SmileyDB3

SmileyDB3 is a library built on sqlite3 to make working with databases easier

Install

pip install SmileyDB3

Usage:

To use the SmileyDB3 class, you would typically instantiate an object of the class and provide the path or name of the SQLite database file as a parameter. For example:

db = SmileyDB3("mydatabase.db")

You can then call the table() method on the db object to create a new table in the database:

my_table = db.table("my_table")

The table() method returns a Table object (my_table in this example) that can be used to perform operations on the created table.

New Functions

Generate like this

Install faker

pip install faker

db = SmileyDB3('mydb.db')
tasks = db.table('tasks')

from faker import Faker

tasks_list = tasks.GenerateLikeThis(
    schema={'name': '', 'reword': 100},
    faker = Faker(),
    n = 20
)

tasks.InsertMany(data_list=tasks_list)

Slice

tasks_list = tasks.Slice(0, 5)
print(tasks_list)

Result

[{'_index': 1, 'name': 'William Macias', 'reword': 41, 'uuid': '8ea20e95-c0f4-4b2d-95b3-ade89b18d6d1', 'created_at': '2025-01-20 08:39:31.684338'}, {'_index': 2, 'name': 'George Martinez', 'reword': 93, 'uuid': '39853737-3fd5-4ab8-abae-1180dc27f7a3', 'created_at': '2025-01-20 08:39:31.888855'}, {'_index': 3, 'name': 'Ashley Smith', 'reword': 33, 'uuid': 'd194c712-e7ca-44d1-9127-fd5e19a5d844', 'created_at': '2025-01-20 08:39:31.970459'}, {'_index': 4, 'name': 'Tricia Stewart', 'reword': 43, 'uuid': '4a5b2cde-bde9-4ccb-a40c-ca5bf3e40303', 'created_at': '2025-01-20 08:39:32.056114'}, {'_index': 5, 'name': 'Luke Wall', 'reword': 79, 'uuid': 'f89dec3f-71c5-44ee-ae86-58f9b76df7bb', 'created_at': '2025-01-20 08:39:32.148086'}]

Limit

tasks_list = tasks.Limit(5)
print(tasks_list)

Result

[{'_index': 1, 'name': 'William Macias', 'reword': 41, 'uuid': '8ea20e95-c0f4-4b2d-95b3-ade89b18d6d1', 'created_at': '2025-01-20 08:39:31.684338'}, {'_index': 2, 'name': 'George Martinez', 'reword': 93, 'uuid': '39853737-3fd5-4ab8-abae-1180dc27f7a3', 'created_at': '2025-01-20 08:39:31.888855'}, {'_index': 3, 'name': 'Ashley Smith', 'reword': 33, 'uuid': 'd194c712-e7ca-44d1-9127-fd5e19a5d844', 'created_at': '2025-01-20 08:39:31.970459'}, {'_index': 4, 'name': 'Tricia Stewart', 'reword': 43, 'uuid': '4a5b2cde-bde9-4ccb-a40c-ca5bf3e40303', 'created_at': '2025-01-20 08:39:32.056114'}, {'_index': 5, 'name': 'Luke Wall', 'reword': 79, 'uuid': 'f89dec3f-71c5-44ee-ae86-58f9b76df7bb', 'created_at': '2025-01-20 08:39:32.148086'}]

---

Insert or add new record

db = SmileyDB3('database.db')

tasks = db.table('tasks')

tasks.Insert(
    data = {
        'name': 'This is task name 2', 
        'description': 'This task description 2',
        'coins': 50,
        'workers': 80
    }
)

Insert list of data

list_data = [
    {'name': 'test 1', 'description': 'test 1', 'coins': 50, 'workers': 10},
    {'name': 'test 2', 'description': 'test 2', 'coins': 500, 'workers': 20},
    {'name': 'test 3', 'description': 'test 3', 'coins': 100, 'workers': 50},
    {'name': 'test 4', 'description': 'test 4', 'coins': 5000, 'workers': 80}
]

tasks.InsertMany(data_list=list_data)

If you want to make a login system, SmileyDB3 makes it easy for you.

Register a new user

db = SmileyDB3('database.db')

users = db.table('users')

users.Register(data = {'email': 'test@example.com', 'password': '2020'})

Note

By default, the function 'Register' makes a hash for any password automatically. If you want to keep it as plain text, make sure that the value of  'password_hash' argument is False

db = SmileyDB3('database.db')

users = db.table('users')

users.Register(
    data = {'email': 'test666@example.com', 'password': '2020'},
    password_hash = False
)

Login

db = SmileyDB3('database.db')

users = db.table('users')


result = users.LogIn(
    data = {'email': 'test666@example.com', 'password': '2020'},
)

print(result)

Result

{'_index': 3, 'email': 'test666@example.com', 'password': '2020', 'uuid': '2626a962-d5d7-49fa-98f1-53d4bd722ee9', 'created_at': '2024-07-11 11:10:46.319231'}

Get all records

print(tasks.GetALL())

Get records by id

print(tasks.GetByID(uuid='e927c787-bf9a-4ec7-b575-2efacd90728e'))

Get records by any column like name

print(tasks.GetBy(name = 'This is task name'))

You can use also FindBy or FilterBy function it will give you the same result

Get one record by any column like workers in this example

tasks = db.table('tasks')
print(tasks.FindOne(workers = 80))

Result

{'_index': 4, 'name': 'test 4', 'description': 'test 4', 'coins': 5000, 
'workers': 80, 'uuid': '1fad0ed8-fbbc-4fc9-8e46-3f6c355dbf84', 'created_at': '2024-07-11 10:42:26.818831'}

