#8 compatibility dbapi2/sqlite3

.devcontainer/py3.6-dev/Dockerfile

@@ -4,3 +4,6 @@ ADD https://dl.yarnpkg.com/debian/pubkey.gpg /etc/apt/trusted.gpg.d/yarn.asc
 
 RUN chmod +r /etc/apt/trusted.gpg.d/*.asc && \
     echo "deb http://dl.yarnpkg.com/debian/ stable main" > /etc/apt/sources.list.d/yarn.list
+
+COPY install-legacy-extensions.sh /usr/local/bin/install-legacy-extensions.sh
+RUN chmod +x /usr/local/bin/install-legacy-extensions.sh

.devcontainer/py3.6-dev/devcontainer.json

@@ -17,29 +17,24 @@
 	// "forwardPorts": [],
 
 	// Use 'postCreateCommand' to run commands after the container is created.
-	// "postCreateCommand": "pip3 install --user -r requirements.txt",
+	"postCreateCommand": "install-legacy-extensions.sh",
 
 	// Configure tool-specific properties.
 	// Py3.6 support (switch extensions to `pre-release` and `install another version`):
 	// Pylance v2022.6.30
 	// Python v2022.8.1
-	// Python Debugger v2023.1.XXX (pre-release version | debugpy v1.5.1)
+	// Python Debugger v2023.1.12492010 (pre-release version | debugpy v1.5.1)
 	// Black Formatter v2022.2.0
 	// Isort v2022.1.11601002 (pre-release)
 	"customizations": {
 		"vscode": {
 			"extensions": [
 				"littlefoxteam.vscode-python-test-adapter",
 				"jkillian.custom-local-formatters",
-				"ms-python.vscode-pylance",
-				"ms-python.python",
-				"ms-python.debugpy",
-				"ms-python.black-formatter",
-				"ms-python.isort",
 				"ms-toolsai.jupyter"
 			]
 		}
-	}
+	},
 
 	// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
 	// "remoteUser": "root"

.devcontainer/py3.6-dev/install-legacy-extensions.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+code --install-extension "[email protected]"
+code --install-extension "[email protected]"
+code --install-extension "[email protected]"
+code --install-extension "[email protected]"
+code --install-extension "[email protected]"

.devcontainer/py3.7/devcontainer.json

@@ -0,0 +1,38 @@
+// For format details, see https://aka.ms/devcontainer.json. For config options, see the
+// README at: https://github.com/devcontainers/templates/tree/main/src/python
+{
+	"name": "Python 3.7",
+	// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
+	"image": "mcr.microsoft.com/devcontainers/python:3.7",
+	"features": {
+		"ghcr.io/warrenbuckley/codespace-features/sqlite:1": {}
+	},
+
+	// Features to add to the dev container. More info: https://containers.dev/features.
+	// "features": {},
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	// "forwardPorts": [],
+
+	// Use 'postCreateCommand' to run commands after the container is created.
+	// "postCreateCommand": "pip3 install --user -r requirements.txt",
+
+	// Configure tool-specific properties.
+	"customizations": {
+		"vscode": {
+			"extensions": [
+				"littlefoxteam.vscode-python-test-adapter",
+				"jkillian.custom-local-formatters",
+				"ms-python.vscode-pylance",
+				"ms-python.python",
+				"ms-python.debugpy",
+				"ms-python.black-formatter",
+				"ms-python.isort",
+				"ms-toolsai.jupyter"
+			]
+		}
+	}
+
+	// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
+	// "remoteUser": "root"
+}

.github/workflows/test.yaml

@@ -13,7 +13,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.6", "3.12"]
+        # last supported for sqlitecloud, last security maintained, last release
+        python-version: ["3.6", "3.8", "3.12"]
 
     steps:
     - uses: actions/checkout@v4

.gitignore

@@ -2,7 +2,7 @@
 build/
 experiments/
 sdk/
-venv/
+.venv*/
 main.dSYM/
 .env
 *.pyc
@@ -12,6 +12,11 @@ main.dSYM/
 .DS_Store
 
