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, like 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) )
-
3 - To set conditions, use Where:
-
For example,
a = Select(... age=Where.gt(45) )
Some possible conditions:
- field=Where.eq(value) - ...the field is EQUAL to the value;
- field=Where.gt(value) - ...the field is GREATER than the value;
- field=Where.lt(value) - ...the field is LESS than the value;
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=Where.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=Where.eq("Sci-Fi"),
awards=Where.like("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=Where.list(['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 like this:
SelectIN( 'Review r', movie=[GroupBy, Distinct], rate=Having.avg(Where.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(Where.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 toSELECT 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!
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