picorm 0.1.4

Small ORM with limited functions for multiple database engines for pet-projects

picorm

Picorm is a small ORM with limited functions for multiple database engines for pet-projects, mostly for simple CRUD operations in cases, when you don't want to introduce a solid ORM like SQLAlchemy or whatever, but still want to keep storage-related stuff out of your code.

Getting Started

Installation

To install from pypi:

pip install picorm

Simple usage

from picorm import FileStorage as Storage # import one of storage implementations

storage = Storage('path_to_database_file') # create storage object

# every collection that you need to store must inherit from storage's Table class
class Users(storage.Table): 
    def __init__(self, fields = {}):
        defaults = OrderedDict([('key', 'users')]) # specify table name
        for k, v in fields.items():
            defaults[k] = v
        super().__init__(defaults)
        storage.create('users', OrderedDict([ # specify table name and desired fields to be stored
            ('key', storage.types['int']), 
            ('id', storage.types['int']),
            ('name', storage.types['str']),
            ('type', storage.types['str']),
        ]))
        # every query on storage.users will return object of this class if not specified otherwise
        class User(self.Record): 
            def __init__(self, fields = {}):
                # default values for fields
                defaults = OrderedDict([
                    ('key', -1), 
                    ('id', -1),
                    ('name', ':null'),
                    ('type', ':null'),
                ])
                for k, v in fields.items():
                    defaults[k] = v
                super().__init__(defaults)
            # that's it, you can add your own methods and properties
        self.User = User # attach classes to table object
users = Users() # create table object
users.Record = users.User # make every query return object of class User

Storage querying

new_user = users.User({'id': 42, 'name': 'foo'}) # create record, you can do it this way or through storage.users.User
users.add (new_user) # place it in storage
found_user = users.find_one({'name': 'foo'}) # get storage Record - an object of class User
found_user.get('id') # get record's field value
found_user.set({'name': 'bar'}) # change desired fields
storage.disconnect() # don't forget to disconnect from storage if you're planning to switch engines

Return different subclasses of table record

In those cases, when you need queries to return various subclasses of table record, you can simply introduce them after User definition in example:

class Users(storage.Table): 
    def __init__(self, fields = {}):
        # ...
        class Player(User): # an example of subclassing table Record
            type = 'player'
            def __init__(self, fields):
                overrides = {'type': Player.type}
                merged = {**fields, **overrides}
                super().__init__(merged)
        
        # ...
        self.Player = Player # attach class to table object
        
        # create a type -> class map to return objects of different subclasses of table record
        self.type_class_map = { 
            Player.type: Player,
            User.type: User,
            ':null': User, # "default" class to wrap record
        }

# make every query return object of either Player or User class based on "type" field value
users.Record = lambda fields: users.type_class_map[fields['type']](fields)

Table methods

method	arguments	returns
create	self, name, schema, log	None
find	self, selector	list of Record objects
find_one	self, selector	Record object or None
find_max	self, key	Record object or None
add	self, record	None
remove	self, record	None

Record operations

method	arguments	returns
set	self, fields	None
get	self, key	Record's field value

Supported engines

• File storage
• SQLite storage

Development

Environment setup

1. Install Python 3.9+
2. Install virtualenv

   pip install virtualenv
   

3. Clone this project
4. From project directory, run

   virtualenv .env
   

   Note: This will create a virtual environment using the Python version that virtualenv was run with (which will be the version it was installed with). To use a specific Python version, run:

   virtualenv --python=<path_to_other_python_version> .env
   # For example, this might look like
   virtualenv --python=/usr/bin/python3.6 .env
   

5. Assuming you are using the bash shell, run:

   source .env/bin/activate
   

   For other shells, see the other activate.* scripts in the .env/bin/ directory. If you are on Windows, run:

   .env\Scripts\activate.bat
   

6. Install all of the required packages using

   pip install -r requirements.txt
   

Testing

This project uses tox -> pytest. To trigger tests either run tox or pytest optionally with -vv and -s flags for verbosity and prints.

Packaging module

Run the following command to package picorm module:

python -m pip install --upgrade build
python -m build

Generated archive and .whl package will be placed in dist directory.

Contributions

PR are always welcome!