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tiny ORM for SQL-databases

Project description

This package represents a new ORM to work with SQL-syntax databases (for now, only PostgreSQL is supported).

Initializing

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. 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)

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