Skip to main content

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

Project description

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]
    )

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sql_blocks-0.2.2.tar.gz (13.6 kB view details)

Uploaded Source

Built Distribution

sql_blocks-0.2.2-py3-none-any.whl (10.9 kB view details)

Uploaded Python 3

File details

Details for the file sql_blocks-0.2.2.tar.gz.

File metadata

  • Download URL: sql_blocks-0.2.2.tar.gz
  • Upload date:
  • Size: 13.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for sql_blocks-0.2.2.tar.gz
Algorithm Hash digest
SHA256 502c0ea524b55d136e711c5d40499b5c3d3b4cb3adf18d7614084500df330830
MD5 540afabfbe99585287457f239a3c9899
BLAKE2b-256 75abe1ebaee32be32276d6aed76f589b4d6e5018dbb3217185b43d153e302ab1

See more details on using hashes here.

File details

Details for the file sql_blocks-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: sql_blocks-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 10.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for sql_blocks-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 b79e863ca62ac90ca66e154d573ce9fcbcb5ad8fe61d4accc867253cab18e7f4
MD5 a86e342356c7f907c9f55ecc3ede07c7
BLAKE2b-256 c8c276399b4b4a00de180cf2cdb8b7702ac64eed1698451b3aae466d055121c3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page