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‎.gitignore

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env/

‎02-Installing SQLAlchemy and connecting to database.ipynb

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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": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"from sqlalchemy import create_engine\n",
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"\n",
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"# Connecting to MySQL server at localhost using PyMySQL DBAPI \n",
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"# engine = create_engine(\"mysql+pymysql://root:pass@localhost/mydb\")\n",
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"\n",
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"# Connecting to MySQL server at 23.92.23.113 using mysql-python DBAPI \n",
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"# engine = create_engine(\"mysql+mysqldb://root:pass@23.92.23.113/mydb\")\n",
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"\n",
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"# Connecting to PostgreSQL server at localhost using psycopg2 DBAPI \n",
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"engine = create_engine(\"postgresql+psycopg2://root:pass@localhost/mydb\")\n",
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"\n",
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"# Connecting to Oracle server at localhost using cx-Oracle DBAPI\n",
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"# engine = create_engine(\"oracle+cx_oracle://root:pass@localhost/mydb\")\n",
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"\n",
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"# Connecting to MSSQL server at localhost using PyODBC DBAPI\n",
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"# engine = create_engine(\"oracle+pyodbc://root:pass@localhost/mydb\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# from sqlalchemy import create_engine\n",
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"\n",
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"# engine = create_engine('sqlite:///sqlite3.db') # using relative path\n",
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"# engine = create_engine('sqlite:////path/to/sqlite3.db') # using absolute path"
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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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"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": 11,
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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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"Engine(postgres+psycopg2://postgres:***@localhost/sqlalchemy_tuts)\n"
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]
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}
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],
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"source": [
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"from sqlalchemy import create_engine\n",
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"\n",
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"engine = create_engine(\"postgres+psycopg2://postgres:pass@localhost/sqlalchemy_tuts\")\n",
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"engine.connect()\n",
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"\n",
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"print(engine)"
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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": 12,
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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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"2018-07-07 18:39:14,402 INFO sqlalchemy.engine.base.Engine select version()\n",
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"2018-07-07 18:39:14,403 INFO sqlalchemy.engine.base.Engine {}\n",
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"2018-07-07 18:39:14,408 INFO sqlalchemy.engine.base.Engine select current_schema()\n",
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"2018-07-07 18:39:14,410 INFO sqlalchemy.engine.base.Engine {}\n",
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"2018-07-07 18:39:14,413 INFO sqlalchemy.engine.base.Engine SELECT CAST('test plain returns' AS VARCHAR(60)) AS anon_1\n",
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"2018-07-07 18:39:14,416 INFO sqlalchemy.engine.base.Engine {}\n",
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"2018-07-07 18:39:14,419 INFO sqlalchemy.engine.base.Engine SELECT CAST('test unicode returns' AS VARCHAR(60)) AS anon_1\n",
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"2018-07-07 18:39:14,421 INFO sqlalchemy.engine.base.Engine {}\n",
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"2018-07-07 18:39:14,423 INFO sqlalchemy.engine.base.Engine show standard_conforming_strings\n",
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"2018-07-07 18:39:14,424 INFO sqlalchemy.engine.base.Engine {}\n",
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"Engine(postgres+psycopg2://postgres:***@localhost/sqlalchemy_tuts)\n"
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]
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}
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],
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"source": [
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"from sqlalchemy import create_engine\n",
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"\n",
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"engine = create_engine(\n",
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" \"postgres+psycopg2://postgres:pass@localhost/sqlalchemy_tuts\", \n",
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" echo=True, pool_size=6, max_overflow=10, encoding='latin1'\n",
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")\n",
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"\n",
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"engine.connect()\n",
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"\n",
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"print(engine)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎03-Defining Schema in SQLAlchemy Core.ipynb

