os.path.abspath(self.filename)
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#os.makedirs(path, exist_ok = True)
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self.database.init(
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path,
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pragmas = { "foreign_keys": 1 },
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field_types = { "list": "text" },
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autoconnect = False
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SqliteDatabase.__init__(
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self,
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None,
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pragmas = kwargs.get("pragmas", { "foreign_keys": 1 }),
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field_types = kwargs.get("field_types", { "list": "text" }),
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autoconnect = kwargs.get("autoconnect", False)
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)
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if not os.path.exists(path):
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with self.database:
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self.database.create_tables([Execution])
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self.database.create_tables([
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Shape,
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Mesh,
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FlowOnephase
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])
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@property
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def tables(self):
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return models.__models__
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def setup(self, filename: str):
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if not self.filepath:
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self.filepath = os.path.abspath(filename) if filename else None
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self.init(
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self.filepath,
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pragmas = self.pragmas_,
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#field_types = self.field_types_,
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#autoconnect = self.autoconnect_
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)
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print(self.tables)
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self.connect()
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self.create_tables(self.tables)
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self.close()
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# NOTE: avoid circular or partial import
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from . import models
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@ -11,13 +11,10 @@ from peewee import (
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TimeField, DateTimeField
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)
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from anisotropy.database.utils import JSONField
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from .database import Database
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sqliteDB = SqliteDatabase(
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None,
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pragmas = { "foreign_keys": 1 },
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field_types = { "list": "text" },
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autoconnect = False
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)
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__database__ = Database()
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class Execution(Model):
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exec_id = AutoField()
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@ -26,7 +23,7 @@ class Execution(Model):
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executionTime = TimeField(null = True)
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class Meta:
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database = sqliteDB
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database = __database__
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table_name = "executions"
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@ -55,9 +52,9 @@ class Shape(Model):
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porosityRounded = FloatField(null = True)
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class Meta:
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database = sqliteDB
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database = __database__
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table_name = "shapes"
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depends_on = Execution
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#depends_on = Execution
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class Mesh(Model):
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@ -77,9 +74,9 @@ class Mesh(Model):
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class Meta:
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database = sqliteDB
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database = __database__
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table_name = "meshes"
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depends_on = Execution
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#depends_on = Execution
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class FlowOnephase(Model):
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@ -93,8 +90,14 @@ class FlowOnephase(Model):
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permeability = FloatField(null = True)
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class Meta:
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database = sqliteDB
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database = __database__
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table_name = "flows"
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depends_on = Execution
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#depends_on = Execution
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__models__ = [
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Execution,
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Shape,
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Mesh,