 .idea
-SqliteCloud.egg-info
+sqlitecloud.egg-info
 
 playground.ipynb
+
+src/tests/assets/*-shm
+src/tests/assets/*-wal
+
+chinook.sqlite

README.md

@@ -4,32 +4,43 @@
   <img src="https://sqlitecloud.io/social/logo.png" height="300" alt="SQLite Cloud logo">
 </p>
 
-![Build Status](https://github.com/sqlitecloud/sqlitecloud-py/actions/workflows/deploy.yaml/badge.svg "Build Status")
-[![codecov](https://codecov.io/github/sqlitecloud/python/graph/badge.svg?token=38G6FGOWKP)](https://codecov.io/github/sqlitecloud/python)
+![Build Status](https://github.com/sqlitecloud/sqlitecloud-py/actions/workflows/test.yaml/badge.svg "Build Status")
+[![codecov](https://codecov.io/gh/sqlitecloud/sqlitecloud-py/graph/badge.svg?token=38G6FGOWKP)](https://codecov.io/gh/sqlitecloud/sqlitecloud-py)
 ![PyPI - Version](https://img.shields.io/pypi/v/sqlitecloud?link=https%3A%2F%2Fpypi.org%2Fproject%2FSqliteCloud%2F)
 ![PyPI - Downloads](https://img.shields.io/pypi/dm/sqlitecloud?link=https%3A%2F%2Fpypi.org%2Fproject%2FSqliteCloud%2F)
 ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/sqlitecloud?link=https%3A%2F%2Fpypi.org%2Fproject%2FSqliteCloud%2F)
 
 
-- [Driver for SQLite Cloud](#driver-for-sqlite-cloud)
-- [Example](#example)
+- [SQLite Cloud](#)
+- [Compatibility with sqlite3 API](#compatibility-with-sqlite3-api)
+  - [Autocommit transactions: Difference between sqlitecloud and sqlite3](#autocommit-transactions-difference-between-sqlitecloud-and-sqlite3)
+- [Installation and Usage](#installation-and-usage)
 - [SQLite Cloud loves sqlite3](#sqlite-cloud-loves-sqlite3)
+- [SQLite Cloud for SQLAlchemy (beta)](#sqlite-cloud-for-sqlalchemy-beta)
 - [SQLite Cloud for Pandas DataFrame](#sqlite-cloud-for-pandas-dataframe)
 
 ---
 
 [SQLite Cloud](https://sqlitecloud.io) is a powerful Python package that allows you to interact with the SQLite Cloud database seamlessly. It provides methods for various database operations. This package is designed to simplify database operations in Python applications, making it easier than ever to work with SQLite Cloud.
 
 
-#### Compatibility with sqlite3 API
+## Compatibility with sqlite3 API
 
-We aim for full compatibility with the Python built-in [sqlite3](https://docs.python.org/3.6/library/sqlite3.html) API (based on Python [PEP 249](https://peps.python.org/pep-0249)), with the primary distinction being that our driver connects to SQLite Cloud databases. This allows you to migrate your local SQLite databases to SQLite Cloud without needing to modify your existing Python code that uses the sqlite3 API.
+We aim for full compatibility with the Python built-in [sqlite3](https://docs.python.org/3.6/library/sqlite3.html) API (based on Python DBAPI 2.0 [PEP 249](https://peps.python.org/pep-0249)), with the primary distinction being that our driver connects to SQLite Cloud databases. This allows you to migrate your local SQLite databases to SQLite Cloud without needing to modify your existing Python code that uses the sqlite3 API.
 