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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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"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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"posts\n",
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"users\n",
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"-------------\n",
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"users\n",
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"posts\n"
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]
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}
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],
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"source": [
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"from sqlalchemy import create_engine, MetaData, Table, Integer, String, Column, Text, DateTime, Boolean, ForeignKey\n",
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"\n",
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"metadata = MetaData()\n",
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"\n",
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"user = Table('users', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('user', String(200), nullable=False),\n",
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")\n",
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"\n",
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"posts = Table('posts', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('post_title', String(200), nullable=False),\n",
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" Column('post_slug', String(200), nullable=False),\n",
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" Column('content', Text(), nullable=False),\n",
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" Column('user_id', Integer(), ForeignKey(\"users.id\")),\n",
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")\n",
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"\n",
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"for t in metadata.tables:\n",
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" print(metadata.tables[t])\n",
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"\n",
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"print('-------------') \n",
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"\n",
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"for t in metadata.sorted_tables:\n",
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" print(t.name) # print table name"
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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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"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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"['posts.id', 'posts.post_title', 'posts.post_slug', 'posts.content', 'posts.user_id']\n",
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"['posts.id', 'posts.post_title', 'posts.post_slug', 'posts.content', 'posts.user_id']\n",
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"{ForeignKey('users.id')}\n",
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"PrimaryKeyConstraint(Column('id', Integer(), table=<posts>, primary_key=True, nullable=False))\n",
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"MetaData(bind=None)\n",
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"post_title\n",
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"VARCHAR(200)\n"
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]
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}
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],
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"source": [
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"print(posts.columns) # return a list of columns\n",
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"print(posts.c) # same as posts.columns\n",
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"print(posts.foreign_keys) # returns a set containing foreign keys on the table\n",
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"print(posts.primary_key) # returns the primary key of the column\n",
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"print(posts.metadata) # get the MetaData object from the table\n",
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"print(posts.columns.post_title.name) # returns the name of the column\n",
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"print(posts.columns.post_title.type) # returns the type of the column"
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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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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/pp/project/sqlalchemy/env/lib/python3.5/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
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" \"\"\")\n"
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]
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}
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],
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"source": [
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"from sqlalchemy import create_engine, MetaData, Table, Integer, String, \\\n",
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" Column, DateTime, ForeignKey, Numeric, CheckConstraint\n",
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"\n",
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"from datetime import datetime\n",
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"\n",
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"metadata = MetaData()\n",
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"\n",
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"engine = create_engine(\"postgres+psycopg2://postgres:pass@localhost/sqlalchemy_tuts\")\n",
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"\n",
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"customers = Table('customers', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('first_name', String(100), nullable=False),\n",
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" Column('last_name', String(100), nullable=False),\n",
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" Column('username', String(50), nullable=False),\n",
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" Column('email', String(200), nullable=False),\n",
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" Column('address', String(200), nullable=False),\n",
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" Column('town', String(50), nullable=False),\n",
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" Column('created_on', DateTime(), default=datetime.now),\n",
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" Column('updated_on', DateTime(), default=datetime.now, onupdate=datetime.now)\n",
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")\n",
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"\n",
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"\n",
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"items = Table('items', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('name', String(200), nullable=False),\n",
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" Column('cost_price', Numeric(10, 2), nullable=False),\n",
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" Column('selling_price', Numeric(10, 2), nullable=False),\n",
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" Column('quantity', Integer(), nullable=False),\n",
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" CheckConstraint('quantity > 0', name='quantity_check')\n",
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")\n",
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"\n",
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"\n",
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"orders = Table('orders', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('customer_id', ForeignKey('customers.id')),\n",
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" Column('date_placed', DateTime(), default=datetime.now),\n",
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" Column('date_shipped', DateTime())\n",
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")\n",
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"\n",
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"\n",
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"order_lines = Table('order_lines', metadata,\n",
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" Column('id', Integer(), primary_key=True),\n",
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" Column('order_id', ForeignKey('orders.id')),\n",
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" Column('item_id', ForeignKey('items.id')),\n",
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" Column('quantity', Integer())\n",
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")\n",
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"\n",
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"\n",
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"metadata.create_all(engine)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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