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+ SQLAlchemy
-Data Science @ Statnett
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- SQLAlchemy
+Data Engineering @ Statnett
-Simeon Simeonov
-Simeon Simeonov
+ -Agenda
+Agenda
-
-
- SQLAlchemy - Design & overview -
- SQLAlchemy - A small practical example -
- Q & A +
- SQLAlchemy - Design & overview +
- SQLAlchemy - A small practical example +
- Q & A
What is SQLAlchemy?
+What is SQLAlchemy?
-SQLAlchemy is a Python library created by Mike Bayer to provide a high-level Pythonic interface to RDBMS such as PostgreSQL, SQLite, MySQL, Oracle, DB2.
-SQLAlchemy includes RDBMS-independent SQL expression language and an object-relational mapper (ORM).
-SQLAlchemy is a Python library created by Mike Bayer to provide a high-level Pythonic interface to RDBMS such as PostgreSQL, SQLite, MySQL, Oracle, DB2.
+SQLAlchemy includes RDBMS-independent SQL expression language and an object-relational mapper (ORM).
+Why use SQLAlchemy?
+Why use SQLAlchemy?
-
-
free software - free as in "freedom" (MIT licensed)
- portability - the programming interface is independent of the type of RDBMS and connector used
- security - no more SQL injections
- abstraction - no need to bother with complex JOINs
- object-orientation - you work with objects instead of tables and rows
- performance - exploits the likehood of reusing a particular query
- flexibility - you can override almost anything
+ free software - free as in "freedom" (MIT licensed)
+ portability - the programming interface is independent of the type of RDBMS and connector used
+ security - no more SQL injections
+ abstraction - no need to bother with complex JOINs
+ object-orientation - you work with objects instead of tables and rows
+ performance - exploits the likehood of reusing a particular query
+ flexibility - you can override almost anything
Basic architecture
-SQLAlchemy consists of several components, including the ORM.
--
-
- Engine- manages the connection pool and the RDBMS-independent SQL dialect layer -
- MetaData - used to collect and organize information about your table layout (schema) -
- SQL expression language - provides an API to execute your queries and updates against your tables, all from Python, and all in a database-independent way (low-level interface) -
- ORM - provides a convenient way to add database persistence to your Python objects without requiring you to design your objects around the database, or the database around the objects (high-level interface) -
- Session - establishes all conversations with the RDBMS and represents a "holding zone" for all the objects which you've loaded or associated with it during its lifespan -
- Example
-SQLAlchemy gives us the choice between classical mapping and the newer declarative mapping
-
-
- import sqlalchemy
- sqlalchemy.__version__
- # Out: '1.3.23'
-
- from sqlalchemy import create_engine
-
- # engine = create_engine("postgresql+psycopg2://user:zipassword@localhost/mydb" , echo=True)
- # The string form of the URL is dialect+driver://user:password@host/dbname[?key=value..],
- # where dialect is a database name such as mysql, oracle, postgresql, etc.,
- # and driver the name of a DBAPI, such as psycopg2, pyodbc, cx_oracle
- # The echo flag is a shortcut to setting up SQLAlchemy logging,
- # which is accomplished via Python’s standard logging module.
- # engine = create_engine("sqlite:///library.db", echo=True)
- engine = create_engine("sqlite:///:memory:", echo=True)
-
- from sqlalchemy import Column, ForeignKey, Integer, String, Table
-
- metadata = MetaData()
-
- authors_table = Table(
- "authors",
- metadata,
- Column("author_id", Integer, primary_key=True),
- Column("name", String),
- ) # Column("name", String(50)) is possible
-
- books_table = Table(
- "books",
- metadata,
- Column("book_id", Integer, primary_key=True),
- Column("title", String),
- Column("description", String),
- Column("author_id", ForeignKey('authors.author_id')),
- )
-
- metadata.create_all(engine) # creates the tables
-
-
- Example (cont...)
-Use of SQL expression language
-
-
- insert_stmt = authors_table.insert(bind=engine)
- type(insert_stmt)
- # Out: <class 'sqlalchemy.sql.expression.Insert'>
- print(insert_stmt)
- # Out: INSERT INTO authors (id, name) VALUES (:id,:name)
-
- compiled_stmt = insert_stmt.compile()
- print(compiled_stmt.params)
- # Out: {'id': None, 'name': None}
-
- insert_stmt.execute(name="Alexandre Dumas") # insert a single entry
- insert_stmt.execute([{"name": "Mr X"}, {"name": "Mr Y"}]) # a list of entries
-
- metadata.bind = engine # no need to explicitly bind the engine from now on
- select_stmt = authors_table.select(authors_table.c.id==2)
- result = select_stmt.execute()
- result.fetchall()
- # Out: [(1, 'Mr X')]
-
- del_stmt = authors_table.delete()
- del_stmt.execute(whereclause=text("name='Mr Y'"))
- del_stmt.execute() # delete all
-
-
- Example (cont...)
