Metadata-Version: 2.1
Name: datalite
Version: 0.2
Summary: A small package that binds dataclasses to an sqlite database
Home-page: https://github.com/ambertide/datalite
Author: Ege Ozkan
Author-email: egeemirozkan24@gmail.com
License: UNKNOWN
Description: # Datalite
        
        Datalite is a simple Python
        package that binds your dataclasses to a table in a sqlite3 database,
        using it is extremely simple, say that you have a dataclass definition,
        just add the decorator `@datalite(db_name="db.db")` to the top of the
        definition, and the dataclass will now be bound to the file `db.db`
        
        For example:
        
        ```python
        from dataclasses import dataclass
        from datalite import datalite
        
        
        @datalite(db_path="db.db")
        @dataclass
        class Student:
            student_id: int
            student_name: str = "John Smith"
        ```
        
        This snippet will generate a table in the sqlite3 database file `db.db` with
        table name `student` and rows `student_id`, `student_name` with datatypes
        integer and text, respectively. The default value for `student_name` is
        `John Smith`.
        
        ## Entry manipulation
        
        After creating an object traditionally, given that you used the `datalite` decorator,
        the object has two new methods: `.create_entry()` and `.remove_entry()`, you
        can add the object to its associated table using the former, and remove it
        using the latter.
        
        ```python
        student = Student(10, "Albert Einstein")
        student.create_entry()  # Adds the entry to the table associated in db.db
        student.remove_entry()  # Removes from the table.
        ```
        
        But what if you have created your object in a previous session, or wish
        to remove an object unreachable? ie: If the object is already garbage 
        collected by the Python interpreter? `remove_from(class_, obj_id)` is
        a function that can be used for this express purpose, for instance:
        
        ```python
        remove_from(Student, 2)  # Removes the Student with obj_id 2.
        ```
        
        Object IDs are auto-incremented, and correspond to the order the entry were
        inserted onto the system.
        
        ## Fetching Records
        > :warning: **Limitation! Fetch can only fetch limited classes correctly**: int, float and str!
        
        Finally, you may wish to recreate objects from a table that already exist, for
        this purpose we have the function `fetch_from(class_, object_id)` as well
        as `is_fetchable(className, object_id)` former fetches a record from the
        SQL database whereas the latter checks if it is fetchable (most likely
        to check if it exists.)
        
        ```python
        >>> fetch_from(Student, 2)
        Student(student_id=10, student_name='Albert Einstein')
        ```
        
        We have three helper methods, `fetch_range(class_, range_)` and
        `fetch_all(class_)` are very similar: the former fetches the records
        fetchable from the object id range provided by the user, whereas the
        latter fetches all records. Both return a tuple of `class_` objects.
        
        The last helper method, `fetch_if(class_, condition)` fetches all
        the records of type `class_` that fit a certain condition. Here conditions
        must be written is SQL syntax.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
