Update readme, bump version

README.md

@@ -1,10 +1,16 @@
 # aiodatalite
 
+[![Maintainability](https://api.codeclimate.com/v1/badges/985ef318eb057cefee4f/maintainability)](https://codeclimate.com/github/kotikotprojects/aiodatalite/maintainability)
+[![Test Coverage](https://api.codeclimate.com/v1/badges/985ef318eb057cefee4f/test_coverage)](https://codeclimate.com/github/kotikotprojects/aiodatalite/test_coverage)
+![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/kotikotprojects/aiodatalite/python-publish.yml)
+[![Documentation Status](https://readthedocs.org/projects/aiodatalite/badge/?version=latest)](https://aiodatalite.readthedocs.io/en/latest/?badge=latest)
+![PyPI - Version](https://img.shields.io/pypi/v/aiodatalite)
+
 > [!WARNING]  
 > Original project is a hobby project and it should not be used for security-critical or user facing applications.
 > The same goes for this fork
 
-It should be noted that Datalite is not suitable for secure web applications, it really is only suitable for cases when you can trust user input.
+[Full Documentation](https://aiodatalite.readthedocs.io/en/latest/)
 
 Datalite is a simple Python
 package that binds your dataclasses to a table in a sqlite3 database,
@@ -12,8 +18,6 @@ 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`
 
-[Detailed API reference](https://datalite.readthedocs.io/en/latest/)
-
 ## Download and Install
 
 You can install `aiodatalite` simply by
@@ -40,7 +44,7 @@ from dataclasses import dataclass
 from aiodatalite import datalite
 
 
-@datalite(db_path="db.db")
+@datalite(db_path="db.db", automarkup=True)
 @dataclass
 class Student:
     student_id: int
@@ -52,6 +56,8 @@ table name `student` and rows `student_id`, `student_name` with datatypes
 integer and text, respectively. The default value for `student_name` is
 `John Smith`.
 
+Read more about types and restrictions (most of them have been removed thanks to pickle) in our docs
+
 ## Basic Usage
 
 ### Entry manipulation
@@ -64,10 +70,10 @@ the middle.
 
 ```python
 student = Student(10, "Albert Einstein")
-student.create_entry()  # Adds the entry to the table associated in db.db.
+await student.create_entry()  # Adds the entry to the table associated in db.db.
 student.student_id = 20 # Update an object on memory.
-student.update_entry()  # Update the corresponding record in the database.
-student.remove_entry()  # Removes from the table.
+await student.update_entry()  # Update the corresponding record in the database.
+await student.remove_entry()  # Removes from the table.
 ```
 
 But what if you have created your object in a previous session, or wish
@@ -76,15 +82,13 @@ 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.
+await 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, bytes and str!
 
 Finally, you may wish to recreate objects from a table that already exist, for
 this purpose we have the module `fetch` module, from this you can import `
@@ -93,7 +97,7 @@ former fetches a record from the SQL database given its unique object_id
 whereas the latter checks if it is fetchable (most likely to check if it exists.)
 
 ```python
->>> fetch_from(Student, 2)
+>>> await fetch_from(Student, 2)
 Student(student_id=10, student_name='Albert Einstein')
 ```
 
@@ -110,6 +114,6 @@ and returns the object whose `field` equals the provided `value`.
 
 #### Pagination
 
-`datalite` also supports pagination on `fetch_if`, `fetch_all` and `fetch_where`,
+`aiodatalite` also supports pagination on `fetch_if`, `fetch_all` and `fetch_where`,
 you can specify `page` number and `element_count` for each page (default 10), for
 these functions in order to get a subgroup of records.

pyproject.toml

@@ -1,8 +1,10 @@
 [tool.poetry]
 name = "aiodatalite"
-version = "0.7.3"
+version = "1.0.0"
 description = "A simple Python library to bind dataclasses with databases. Now asynchronous!"
 authors = ["hhh <h@localhost>", "Ege Ozkan <egeemirozkan24@gmail.com>"]
+documentation = "https://aiodatalite.readthedocs.io"
+repository = "https://github.com/kotikotprojects/aiodatalite"
 readme = "README.md"