-Use of classical mapping
-
-
- from sqlalchemy.orm import backref, mapper, relation
-
- class Author:
- def __init__(self, name):
- self.name = name
-
- def __str__(self):
- return self.name
-
-
- class Book:
- def __init__(self, title, description, author):
- self.title = title
- self.description = description
- self.author = author
-
- def __str__(self):
- return self.title
-
- mapper(Book, books_table)
- mapper(Author, authors_table, properties = {"books": relation(Book, backref="author")})
-
-
- Example (cont...)
-Doing the same thing the easy way with declarative mapping
-
-
- from sqlalchemy.ext.declarative import declarative_base
- from sqlalchemy.orm import relationship, backref
-
- Base = declarative_base()
-
- class Author(Base):
- __tablename__ = "authors"
-
- author_id = Column(Integer, primary_key=True)
- name = Column(String)
-
- def __init__(self, name):
- self.name = name
-
- def __str__(self):
- return self.name
-
-
- class Book(Base):
- __tablename__ = "books" # self.__table__ will be available for our objects
-
- book_id = Column(Integer, primary_key=True)
- title = Column(String)
- description = Column(String)
- author_id = Column(Integer, ForeignKey("authors.author_id"))
- author = relationship(Author, backref=backref("books", order_by=title))
-
- def __init__(self, title, description, author):
- self.title = title
- self.description = description
- self.author = author
-
- def __str__(self):
- return self.title
-
- Base.metadata.create_all(engine) # create tables
-
-
- Example (cont...)
-Creating instances
-
-
- from sqlalchemy.orm import sessionmaker
-
- Session = sessionmaker(bind=engine) # bound session
- session = Session()
-
- author_1 = Author("Richard Dawkins")
- author_2 = Author("Matt Ridley")
-
- book_1 = Book("The Red Queen", "A popular science book", author_2)
- book_2 = Book("The Selfish Gene", "A popular science book", author_1)
- book_3 = Book("The Blind Watchmaker", "The theory of evolutio", author_1) # typo
-
- session.add(author_1)
- session.add(author_2)
- session.add(book_1)
- session.add(book_2)
- session.add(book_3)
- # or simply session.add_all([author_1, author_2, book_1, book_2, book_3])
-
- # session.flush()
- session.commit() # flushes (issues the statements and sends them to the RDBMS) and commits
-
- book_3.description = "The theory of evolution" # update the object
- book_3 in session # check whether the object is in the session
- # Out: True
-
- session.commit()
-
-
- Example (cont...)
-Queries
-
-
- session.query(Book).order_by(Book.book_id) # returns a Query instance with a .statement attribute
- session.query(Book).order_by(Book.book_id).all() # returns an object-list
-
- # return all book objects where title == "The Selfish Gene"
- session.query(Book).filter(Book.title == "The Selfish Gene").order_by(Book.book_id).all()
-
- # using LIKE
- session.query(Book).filter(Book.title.like("The%")).order_by(Book.book_id).all()
-
- query = session.query(Book).filter(Book.book_id == 9).order_by(Book.book_id)
- query.count() # returns 0
- query.all() # returns an empty list
- query.first() # returns None
- query.one() # raises NoResultFound exception
-
- query = session.query(Book).filter(Book.book_id == 1).order_by(Book.book_id)
- book_1 = query.one()
- book_1.description # returns "A popular science book"
- book_1.author.books # returns a list of Book-objects representing all the books from the same author.
-
- # get a list of all Book-instances where the author"s name is "Richard Dawkins"
- session.query(Book).filter(Book.author_id == Author.author_id).filter(Author.name == "Richard Dawkins").all()
- session.query(Book).join(Author).filter(Author.name == "Richard Dawkins").all()
- session.query(Book).\
- from_statement("SELECT b.* FROM books b, authors a WHERE b.author_id = a.author_id AND a.name=:name").\
- params(name="Richard Dawkins").all()
- session.query(Book).filter(Book.author == author_1).all()
-
-
- Some nice features
-
-
- import pandas as pd
-
- from sqlalchemy import func
-
- class Book(Base):
- # ...
