sql-blocks 0.2.4

Allows you to create objects for parts of SQL query commands. Also to combine these objects by joining them, adding or removing parts...

SQL_Blocks

1 - You can assemble a simple object that will then be converted into an SQL command:

a = Select('Actor') # --> SELECT * FROM Actor act

Note that an alias "act" has been added.

You can specify your own alias: a = Select('Actor a')

---

2 - You can also add a field, contains this...

• a = Select('Actor a', name=Field)

• Here are another ways to add a field:

  • Select('Actor a', name=Distinct )

  • Select('Actor a', name=NamedField('actors_name'))

  • Select( 'Actor a', name=NamedField('actors_name', Distinct) )

  2.1 -- Using expression as a field:

    Select(
        'Product',
        due_date=NamedField(
            'YEAR_ref',
            ExpressionField('extract(year from {f})') #  <<---
        )
    )

...should return: SELECT extract(year from due_date) as YEAR_ref...

---

3 - To set conditions, use Where:

• For example, a = Select(... age=gt(45) )

  Some possible conditions:

  • field=eq(value) - ...the field is EQUAL to the value;
  • field=gt(value) - ...the field is GREATER than the value;
  • field=lt(value) - ...the field is LESS than the value;

You may use Where.eq, Where.gt, Where.lt ... or simply eq, gt, lt ... 😉

3.1 -- If you want to filter the field on a range of values:

a = Select( 'Actor a', age=Between(45, 69) )

3.2 -- Sub-queries:

query = Select('Movie m', title=Field,
    id=SelectIN(
        'Review r',
        rate=gt(4.5),
        movie_id=Distinct
    )
)

>> print(query)

    SELECT
        m.title
    FROM
        Movie m
    WHERE
        m.id IN (
            SELECT DISTINCT r.movie
            FROM Review r WHERE r.rate > 4.5
        )

3.3 -- Optional conditions:

    OR=Options(
        genre=eq("Sci-Fi"),
        awards=contains("Oscar")
    )

Could be AND=Options(...)

3.4 -- Negative conditions use the Not class instead of Where

based_on_book=Not.is_null()

3.5 -- List of values

hash_tag=inside(['space', 'monster', 'gore'])

---

4 - A field can be two things at the same time:

• m = Select('Movie m' release_date=[Field, OrderBy])
  • This means that the field will appear in the results and also that the query will be ordered by that field.
• Applying GROUP BY to item 3.2, it would look contains this:

  SelectIN(
      'Review r', movie=[GroupBy, Distinct],
      rate=Having.avg(gt(4.5))
  )
  

---

5 - Relationships:

    query = Select('Actor a', name=Field,
        cast=Select('Cast c', id=PrimaryKey)
    )

>> print(query)

SELECT
    a.name
FROM
    Actor a
    JOIN Cast c ON (a.cast = c.id)    

---

6 - The reverse process (parse):

text = """
        SELECT
                cas.role,
                m.title,
                m.release_date,
                a.name as actors_name
        FROM
                Actor a
                LEFT JOIN Cast cas ON (a.cast = cas.id)
                LEFT JOIN Movie m ON (cas.movie = m.id)
        WHERE
                (
                    m.genre = 'Sci-Fi'
                    OR
                    m.awards LIKE '%Oscar%'
                )
                AND a.age <= 69 AND a.age >= 45
        ORDER BY
                m.release_date DESC
"""

a, c, m = Select.parse(text)

6.1 --- print(a)

    SELECT
            a.name as actors_name
    FROM
            Actor a
    WHERE
            a.age <= 69
            AND a.age >= 45

6.2 --- print(c)

SELECT
        c.role
FROM
        Cast c

6.3 --- print(m)

SELECT
        m.title,
        m.release_date
FROM
        Movie m
WHERE
        ( m.genre = 'Sci-Fi' OR m.awards LIKE '%Oscar%' )
ORDER BY
        m.release_date DESC

6.4 --- print(a+c)

SELECT
        a.name as actors_name,
        cas.role
FROM
        Actor a
        JOIN Cast cas ON (a.cast = cas.id)
WHERE
        a.age >= 45
        AND a.age <= 69

6.5 --- print(c+m)

... or print(m+c)

SELECT
        cas.role,
        m.title,
        m.release_date,
        m.director
FROM
        Cast cas
        JOIN Movie m ON (cas.movie = m.id)
WHERE
        ( m.genre = 'Sci-Fi' OR m.awards LIKE '%Oscar%' )
        AND m.director LIKE '%Coppola%'
ORDER BY
        m.release_date,
        m.director

---

7 - You can add or delete attributes directly in objects:

• a(gender=Field)
• m.delete('director')

---

8 - Defining relationship on separate objects:

a = Select...
c = Select...
m = Select...

a + c => ERROR: "No relationship found between Actor and Cast"

8.1 - But...

a( cast=ForeignKey('Cast') )
c(id=PrimaryKey)

a + c => Ok!