 - Documentation: Our API closely follows the sqlite3 API. You can refer to the sqlite3 documentation for most functionality. The list of implemented features are documented [here](https://github.com/sqlitecloud/sqlitecloud-py/issues/8).
 - Source: [https://github.com/sqlitecloud/sqlitecloud-py](https://github.com/sqlitecloud/sqlitecloud-py)
 - Site: [https://sqlitecloud.io](https://sqlitecloud.io/developers)
 
-## Example
+### Autocommit transactions: Difference between sqlitecloud and sqlite3
+
+In `sqlitecloud`, autocommit is **always enabled**, and we currently do not support disabling it. This means that the `isolation_level` is always set to `None`, resulting in autocommit being permanently on.
+
+This behavior differs from the sqlite3 Python module, where autocommit can be controlled (see details in the section [Controlling Transactions](https://docs.python.org/3.6/library/sqlite3.html#controlling-transactions) in the official documentation).
+
+To manage transactions in sqlitecloud, you should explicitly use the `BEGIN`, `ROLLBACK`, `SAVEPOINT`, and `RELEASE` commands as needed.
+
+## Installation and Usage
 
 ```bash
 $ pip install sqlitecloud
@@ -87,6 +98,81 @@ for row in cursor:
     print(row)
 ```
 
+## SQLite Cloud for SQLAlchemy (beta)
+
+_This is an initial release, features and stability may not be guaranteed in all scenarios._
+
+_If you encounter any bugs or issues, please feel free to open an issue on our GitHub repository._
+
+We’ve implemented the initial support for `sqlitecloud` with [SQLAlchemy](https://www.sqlalchemy.org/), allowing you to utilize all standard SQLAlchemy operations and queries.
+For further information, please see the dedicated [REDAME](https://github.com/sqlitecloud/sqlitecloud-py/tree/%238-compatibility-sqlite3-dbapi2/sqlalchemy-sqlitecloud).
+
+### Example
+
+_The example is based on `chinook.sqlite` databse on SQLite Cloud_
+
+Install the package:
+
+```bash
+$ pip install sqlalchemy-sqlitecloud
+```
+
+
+```python
+import sqlalchemy
+from sqlalchemy import Column, ForeignKey, Integer, String
+from sqlalchemy.dialects import registry
+from sqlalchemy.orm import backref, declarative_base, relationship, sessionmaker
+
+Base = declarative_base()
+
+
+class Artist(Base):
+    __tablename__ = "artists"
+
+    ArtistId = Column("ArtistId", Integer, primary_key=True)
+    Name = Column("Name", String)
+    Albums = relationship("Album", backref=backref("artist"))
+
+
+class Album(Base):
+    __tablename__ = "albums"
+
+    AlbumId = Column("AlbumId", Integer, primary_key=True)
+    ArtistId = Column("ArtistId", Integer, ForeignKey("artists.ArtistId"))
+    Title = Column("Title", String)
+
+# SQLite Cloud connection string
+connection_string = "sqlitecloud://myhost.sqlite.cloud:8860/mydatabase.sqlite?apikey=myapikey"
+
+engine = sqlalchemy.create_engine(connection_string)
+Session = sessionmaker(bind=engine)
+session = Session()
+
+name = "John Doe"
+query = sqlalchemy.insert(Artist).values(Name=name)
+result_insert = session.execute(query)
+
+title = "The Album"
+query = sqlalchemy.insert(Album).values(
+    ArtistId=result_insert.lastrowid, Title=title
+)
+session.execute(query)
+
+query = (
+    sqlalchemy.select(Artist, Album)
+    .join(Album, Artist.ArtistId == Album.ArtistId)
+    .where(Artist.ArtistId == result_insert.lastrowid)
+)
+
+result = session.execute(query).fetchone()
+
+print("Artist Name: " + result[0].Name)
+print("Album Title: " + result[1].Title)
+
+```
+
+
 ## SQLite Cloud for Pandas DataFrame
 
 [Pandas](https://pypi.org/project/pandas/) is a Python package for data manipulation and analysis. It provides high-performance, easy-to-use data structures, such as DataFrame.