Skip to main content

tiny ORM for SQL-databases

Project description

Initializing

This package represents a new ORM to work with SQL-syntax databases (for now, only PostgreSQL and SQLite are natively supported, but you may inherit your own connectors from IConnector abstract class).

To start working, all you need to do is import a package's facade object and initialise it:

import qrookDB.DB as DB
DB = DB.DB('postgres', 'db_name', 'username', 'password', format_type='dict')
DB.create_logger(app_name='qrookdb_test', file='app_log.log')
DB.create_data(__name__, in_module=True)

Here we first created a database connection, providing connect parameters (format_type defines the form in which results'll be returned - 'list' and 'dict' supported), then initialized an internal logger to write both in console and file. Note that instead of 'postgres' you could've sent the instance of the connector (including your own connectors). The 'create_data' function reads database system tables to get info about all user-defined tables, and creates QRTable objects based on this info. Now you can use table names (ones given to them in database) to access to these objects as DB instance fields (also, configuration showed above adds these table names to your current module, so you can use short names: 'books' instead of 'DB.books').

Querying

You can form execute queries using either DB instance or concrete tables (in this case, you don't need to mention in which table to perform queries). To execute any query, use one of 'exec', 'one' and 'all' methods (latter two define how many rows to return from query; 'exec' returns None by default). If forming of the query fails, it won't be executed at all (and will return None if you try); you can use 'get_error' method of the query to get the error description (it will be logged, though). Note: if error occured in the middle of query-building, query will ignore the rest of building proccess.

Select queries examples

op = DB.operators

print(DB.books)
print(books, books.id)

# logical 'and' is used by default for multiple where conditions; 'op' module contains special operators
data = DB.select(books).where(original_publication_year=2000, language_code='eng').    where(id=op.In(470, 490, 485)).all()

# you can add raw-string query parts, but it'll be on your conscience in terms of security   
query = books.select('count(*)').group_by(books.original_publication_year)
data = query.all()

data = DB.select(books, books.id).where('id < 10').order_by(books.id, desc=True).    limit(3).offset(2).all()

# here fields have same name ('id'), but via different tables it'll be ok
# (for data in dict-format, table-names'll be added to keys) 
data = books.select(authors.id, books.id)    .join(books_authors, op.Eq(books_authors.book_id, books.id))    .join(authors, op.Eq(books_authors.author_id, authors.id)).all()
    # .join(books_authors, 'books_authors.book_id = books.id')
data = books.select(books.id).where(id=1).where(bool='or', id=2).all()

# error - trying to select two equal fields;
q = DB.select(events, events.id, events.id).where(id=1)
data = q.all()
print('data is None here:', data, ';	error:', q.get_error())

Update, Insert, Delete queries examples

# if auto_commit is not set, you'll have to commit manually 
ok = DB.delete(events, auto_commit=True).where(id=1).exec()

from datetime import datetime
t = datetime.now().time()
d = datetime.now().date()
ok = DB.update(events, auto_commit=False).set(time=t).where(id=6).exec()
DB.commit()

# other possible variants for values: values([t]), values([d, t])
# other possible variants for returning: returning(events.date, events.time), returning(['date', 'time']), returning('date', 'time')
query = events.insert(events.date, events.time, auto_commit=True).values([[d, t], [None, t]]).returning('*')
data = query.all()

# you can also execute fully-raw queries; if you need to return values, 
use 'config_fields' to define results' names (not necessary for 'list' data format) 
data = DB.exec('select * from get_book_authors(1) as f(id int, name varchar)').config_fields('id', 'name').all()
print(data)

Table's meta-data

Using this package you can easily discover your database. DB instance provides information about table's name, its columns (with their name and type) and info about primary and foreign keys. Example of function which prints all info about existing tables is shown below.

def print_tables():
    tables = DB.meta['tables']
    for table_name, table in tables.items():
        meta = table.meta
        print(f"
===--- {meta['table_name']} ---===")
        for field_name, field in meta['fields'].items():
            pk_flag = field.primary_key is True  # or field == meta['primary_key']
            print(f"{'(*)' if pk_flag else '   '} {field.name}: {field.type}")

        if len(meta['foreign_keys']):
            print('Constraints:')
            for fields_with_fk in meta['foreign_keys']:
                fk = fields_with_fk.foreign_key
                print(f'	Foreign key: {fields_with_fk.name} references {fk.table.meta["table_name"]}({fk.name})')

and the result can be:

===--- publications ---===
    book_id: integer
    isbn: bigint
(*) id: integer
    created_at: timestamp with time zone
    isbn13: bigint
    language_code: character varying
    publication_year: smallint
    info: jsonb
    updated_at: timestamp with time zone
Constraints:
	Foreign key: book_id references books(id)

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

qrookDB-1.3.3.1.tar.gz (22.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

qrookDB-1.3.3.1-py3-none-any.whl (42.5 kB view details)

Uploaded Python 3

File details

Details for the file qrookDB-1.3.3.1.tar.gz.

File metadata

  • Download URL: qrookDB-1.3.3.1.tar.gz
  • Upload date:
  • Size: 22.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.8.10

File hashes

Hashes for qrookDB-1.3.3.1.tar.gz
Algorithm Hash digest
SHA256 25d3da1c37caba94c321a84a316a23cf8ef523c7fc217f5ae6e9e6093626b7a0
MD5 136bff4046e3d48d9137eff6da49d30a
BLAKE2b-256 c3fcfe942092ea5a792b3f1290915c8f82404305586320d1d6968fa2059e82ac

See more details on using hashes here.

File details

Details for the file qrookDB-1.3.3.1-py3-none-any.whl.

File metadata

  • Download URL: qrookDB-1.3.3.1-py3-none-any.whl
  • Upload date:
  • Size: 42.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.8.10

File hashes

Hashes for qrookDB-1.3.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 17954ca2bdeb2d5c1513b14d1b377239c5d7711315065174f9403cd07548783b
MD5 1c503801ddaf4d3f2b57a25a38ada33a
BLAKE2b-256 e318a6e8bb32bcfedbeff68e6e7e287ec83f6c03873cb1fe611261a51f89fb26

See more details on using hashes here.

Supported by

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