Filtring records by any column

use larger_than, less_than, not, equal, between, less_or_equal, larger_or_equal

example of how to use less_than filter

tasks = db.table('tasks')


print(tasks.Filter(
    filter_keys = {'workers': {'less_than': 100}}
))

Result

[{'key': 'workers', 'records': [{'_index': 13, 'workers': 10, 'coins': 20, 'uuid': '5dcabe12-17b3-4a64-928c-a524b6fb6479', 'created_at': '2024-08-11 12:41:05.248027'}, {'_index': 19, 'workers': 50, 'coins': 50, 'uuid': 'f1273e5b-c937-45e4-931c-d1b6d9f31a51', 'created_at': '2024-08-11 12:43:27.156194'}, {'_index': 20, 'workers': 50, 'coins': 50, 'uuid': 'b1c67c92-6a2d-4a72-84a1-b5466d3ca839', 'created_at': '2024-08-11 12:44:17.355148'}, {'_index': 21, 'workers': 50, 'coins': 50, 'uuid': '4b46f78c-98b0-4dad-84c7-ac76af218102', 'created_at': '2024-08-11 12:44:27.422767'}, {'_index': 22, 'workers': 80, 'coins': 500, 'uuid': 'f0eecddd-d046-4fd6-b441-9188a3d73985', 'created_at': '2024-08-11 12:44:38.911006'}, {'_index': 25, 'workers': 71, 'coins': 809, 'uuid': '484bb9e4-647b-4dc2-afac-c3e27a0e613e', 'created_at': '2024-08-11 12:47:30.265126'}, {'_index': 27, 'workers': 50, 'coins': 394, 'uuid': 'da2ee6b2-3653-4cae-b570-510d998f09a2', 'created_at': '2024-08-11 12:47:52.165459'}, {'_index': 29, 'workers': 99, 'coins': 817, 'uuid': 'a6d3b21c-b2ba-4530-9e09-35b00a37e493', 'created_at': '2024-08-11 12:48:34.145886'}, {'_index': 31, 'workers': 71, 'coins': 463, 'uuid': 'c71a7b11-9b3b-4787-89d2-d7f19904e228', 'created_at': '2024-08-11 
12:51:37.325311'}]}]

example of how to use between filter

tasks = db.table('tasks')


print(tasks.Filter(
    filter_keys = {'workers': {'between': [100, 200]}}
))

Result

[{'key': 'workers', 'records': [{'_index': 1, 'workers': 200, 'coins': 20, 'uuid': '545145bc-c03e-4228-aece-d5a7e50c996f', 'created_at': '2024-08-11 12:27:05.446859'}, {'_index': 14, 'workers': 100, 'coins': 20, 'uuid': '6d84bceb-5f8f-464b-97b1-f6b46906149b', 'created_at': '2024-08-11 12:41:44.623149'}, {'_index': 15, 'workers': 200, 'coins': 20, 'uuid': '4e25ace6-b167-483d-97bc-6f765f324560', 'created_at': '2024-08-11 12:41:49.830534'}, {'_index': 16, 'workers': 200, 'coins': 20, 'uuid': 'c4542f0d-1238-4631-8518-02c3e67809dd', 'created_at': '2024-08-11 12:42:32.767674'}, {'_index': 17, 'workers': 200, 'coins': 20, 'uuid': '37e6e806-5567-4fc7-bdab-89f520314b5f', 'created_at': '2024-08-11 12:42:51.708270'}]}]

Update record by uuid

result = tasks.Update(
    uuid='31c37a83-02db-4e8d-9d62-124888626892',
    data = {'coins': 1}
)

print(result)

Result

{'_index': 5, 'name': 'This is task name 2', 'description': 'This task description 2', 'coins': 1, 'workers': 80, 'uuid': '31c37a83-02db-4e8d-9d62-124888626892', 'created_at': '2024-07-11 10:24:26.020235'}

Update many by name or any other column name

result = tasks.UpdateMany(
    data = {'coins': 1000},
    name = 'This is task name 2'
)

print(result)

Result

[
    {'_index': 2, 'name': 'This is task name 2', 'description': 'This task description 2', 'coins': 1000, 'workers': 80, 'uuid': 'e927c787-bf9a-4ec7-b575-2efacd90728e', 'created_at': '2024-07-11 10:09:48.163728'}, 

    {'_index': 3, 'name': 'This is task name 2', 'description': 'This task description 2', 'coins': 1000, 'workers': 80, 'uuid': '9d74c2ea-b943-4aa9-bd06-52ba1beecc5b', 'created_at': '2024-07-11 10:23:49.426697'}, 
    
    {'_index': 4, 'name': 'This is task name 2', 'description': 'This task description 2', 'coins': 1000, 'workers': 80, 'uuid': '93ed7665-f6e3-40be-ab3b-8d609eaf1896', 'created_at': '2024-07-11 10:24:16.574957'}, 
    
    {'_index': 5, 'name': 'This is task name 2', 'description': 'This task description 2', 'coins': 1000, 'workers': 80, 'uuid': '31c37a83-02db-4e8d-9d62-124888626892', 'created_at': '2024-07-11 
    10:24:26.020235'
    }
]

Delete record by uuid

tasks.Delete(uuid='b3bd4856-28f2-4d24-aaca-c22724d2e0a1')

Delete records by name or any other column name

tasks.DeleteMany(
    name = 'This is task name 2'
)

Convert data to CSV, JSON, HTML, etc

tasks.convert().to_csv('out.csv')
tasks.convert().to_json('out.json')

Credits

sqlite3:

The sqlite3 library is part of the Python Standard Library, which means it is included with Python itself. You can import and use the sqlite3 module directly in your Python code without needing to install any additional

bcrypt:

Modern password hashing for your software and your servers