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FlowOnephase
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]
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@ -1,662 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "c4317e7e-d7b9-4bec-9cad-e26a377458b8",
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"metadata": {},
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"outputs": [],
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"source": [
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"from peewee import (\n",
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" SqliteDatabase, JOIN, \n",
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" Model, Field, \n",
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" AutoField, ForeignKeyField, \n",
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" TextField, FloatField, \n",
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" IntegerField, BooleanField, \n",
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" TimeField\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "db03ea1b-e950-4f0b-8c4f-c137417981ca",
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"metadata": {},
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"outputs": [],
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"source": [
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"db = SqliteDatabase(\"test_db.db\", pragmas = { \"foreign_keys\" : 1, \"journal_mode\": \"wal\" })"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "e904a64b-9108-414b-974b-2dbf96018cf5",
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"metadata": {},
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"outputs": [],
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"source": [
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"class ListField(Field):\n",
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" field_type = \"list\"\n",
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"\n",
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" def db_value(self, value):\n",
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" return str(value)\n",
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"\n",
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" def python_value(self, value):\n",
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" pval = []\n",
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"\n",
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" for entry in value[1 : -1].split(\",\"):\n",
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" try:\n",
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" pval.append(float(entry))\n",
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"\n",
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" except:\n",
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" pval.append(entry.strip().replace(\"'\", \"\"))\n",
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"\n",
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" return pval"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "a6049589-dd33-4cfa-8434-1c00285c01e0",
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"metadata": {},
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"outputs": [],
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"source": [
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"class Structure(Model):\n",
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" structure_id = AutoField()\n",
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"\n",
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" type = TextField()\n",
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" direction = ListField()\n",
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" theta = FloatField()\n",
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"\n",
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" r0 = FloatField(null = True)\n",
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" L = FloatField(null = True)\n",
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" radius = FloatField(null = True)\n",
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"\n",
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" filletsEnabled = BooleanField(null = True)\n",
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" fillets = FloatField(null = True)\n",
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" #path = TextField()\n",
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" \n",
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" class Meta:\n",
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" database = db\n",
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" db_table = \"structures\"\n",
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"\n",
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"\n",
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"class Mesh(Model):\n",
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" mesh_id = AutoField()\n",
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" structure_id = ForeignKeyField(Structure, backref = \"meshes\")\n",
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"\n",
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" maxSize = FloatField(null = True) \n",
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"\n",
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" class Meta:\n",
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" database = db\n",
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" db_table = \"meshes\"\n",
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" depends_on = Structure"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "77c8b505-8b72-4f41-9f6d-d0b4e44884ea",
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"metadata": {},
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"outputs": [],
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"source": [
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"db.create_tables([Structure, Mesh])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"id": "708acdf5-a604-44c1-8631-d274d0273c1b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "62c1c0a0-74ae-43cc-bc75-1fbd353540ae",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1"
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]
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},
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"s1 = Structure(type = \"simple\", direction = [1, 0, 0], theta = 0.01)\n",
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"s1.save()\n",
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"\n",
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"m1 = Mesh(structure_id = s1, maxSize = 1e-2)\n",