8.2

c( movie=ForeignKey('Movie') )
m(id=PrimaryKey)

c + m => Ok!

m + c => Ok!

---

9 - Comparing objects

9.1

        a1 = Select.parse('''
                SELECT gender, Max(act.age) FROM Actor act
                WHERE act.age <= 69 AND act.age >= 45
                GROUP BY gender
            ''')[0]

        a2 = Select('Actor',
            age=[ Between(45, 69), Max ],
            gender=[GroupBy, Field]
        )       

a1 == a2 # --- True!

9.2

    m1 = Select.parse("""
        SELECT title, release_date FROM Movie m ORDER BY release_date 
        WHERE m.genre = 'Sci-Fi' AND m.awards LIKE '%Oscar%'
    """)[0]

    m2 = Select.parse("""
        SELECT release_date, title
        FROM Movie m
        WHERE m.awards LIKE '%Oscar%' AND m.genre = 'Sci-Fi'
        ORDER BY release_date 
    """)[0]

m1 == m2 # --- True!

9.3

best_movies = SelectIN(
    Review=Table('role'),
    rate=[GroupBy, Having.avg(gt(4.5))]
)
m1 = Select(
    Movie=Table('title,release_date'),
    id=best_movies
)

sql = "SELECT rev.role FROM Review rev GROUP BY rev.rate HAVING Avg(rev.rate) > 4.5"
m2 = Select(
    'Movie', release_date=Field, title=Field,
    id=Where(f"IN ({sql})")
)

m1 == m2 # --- True!

---

10 - CASE...WHEN...THEN

Select(
    'Product',
    label=Case('price').when(
        lt(50), 'cheap'
    ).when(
        gt(100), 'expensive'
    ).else_value(
        'normal'
    )
)

---

11 - optimize method

p1 = Select.parse("""
        SELECT * FROM Product p
        WHERE (p.category = 'Gizmo'
                OR p.category = 'Gadget'
                OR p.category = 'Doohickey')
            AND NOT price <= 387.64
            AND YEAR(last_sale) = 2024
        ORDER BY
            category
    """)[0]
    p1.optimize() #  <<===============
    p2 = Select.parse("""
        SELECT category FROM Product p
        WHERE category IN ('Gizmo','Gadget','Doohickey')
            and p.price > 387.64
            and p.last_sale >= '2024-01-01'
            and p.last_sale <= '2024-12-31'
        ORDER BY p.category LIMIT 100
    """)[0]
    p1 == p2 # --- True!

This will...

• Replace OR conditions to SELECT IN ...
• Put LIMIT if no fields or conditions defined;
• Normalizes inverted conditions;
• Auto includes fields present in ORDER/GROUP BY;
• Replace YEAR function with date range comparison.

The method allows you to select which rules you want to apply in the optimization...Or define your own rules!

---

12 - Adding multiple fields at once

    query = Select('post p')
    query.add_fields(
        'user_id, created_at',
        order_by=True, group_by=True
    )

...is the same as...

    query = Select(
        'post p',
        user_id=[Field, GroupBy, OrderBy],
        created_at=[Field, GroupBy, OrderBy]
    )

13 - Change parser engine

a, c, m = Select.parse(
    """
        Actor(name, id ?age = 40)
        <- Cast(actor_id, movie_id) ->
        Movie(id ^title)
    """,
    Cypher 
    # ^^^ recognizes syntax like Neo4J queries
)

print(a+c+m)

SELECT
        act.name,
        mov.title
FROM
        Cast cas
        JOIN Movie mov ON (cas.movie_id = mov.id)
        JOIN Actor act ON (cas.actor_id = act.id)
WHERE
        act.age = 40
ORDER BY
        mov.title

---

Separators and meaning:

• ( ) Delimits a table and its fields
• , Separate fields
• ? For simple conditions (> < = <>)
• <- connects to the table on the left
• -> connects to the table on the right
• ^ Put the field in the ORDER BY clause