- author = relationship(
- Author, backref=backref("books", lazy="dynamic", order_by=title)
- )
- # ...
-
- @hybrid_property
- def newly_arrived(self):
- return self.book_id > 2
-
- @newly_arrived.expression
- def newly_arrived(cls):
- return cls.book_id > 2
- # return func.abs(cls.book_id) > 2
-
- # .books is now a Query object
- query = author_obj.books.filter(Book.title.ilike("%red%"))
-
- session.query(Book).filter(Book.newly_arrived.is_(True)).all()
- # Out: [<__main__.Book at 0x7f132bdf0130>]
- # WHERE (abs(books.book_id) > ?) IS 1 ... in the case of func.abs
-
- # with Pandas
- df = pd.read_sql_table("my_table", con=session.get_bind()) # or con=engine
-
- df = pd.read_sql_query(query.statement, engine)
-
-
-
- Q & A
-Basic architecture
+SQLAlchemy consists of several components, including the ORM.
+-
+
- Engine- manages the connection pool and the RDBMS-independent SQL dialect layer +
- MetaData - used to collect and organize information about your table layout (schema) +
- SQL expression language - provides an API to execute your queries and updates against your tables, all from Python, and all in a database-independent way (low-level interface) +
- ORM - provides a convenient way to add database persistence to your Python objects without requiring you to design your objects around the database, or the database around the objects (high-level interface) +
- Session - establishes all conversations with the RDBMS and represents a "holding zone" for all the objects which you've loaded or associated with it during its lifespan +
+ Example
+SQLAlchemy gives us the choice between classical mapping and the newer declarative mapping
+
+
+ # option 1: classical mapping
+ # explicitly defining Table objects and mapping them to pure Python base classes
+ from sqlalchemy import create_engine
+
+ # engine = create_engine("postgresql+psycopg2://user:zipassword@localhost/mydb" , echo=True)
+ # The string form of the URL is dialect+driver://user:password@host/dbname[?key=value..],
+ # engine = create_engine("sqlite:///library.db", echo=True)
+ engine = create_engine("sqlite:///:memory:", echo=True)
+
+ from sqlalchemy import Column, MetaData, Table
+ from sqlalchemy import DateTime, ForeignKey, Integer, Numeric, String
+
+ metadata = MetaData()
+
+ production_types_table = Table(
+ "production_types",
+ metadata,
+ Column("production_type_id", Integer, primary_key=True),
+ Column("code", String(3), nullable=False, unique=True),
+ Column("description", String), # Column("name", String(128)) is possible
+ )
+
+ bidding_areas_table = Table(
+ "bidding_areas",
+ metadata,
+ Column("bidding_area_id", Integer, primary_key=True),
+ Column("code", String(3), nullable=False, unique=True),
+ Column("name", String(32)),
+ )
+
+ production_plans_table = Table(
+ "production_plans",
+ metadata,
+ Column("record_created_time", DateTime(timezone=False), primary_key=True),
+ Column("start_time", DateTime(timezone=False), primary_key=True),
+ Column("bidding_area_id", Integer, ForeignKey("bidding_areas.bidding_area_id"), primary_key=True),
+ Column("production_type_id", Integer, ForeignKey("production_types.production_type_id"), primary_key=True),
+ Column("value", Numeric, nullable=False),
+ )
+
+ metadata.create_all(engine) # creates the tables
+
+
+ Example (cont...)
+Use of SQL expression language
+
+
+ # option 1: classical mapping (continues)
+ # Using the SQL expression language (low level interface)
+ from sqlalchemy import text
+
+ insert_stmt = bidding_areas_table.insert(bind=engine)
+ type(insert_stmt)
+ # Out: <class 'sqlalchemy.sql.dml.Insert'>
+ print(insert_stmt)
+ # Out: INSERT INTO bidding_areas (bidding_area_id, code, name) VALUES (?, ?, ?)