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"m1.save()\n",
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"\n",
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"#db.commit()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "0e03bc08-94ea-4680-8223-dbafc13dcfe7",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"s1.theta = 0.12\n",
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"s1.save()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"id": "a2f68e62-0324-4ec2-8113-47cf6e1dc5bd",
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"metadata": {},
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"outputs": [],
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"source": [
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"ss = numpy.array([\n",
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" Structure(type = \"simple\", direction = [1, 0, 0], theta = 0.01),\n",
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" Structure(type = \"simple\", direction = [1, 0, 0], theta = 0.02)\n",
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"])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"id": "6683ea42-5fdc-4b33-b709-5ea31ae5567f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dtype('O')"
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]
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},
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ss.dtype"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"id": "83cc7bde-e003-4f2c-ab9b-f9e37634c374",
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"metadata": {},
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"outputs": [],
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"source": [
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"Structure.bulk_create(ss)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"id": "962010a5-68b8-4711-a067-962677aa406d",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1 simple [1.0, 0.0, 0.0] 0.12\n",
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"2 simple [1.0, 0.0, 0.0] 0.01\n",
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"3 simple [1.0, 0.0, 0.0] 0.01\n",
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"4 simple [1.0, 0.0, 0.0] 0.01\n",
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"5 simple [1.0, 0.0, 0.0] 0.01\n",
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"6 simple [1.0, 0.0, 0.0] 0.01\n",
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"7 simple [1.0, 0.0, 0.0] 0.01\n",
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"8 simple [1.0, 0.0, 0.0] 0.01\n",
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"9 simple [1.0, 0.0, 0.0] 0.01\n",
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"10 simple [1.0, 0.0, 0.0] 0.01\n",
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"11 simple [1.0, 0.0, 0.0] 0.01\n",
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"12 simple [1.0, 0.0, 0.0] 0.02\n"
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]
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}
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],
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"source": [
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"for row in Structure.select():\n",
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" print(row.structure_id, row.type, row.direction, row.theta)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "a5fc7787-7045-4bb1-a846-5fff8b21417c",
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"metadata": {},
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"outputs": [],
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"source": [
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"sel = Structure.select()[-1]\n",
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"sel2 = sel.meshes.select()[-1]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "480edddc-478e-47ce-8678-490455badd35",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Mesh: 8>"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sel2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "8286c287-f89d-40bd-8045-a854013915c2",
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"metadata": {},
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"outputs": [],
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"source": [
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"sel3 = Structure.select().dicts().get()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "180b07cb-6c10-4390-9f9c-07bf9f74f39e",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'structure_id': 1,\n",
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" 'type': 'simple',\n",
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" 'direction': [1.0, 0.0, 0.0],\n",
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" 'theta': 0.12,\n",
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" 'r0': None,\n",
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" 'L': None,\n",
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" 'radius': None,\n",
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" 'filletsEnabled': None,\n",
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" 'fillets': None}"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sel3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "448c99bf-2b6f-43de-92d3-dc1267e766d3",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 47,
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"id": "6f9e3cfd-8945-4738-9bf6-704bca131a9a",
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"metadata": {},
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"outputs": [],
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"source": [
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"db = SqliteDatabase(\"newtest2.db\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"id": "ff82a760-902a-416d-a5d6-775ddb418a9c",
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"metadata": {},
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"outputs": [],
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"source": [
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"class Test(Model):\n",
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" test_id = AutoField()\n",
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" text = TextField(null = True)\n",
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" \n",
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" class Meta:\n",
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" database = db\n",
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"\n",
