= Cheat Sheet == Open a database require 'sequel' DB = Sequel.sqlite('my_blog.db') DB = Sequel.connect('postgres://user:password@localhost/my_db') DB = Sequel.postgres('my_db', user: 'user', password: 'password', host: 'localhost') DB = Sequel.ado('mydb') == Open an SQLite memory database Without a filename argument, the sqlite adapter will setup a new sqlite database in memory. DB = Sequel.sqlite == Logging SQL statements require 'logger' DB = Sequel.sqlite(loggers: [Logger.new($stdout)]) # or DB.loggers << Logger.new($stdout) == Using raw SQL DB.run "CREATE TABLE users (name VARCHAR(255) NOT NULL, age INT(3) NOT NULL)" dataset = DB["SELECT age FROM users WHERE name = ?", name] dataset.map(:age) DB.fetch("SELECT name FROM users") do |row| p row[:name] end == Create a dataset dataset = DB[:items] dataset = DB.from(:items) == Most dataset methods are chainable dataset = DB[:managers].where(salary: 5000..10000).order(:name, :department) == Insert rows dataset.insert(name: 'Sharon', grade: 50) == Retrieve rows dataset.each{|r| p r} dataset.all # => [{...}, {...}, ...] dataset.first # => {...} dataset.last # => {...} == Update/Delete rows dataset.exclude(:active).delete dataset.where{price < 100}.update(:active => true) dataset.where(:active).update(:price => Sequel[:price] * 0.90) == Datasets are Enumerable dataset.map{|r| r[:name]} dataset.map(:name) # same as above dataset.inject(0){|sum, r| sum + r[:value]} dataset.sum(:value) # better == Filtering (see also {Dataset Filtering}[rdoc-ref:doc/dataset_filtering.rdoc]) === Equality dataset.where(name: 'abc') === Inequality dataset.where{value > 100} dataset.exclude{value <= 100} === Inclusion dataset.where(value: 50..100) dataset.where{(value >= 50) & (value <= 100)} dataset.where(value: [50,75,100]) dataset.where(id: other_dataset.select(:other_id)) === Subselects as scalar values dataset.where{price > dataset.select(avg(price) + 100)} === LIKE/Regexp DB[:items].where(Sequel.like(:name, 'AL%')) DB[:items].where(name: /^AL/) === AND/OR/NOT DB[:items].where{(x > 5) & (y > 10)}.sql # SELECT * FROM items WHERE ((x > 5) AND (y > 10)) DB[:items].where(Sequel.or(x: 1, y: 2) & Sequel.~(z: 3)).sql # SELECT * FROM items WHERE (((x = 1) OR (y = 2)) AND (z != 3)) === Mathematical operators DB[:items].where{x + y > z}.sql # SELECT * FROM items WHERE ((x + y) > z) DB[:items].where{price - 100 < avg(price)}.sql # SELECT * FROM items WHERE ((price - 100) < avg(price)) === Raw SQL Fragments dataset.where(Sequel.lit('id= 1')) dataset.where(Sequel.lit('name = ?', 'abc')) dataset.where(Sequel.lit('value IN ?', [50,75,100])) dataset.where(Sequel.lit('price > (SELECT avg(price) + 100 FROM table)')) == Ordering dataset.order(:kind) # kind dataset.reverse(:kind) # kind DESC dataset.order(Sequel.desc(:kind), :name) # kind DESC, name == Limit/Offset dataset.limit(30) # LIMIT 30 dataset.limit(30, 10) # LIMIT 30 OFFSET 10 dataset.limit(30).offset(10) # LIMIT 30 OFFSET 10 == Joins DB[:items].left_outer_join(:categories, id: :category_id).sql # SELECT * FROM items # LEFT OUTER JOIN categories ON categories.id = items.category_id DB[:items].join(:categories, id: :category_id). join(:groups, id: Sequel[:items][:group_id]) # SELECT * FROM items # INNER JOIN categories ON categories.id = items.category_id # INNER JOIN groups ON groups.id = items.group_id == Aggregate functions methods dataset.count #=> record count dataset.max(:price) dataset.min(:price) dataset.avg(:price) dataset.sum(:stock) dataset.group_and_count(:category).all dataset.select_group(:category).select_append{avg(:price)} == SQL Functions / Literals dataset.update(updated_at: Sequel.function(:NOW)) dataset.update(updated_at: Sequel.lit('NOW()')) dataset.update(updated_at: Sequel.lit("DateValue('1/1/2001')")) dataset.update(updated_at: Sequel.function(:DateValue, '1/1/2001')) == Schema Manipulation DB.create_table :items do primary_key :id String :name, unique: true, null: false TrueClass :active, default: true foreign_key :category_id, :categories DateTime :created_at, default: Sequel::CURRENT_TIMESTAMP, :index=>true index [:category_id, :active] end DB.drop_table :items == Aliasing DB[:items].select(Sequel[:name].as(:item_name)) DB[:items].select(Sequel.as(:name, :item_name)) DB[:items].select{name.as(:item_name)} # SELECT name AS item_name FROM items DB[Sequel[:items].as(:items_table)].select{items_table[:name].as(:item_name)} # SELECT items_table.name AS item_name FROM items AS items_table == Transactions DB.transaction do # BEGIN dataset.insert(first_name: 'Inigo', last_name: 'Montoya') dataset.insert(first_name: 'Farm', last_name: 'Boy') end # COMMIT Transactions are reentrant: DB.transaction do # BEGIN DB.transaction do dataset.insert(first_name: 'Inigo', last_name: 'Montoya') end end # COMMIT Transactions are aborted if an error is raised: DB.transaction do # BEGIN raise "some error occurred" end # ROLLBACK issued and the error is re-raised Transactions can also be aborted by raising Sequel::Rollback: DB.transaction do # BEGIN raise(Sequel::Rollback) end # ROLLBACK issued and no error raised Savepoints can be used if the database supports it: DB.transaction do dataset.insert(first_name: 'Farm', last_name: 'Boy') # Inserted DB.transaction(savepoint: true) do # This savepoint is rolled back dataset.insert(first_name: 'Inigo', last_name: 'Montoya') # Not inserted raise(Sequel::Rollback) end dataset.insert(first_name: 'Prince', last_name: 'Humperdink') # Inserted end == Retrieving SQL dataset.sql # "SELECT * FROM items" dataset.insert_sql(a: 1) # "INSERT INTO items (a) VALUES (1)" dataset.update_sql(a: 1) # "UPDATE items SET a = 1" dataset.delete_sql # "DELETE FROM items" == Basic introspection dataset.columns # => [:id, :name, ...] DB.tables # => [:items, ...] DB.views # => [:new_items, ...] DB.schema(:items) # => [[:id, {:type=>:integer, ...}], [:name, {:type=>:string, ...}], ...] DB.indexes(:items) # => {:index_name => {:columns=>[:a], :unique=>false}, ...} DB.foreign_key_list(:items) # => [{:name=>:items_a_fk, :columns=>[:a], :key=>[:id], :table=>:other_table}, ...]