sqlosure
is a relational algebra library and DSL for interacting with
relational data, primarily in a SQL-Database from your Clojure-program.
Just add the current version of SQLosure to your deps.edn
.
To interact with a specific database system, you must also include the
corresponding JDBC driver.
Example using PostgreSQL:
{:deps {de.active-group/sqlosure "0.5.0-SNAPSHOT" org.postgresql/postgresql "42.2.14"}
The core of sqlosure
is a declarative query language based on relational
algebra.
There are two types of values in SQLosure: queries and expressions.
Suppose you want to write queries on a employee
model.
An employee consists of
- an id (integer)
- a name (string)
- a flag that tells us whether they are an admin or not (boolean)
Additionally, each user is assigned to an office. An office consists of
- an id (integer)
- a floor (integer)
- a name (string)
The corresponding SQL-tables might have these CREATE
-statements
CREATE TABLE employee (
id INT,
name TEXT,
is_admin BOOLEAN,
office_id INT
);
CREATE TABLE office (
id INT,
floor INT,
name TEXT
);
To construct queries on those tables, you first need to define relations to operate on
(ns your.name.space
(:require [sqlosure.core :refer :all]
[sqlosure.db-connection :as db-connection]))
;; Defines a relation with three fields.
(def employee (table "employee" [["id" $integer-t]
["name" $string-t]
["is_admin" $boolean-t]]))
(def employee-with-office (table "employee" [["id" $integer-t]
["name" $string-t]
["admin" $boolean-t]
["office_id" $integer-t]]))
(def office (table "office" [["id" $integer-t]
["floor" $integer-t]
["name" $string-t]]))
The table
function expects the database table-name as string and a vector
of tuples for each attribute we want to consider.
Note that your are not required to “project” all fields from a table – you
just need to define what you need in this each particular case.
Next, we want to query our database. To accommodate for the differences between different RDBMSs, SQLosure has to concept of a backend. Luckily, SQLosure comes equipped with several of those backends. In this case, let’s say we want to talk to a PostgreSQL-instance. First, we jot down the JDBC connection map:
(def pg-db {:dbtype "postgresql"
:dbname "somedb"
:host "localhost"
:port "5432"
:user "myuser"
:password "secret"})
To actually run the query, there are two basic modes. The one we will use here is more basic. Further down the document we will show the more elaborated way.
(ns ...
[sqlosure.db-connection :as db-connection]
[sqlosure.backends.postgresql :as postgresql])
(def db-conn (db-connect pg-db postgresql/implementation))
(db-connection/run-query db-conn employee)
;; => [[0 "Marco" true]
;; [1 "Markus" false]
;; ...]
As you can see, running a base relation as the query selects the whole table. Now, we only want employees that are admins.
(def admins
(query [emp (embed employee)]
(restrict! ($= (! emp "is_admin") ($boolean true)))
(project emp)))
Let’s break this down
query
is a macro that allows us to construct relations from relational algebra terms.- To operate on relations in this context, we need to “embed” them via
[emp (embed employee)]
. Think of this as follows: Where on the right hand side of this expression we talk about the relation as a whole, the name on the right hand side refers to the individual values of this relation. - To narrow down the values, we call
restrict!
on them (think of aWHERE
clause in SQL). - The argument to
restrict!
narrows down the values to those whose attribute"is_admin"
is equal to false.$=
just the regular === but operates on relations instead of values. SQLosure has many such operators, all prefixed with$
. (! emp "is_admin")
selects the"is_admin"
attribute from the embedded employee relation.- In the end, we call
project
on all values. This means that, when the query is executed, we want all values with all of their attributes.
If we run the query, we get the following result:
(db-connection/run-query db-conn admins)
;; => [[0 "Marco" true]
;; ...
;; [42 "Tim" true]]
Now, perhaps we only want to see the names of employees, instead of the whole
record.
We could of course define a new query that just projects the "name"
of each
employee:
(def admin-names
(query [emp (embed employee)]
(restrict! ($= (! emp "is_admin") ($boolean true)))
(project [["name" (! emp "name")]])))
This would do the trick.
Still, we did just define almost the same query as above.
This is where it comes into play that the result of a query
-call is itself
a query.
This means they easily compose to larger/more complex queries from simpler
ones.
Thus, we can then redefine admin-names
as follows:
(def admin-names
(query [as (embed admins)]
(project [["name" (! emp "name")]])))
We treat admins
just as a base relation.
The schema (e.g. the fields you can select via the !
-operator) depends on
the projection.
Lastly, let’s write a query that returns all admins and the name’s of their offices:
(def admins-with-offices
(query [as (embed admins)
os (embed office)]
(restrict! ($= (! as "office_id")
(! os "id")))
(project [["name" (! as "name")]
["office" (! os "name")]])))
(db-connection/run-query db-conn admins-with-offices)
;; => [["Marco" "Terassen Office"]
;; ["Tim" "Obergeschoss"]
;; ...]