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"db.create_tables([Test])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"id": "a7f89828-9a8d-43ab-92d4-681fd7cbc416",
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"metadata": {},
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"outputs": [
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{
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"data": {
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||||
"text/plain": [
|
||||
"False"
|
||||
]
|
||||
},
|
||||
"execution_count": 49,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"db.is_closed()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 50,
|
||||
"id": "3cf907ef-8988-4f08-b1c1-6c3637cefd29",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"1"
|
||||
]
|
||||
},
|
||||
"execution_count": 50,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"test1 = Test(text = \"hola\")\n",
|
||||
"test1.save()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 51,
|
||||
"id": "0c91e698-a07b-4b52-bc9d-51a37e179cee",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"test2 = Test.create(text = \"asd\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 52,
|
||||
"id": "1deee68c-07b7-4003-a29f-1e726aefc9e0",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"1 hola\n",
|
||||
"2 asd\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for row in Test.select():\n",
|
||||
" print(row.test_id, row.text)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 53,
|
||||
"id": "c59d0a44-b907-427a-91d6-d9c9c72c8bdd",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from multiprocessing import Process, Queue"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 54,
|
||||
"id": "88212490-2dd1-4058-80fe-57ae30bf38cc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def queue(cmd, qin, qout, *args):\n",
|
||||
" while True:\n",
|
||||
" pos, var = qin.get()\n",
|
||||
" \n",
|
||||
" if pos is None:\n",
|
||||
" break\n",
|
||||
"\n",
|
||||
" res = cmd(*var, *args)\n",
|
||||
"\n",
|
||||
" qout.put((pos, res))\n",
|
||||
"\n",
|
||||
" return"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 55,
|
||||
"id": "df6568c8-595d-4c35-9560-16bfe8e3a915",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def db_save(table):\n",
|
||||
" with db.atomic():\n",
|
||||
" return table.save()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 56,
|
||||
"id": "53fa9e79-e3e9-4758-a434-4f411dd15858",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"qin = Queue(1)\n",
|
||||
"qout = Queue()\n",
|
||||
"procs = []\n",
|
||||
"nprocs = 10\n",
|
||||
"\n",
|
||||
"for n in range(nprocs):\n",
|
||||
" args = (db_save, qin, qout)\n",
|
||||
"\n",
|
||||
" procs.append(Process(target = queue, args = args))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 57,
|
||||
"id": "86a39b3c-bbb9-4c7e-938b-3330ad7406b9",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"for p in procs:\n",
|
||||
" p.daemon = True\n",
|
||||
" p.start()\n",
|
||||
"\n",
|
||||
"var = []\n",
|
||||
"for n in range(50):\n",
|
||||
" var.append([Test(text = f\"test_{ n }\")])\n",
|
||||
"\n",
|
||||
"for n in range(len(var)):\n",
|
||||
" qin.put((n, var[n]))\n",
|
||||
"\n",
|
||||
"for _ in range(nprocs):\n",
|
||||
" qin.put((None, None))\n",
|
||||
"\n",
|
||||
"results = [[] for n in range(len(var))]\n",
|
||||
"\n",
|
||||
"for n in range(len(var)):\n",
|
||||
" index, res = qout.get() \n",
|
||||
" results[index] = res\n",
|
||||
"\n",
|
||||
"for p in procs:\n",
|
||||
" p.join()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 58,
|
||||
"id": "38e46264-7a61-4215-afe6-827b835ca82b",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"0"
|
||||
]
|
||||
},
|
||||
"execution_count": 58,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"procs[0].exitcode"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 59,
|
||||
"id": "d8da8120-ba3e-44d3-9b9b-78f040c957c0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"test3 = Test.create(text = \"afterproc\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 60,
|
||||
"id": "c716656c-7aaa-40da-8582-2311f1dd5314",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"1 hola\n",
|
||||
"2 asd\n",
|
||||
"3 test_1\n",
|
||||
"4 test_0\n",
|
||||
"5 test_11\n",
|
||||
"6 test_12\n",
|
||||
"7 test_13\n",
|
||||
"8 test_3\n",
|
||||
"9 test_9\n",
|
||||
"10 test_16\n",
|
||||
"11 test_2\n",
|
||||
"12 test_7\n",
|
||||
"13 test_19\n",
|
||||
"14 test_20\n",
|
||||
"15 test_4\n",
|
||||
"16 test_21\n",
|
||||
"17 test_23\n",
|
||||
"18 test_24\n",
|
||||
"19 test_25\n",
|
||||
"20 test_26\n",
|
||||
"21 test_27\n",
|
||||
"22 test_28\n",
|
||||
"23 test_18\n",
|
||||
"24 test_30\n",
|
||||
"25 test_31\n",
|
||||
"26 test_32\n",
|
||||
"27 test_14\n",
|
||||
"28 test_34\n",
|
||||
"29 test_35\n",
|
||||
"30 test_6\n",
|
||||
"31 test_37\n",
|
||||
"32 test_38\n",
|
||||
"33 test_39\n",
|
||||
"34 test_40\n",
|
||||
"35 test_41\n",
|
||||
"36 test_36\n",
|
||||
"37 test_43\n",
|
||||
"38 test_44\n",
|
||||
"39 test_42\n",
|
||||
"40 test_46\n",
|
||||
"41 test_47\n",
|
||||
"42 test_48\n",
|
||||
"43 test_49\n",
|
||||
"44 test_45\n",
|
||||
"45 test_29\n",
|
||||
"46 test_5\n",
|
||||
"47 test_10\n",
|
||||
"48 test_15\n",
|
||||
"49 test_17\n",
|
||||
"50 test_33\n",
|
||||
"51 test_22\n",
|
||||
"52 test_8\n",
|
||||
"53 afterproc\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for row in Test.select():\n",
|
||||
" print(row.test_id, row.text)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 64,
|
||||
"id": "f46377ad-0af5-4acf-95bb-955e327f51e8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<peewee.SqliteDatabase at 0x7f4cdbc08f70>"
|
||||
]
|
||||
},
|
||||
"execution_count": 64,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"db"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "79a02231-365d-4a20-8899-6b5e8dbc8489",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@ -14,26 +14,21 @@ class TestDatabase(unittest.TestCase):
|
||||
|
||||
def test_setup(self):
|
||||
filepath = os.path.join(self.outputPath, "test_database.db")
|
||||
tables = [
|
||||
self.database.Execution,
|
||||
self.database.Physics,
|
||||
self.database.Shape,
|
||||
self.database.Mesh,
|
||||
self.database.Flow
|
||||
]
|
||||
db = self.database.Database(filepath)
|
||||
db.setup()
|
||||
|
||||
db = self.database.database
|
||||
db.setup(filepath)
|
||||
|
||||
self.assertTrue(
|
||||
os.path.exists(filepath) and os.path.isfile(filepath),
|
||||
"database wasn't created"
|
||||
)
|
||||
|
||||
for table in tables:
|
||||
with db:
|
||||
for table in db.tables:
|
||||
self.assertTrue(table.table_exists())
|
||||
|
||||
def tearDown(self):
|
||||
pass
|
||||
os.removedirs(os.outputPath)
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user