+
+ compiled_stmt = insert_stmt.compile()
+ print(compiled_stmt.params)
+ # Out: {'bidding_area_id': None, 'code': None, 'name': None}
+
+ insert_stmt.execute(bidding_area_id=1, code="NO1", name="Elspot NO1") # insert a single entry
+ # ... or a list of entries
+ insert_stmt.execute(
+ [
+ {"bidding_area_id": 2, "code": "NO2", "name": "Elspot NO2"},
+ {"bidding_area_id": 3, "code": "NO3", "name": "Elspot NO3"},
+ {"bidding_area_id": 4, "code": "NO4", "name": "Elspot NO4"},
+ {"bidding_area_id": 5, "code": "NO5", "name": "Elspot NO5"},
+ {"bidding_area_id": 6, "code": "NO6", "name": "Elspot NO6"},
+ ]
+ )
+
+ metadata.bind = engine # no need to explicitly bind the engine from now on
+ select_stmt = bidding_areas_table.select(bidding_areas_table.c.bidding_area_id==2)
+ result = select_stmt.execute()
+ result.fetchall()
+ # Out: [(2, 'NO2', 'Elspot NO2')]
+
+ del_stmt = bidding_areas_table.delete()
+ del_stmt.execute(whereclause=text("name='Elspot NO6'"))
+ del_stmt.execute() # delete NO6
+
+
+ Example (cont...)
+Use of classical mapping
+
+
+ # option 1: classical mapping (continues)
+ # Defining regular base classes and mapping them to the Table objects
+ from sqlalchemy.orm import mapper
+
+ class ProductionType:
+ def __init__(self, code, description):
+ self.code = code
+ self.description = description
+
+ def __str__(self):
+ return self.code
+
+
+ class BiddingArea:
+ def __init__(self, code, name):
+ self.code = code
+ self.name = name
+
+ def __str__(self):
+ return self.code
+
+ mapper(ProductionType, production_types_table)
+ mapper(BiddingArea, bidding_areas_table)
+
+
+ Example (cont...)
+Use of classical mapping
+
+
+ from sqlalchemy.orm import relationship
+
+ class ProductionPlan:
+ def __init__(self, record_created_time, start_time, production_type, bidding_area, value):
+ self.record_created_time = record_created_time
+ self.start_time = start_time
+ self.production_type = production_type
+ self.bidding_area = bidding_area
+ self.value = value
+
+ def __str__(self):
+ return (
+ f"{self.record_created_time} {self.start_time} "
+ f"{self.production_type} {self.bidding_area} {self.value}"
+ )
+
+
+ mapper(
+ ProductionPlan,
+ production_plans_table,
+ properties = {
+ "production_type": relationship(ProductionType, backref="production_plans"),
+ "bidding_area": relationship(BiddingArea, backref="production_plans"),
+ },
+ )
+
+
+ Example (cont...)
+Doing the same thing the easy way with declarative mapping
+
+
+ # option 2: declarative mapping
+ from sqlalchemy.ext.declarative import declarative_base
+
+ Base = declarative_base()
+
+ class ProductionType(Base):
+ __tablename__ = "production_types"
+
+ production_type_id = Column(Integer, primary_key=True)
+ code = Column(String(3), nullable=False, unique=True)
+ description = Column(String)
+
+ def __init__(self, code, description):
+ self.code = code
+ self.description = description
+
+ def __str__(self):
+ return self.code
+
+ class BiddingArea(Base):
+ __tablename__ = "bidding_areas"
+
+ bidding_area_id = Column(Integer, primary_key=True)
+ code = Column(String(3), nullable=False, unique=True)
+ name = Column(String(32))
+
+ def __init__(self, code, name):
+ self.code = code
+ self.name = name
+
+ def __str__(self):
+ return self.code
+
+
+ Example (cont...)
+Doing the same thing the easy way with declarative mapping
+
+
+ # option 2: declarative mapping (continues)
+ from sqlalchemy.orm import relationship, backref
+
+ class ProductionPlan(Base):
+ __tablename__ = "production_plans"
+
+ record_created_time = Column(DateTime(timezone=False), primary_key=True)
+ start_time = Column(DateTime(timezone=False), primary_key=True)
+ bidding_area_id = Column(Integer, ForeignKey("bidding_areas.bidding_area_id"), primary_key=True)
+ production_type_id = Column(Integer, ForeignKey("production_types.production_type_id"), primary_key=True)
+ value = Column(Numeric, nullable=False)
+
+ # defining relationships.