SQLosure provides a DSL for reading and writing from and to databases. To demonstrate, we will keep our tables from the examples above. There are four basic functions to construct programs that read and write to a database
(ns your.name.space
(:require [sqlosure.core :refer :all]
[sqlosure.db-connection :as db-connection]
[sqlosure.lang :as db]))
;; Defines a relation with three fields.
(def employee ..)
(def office ...)
(db/read! employee)
(db/create! employee [42 "Mike" true 0])
(db/udpate! employee
(fn [id name admin? office-id]
($= name ($string "Marco")))
(fn [id name admin? office-id]
{"is_admin" ($boolean false)}))
(db/delete! employee
(fn [id name admin? office-id]
($= id ($integer 42))))
What do these functions do?
read!
operates in much the same way as we saw above. It takes aquery
as it’s argument and, upon execution, runs the query.create!
takes a base relation (e.g. something that was created via thetable
function) and, upon execution, inserts the record (a vector of values to insert)update!
takes a base relation (e.g. something that was created via thetable
function), a predicate function and an update fuction, and, upon execution, applies the update. The predicate function takes as it’s arguments all fields of the relation and must return an expression (something constructed from$
-functions that returns a$boolean
). The update function takes the same arguments and must return a map with all updates to apply. The keys must correspond to the attributes of the relation, their right hand sides must be$
const values.delete!
takes a base relation (e.g. something that was created via thetable
function), and a predicate function and, upon execution, applies the delete operation. The predicate function takes as it’s arguments all fields of the relation and must return an expression (something constructed from$
-functions that returns a$boolean
).The keen observer might have noticed that a) all those functions just return values and b) there is no mention of a database backend or connection strings. First, let’s construct a program out of these functions, using active-clojure’s free monad.
(ns your.name.space (:require [sqlosure.core :refer :all] [sqlosure.db-connection :as db-connection] [sqlosure.lang :as db] [active.clojure.monad :as monad])) ;; Defines a relation with three fields. (def employee ..) (def office ...) (def make-all-employees-admins! (db/udpate! employee (fn [_ _ _ _] ($boolean true)) (fn [_ _ _ _] {"is_admin" ($boolean true)}))) (def prog (monad/monadic (db/create! employee [0 "Marco" false 0]) (db/create! employee [1 "Erika" true 0]) (db/create! employee [2 "Sibylle" false 0]) [employees (db/read! employee)] make-all-users-admins! (db/delete! employee (fn [id _ _ _] ($= id ($integer 0)))) [employees-after (db/read! employee)] (monad/return {:before employees :after employees-after})))
This program first inserts three employees and reads them back, storing the result as
employees
. Then, after making all employees admins, deletes the user with"id" = 0
. It then reads the users back once more, storing the result asemployees-after
before returning the two query results. Keep in mind that is still just the description of the operations we want to execute.To actually run the program, we need a “command-config” object. For this, we have two optionse.
If we want to run the program with an actual database, we need a
db-connection as above.
Then, we can run the program using the run-db
function:
(ns your.name.space
(:require ...
[sqlosure.runner.database :as db-runner]))
...
(run-db (db-runner/command-config db-conn) prog)
;; => {:before [[0 "Marco" false 0]
;; [1 "Erike" true 0]
;; [2 "Sibylle" false 0]]
;; :after [[1 "Erika" true 0]
;; [2 "Sibylle" true 0]]}
The second argument decides how the program will be executed.
Since we used the sqlosure.runner.database
runner, the program is executed
in the context of our PostgeSQL database, just as before.
Often, we want to construct such programs without really running them against
a database.
SQLosure provides the sqlosure.runner.embedded
runner to enable the user to
run such programs against a simple, map based “database”.
Such a database is just a map from table-names to a set of maps, representing
the individual records.
(ns your.name.space
(:require ...
[sqlosure.runner.embedded :as embedded-runner]))
...
(def empty-db {})
(def db {"employees" #{{"id" 42 "name" "Simon" "is_admin" false "office_id" 23}}})
(run-db (embedded-runner/command-config empty-db) prog)
;; => {:before [[0 "Marco" false 0]
;; [1 "Erike" true 0]
;; [2 "Sibylle" false 0]]
;; :after [[1 "Erika" true 0]
;; [2 "Sibylle" true 0]]}
(run-db (embedded-runner/command-config db) prog)
;; => {:before [[0 "Marco" false 0]
;; [1 "Erike" true 0]
;; [2 "Sibylle" false 0]
;; [42 "Simon" false 23]]
;; :after [[1 "Erika" true 0]
;; [2 "Sibylle" true 0]
;; [42 "Simon" true 23]]}
This yields the exact same result without ever touching the database and is therefore the perfect way to tests your queries (or even just operate on an in-memory “database”).
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