+ # the defined attributes will reference 'ProductionType' and 'BiddingArea' objects
+ production_type = relationship(ProductionType, backref=backref("production_plans"))
+ bidding_area = relationship(BiddingArea, backref=backref("production_plans"))
+
+ def __init__(self, record_created_time, start_time, production_type, bidding_area, value):
+ self.record_created_time = record_created_time
+ self.start_time = start_time
+ self.production_type = production_type # a 'ProductionType' object
+ self.bidding_area = bidding_area # a 'BiddingArea' object
+ self.value = value
+
+ def __str__(self):
+ return (
+ f"{self.record_created_time} {self.start_time} "
+ f"{self.production_type} {self.bidding_area} {self.value}"
+ )
+
+ Base.metadata.create_all(engine) # create tables
+
+
+ Example (cont...)
+Creating instances
+
+
+ # adding some data...
+ import datetime
+ import decimal
+
+ from sqlalchemy.orm import sessionmaker
+
+ Session = sessionmaker(bind=engine) # bound session
+ session = Session()
+
+ bidding_area1 = BiddingArea("NO1", "Elspot NO1")
+ session.add(bidding_area1)
+
+ session.add_all(
+ [
+ BiddingArea("NO2", "Elspot NO2"),
+ BiddingArea("NO3", "Elspot NO3"),
+ BiddingArea("NO4", "Elspot NO4"),
+ BiddingArea("NO5", "Elspot NO5"),
+ ]
+ )
+
+ production_type_B37 = ProductionType("B37", "Thermal unspecified")
+ production_type_B30 = ProductionType("B30", "Wind unspecified")
+
+ session.add_all(
+ [
+ ProductionType("B19", "Wind Onshore"),
+ ProductionType("B10", "Hydro-electric pure pumped storage head installation"),
+ ProductionType("B11", "Hydro Run-of-river head installation"),
+ ProductionType("B12", "Hydro-electric storage head installation"),
+ ProductionType("A04", "Generation"),
+ production_type_B37,
+ production_type_B30,
+ ]
+ )
+
+
+ Example (cont...)
+Creating instances
+
+
+ # adding some production plans...
+
+ session.add(
+ ProductionPlan(
+ datetime.datetime.now(),
+ datetime.datetime(2022, 11, 2, 1, 0),
+ production_type_B37,
+ bidding_area1,
+ decimal.Decimal("80.5"),
+ )
+ )
+
+ production_plan2 = ProductionPlan(
+ datetime.datetime.now(),
+ datetime.datetime(2022, 11, 2, 2, 0),
+ production_type_B37,
+ bidding_area1,
+ decimal.Decimal("90.5"),
+ )
+
+ session.add(production_plan2)
+
+ session.flush() # execute pending operations
+ session.commit() # execute and commit pending operations
+
+ production_plan2.value = decimal.Decimal("70.5")
+ production_plan2 in session
+ # Out: True
+
+ session.commit()
+
+
+ Example (cont...)
+Queries
+
+
+ import pandas as pd
+
+ session.query(ProductionPlan).order_by(ProductionPlan.start_time) # returns a Query instance
+ session.query(ProductionPlan).order_by(ProductionPlan.start_time).all() # returns an object-list
+
+ # return all production plans where start_time after 2022-09-01 00:00
+ session.query(ProductionPlan).filter(ProductionPlan.start_time > datetime.datetime(2022, 9, 1, 0, 0)).all()
+
+ # return production plans with value > 80
+ query = session.query(ProductionPlan).filter(ProductionPlan.value > 80).order_by(ProductionPlan.start_time)
+ query.count() # returns 1
+ production_plan = query.first() # returns the first object (element)
+ production_plan = query.one() # raises NoResultFound exception or MultipleResultsFound in case elements != 1
+
+ # generate Pandas DataFrame from a query or entire table
+ df = pd.read_sql_table("my_table", con=session.get_bind()) # or con=engine
+ df = pd.read_sql_query(query.statement, engine)
+
+ # return production plans with production type 'B37'
+ session.query(ProductionPlan).filter(
+ ProductionPlan.production_type_id == ProductionType.production_type_id
+ ).filter(ProductionType.code == "B37").all()
+ session.query(ProductionPlan).join(ProductionType).filter(ProductionType.code == "B37").all()
+ session.query(ProductionPlan).filter(ProductionPlan.production_type == production_type_B37).all()
+ session.query(
+ ProductionPlan
+ ).from_statement(
+ text(
+ "SELECT pp.* FROM production_plans pp, production_types pt "
+ "WHERE pp.production_type_id = pt.production_type_id AND pt.code=:code"
+ )
+ ).params(code="B37").all()
+
+
+