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# Python-generated files
__pycache__/
*.py[oc]
build/
dist/
wheels/
*.egg-info
# Virtual environments
.venv
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[codz]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py.cover
*.lcov
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
# Pipfile.lock
# UV
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# uv.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
# poetry.lock
# poetry.toml
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
# pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
# https://pdm-project.org/en/latest/usage/project/#working-with-version-control
# pdm.lock
# pdm.toml
.pdm-python
.pdm-build/
# pixi
# Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
# pixi.lock
# Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
# in the .venv directory. It is recommended not to include this directory in version control.
.pixi/*
!.pixi/config.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule*
celerybeat.pid
# Redis
*.rdb
*.aof
*.pid
# RabbitMQ
mnesia/
rabbitmq/
rabbitmq-data/
# ActiveMQ
activemq-data/
# SageMath parsed files
*.sage.py
# Environments
.env
.envrc
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
# .idea/
# Abstra
# Abstra is an AI-powered process automation framework.
# Ignore directories containing user credentials, local state, and settings.
# Learn more at https://abstra.io/docs
.abstra/
# Visual Studio Code
# Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore
# that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
# and can be added to the global gitignore or merged into this file. However, if you prefer,
# you could uncomment the following to ignore the entire vscode folder
# .vscode/
# Temporary file for partial code execution
tempCodeRunnerFile.py
# Ruff stuff:
.ruff_cache/
# PyPI configuration file
.pypirc
# Marimo
marimo/_static/
marimo/_lsp/
__marimo__/
# Streamlit
.streamlit/secrets.toml
generated/
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3.12
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[project]
name = "sync-protocol"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
authors = [
{ name = "Alireza Rabie", email = "alireza@aazerra.dev" }
]
requires-python = ">=3.12"
dependencies = [
"click>=8.4.2",
"jinja2>=3.1.6",
]
[project.scripts]
schema= "generator.main:cli"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[tool.hatch.build.targets.wheel]
packages = ["src/generator"]
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{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://sadtech.ir/schemas/operation.schema.json",
"title": "Operation",
"description": "An operation is a single action that can be performed on the database by sync protocol.",
"type": "object",
"properties": {
"id": {
"description": "The unique identifier of the operation.",
"type": "string"
},
"type": {
"description": "The type of the operation.",
"type": "string",
"enum": [
"insert",
"update",
"delete"
]
},
"device_id": {
"description": "The unique identifier of the device that performed the operation.",
"type": "string"
},
"timestamp": {
"description": "The timestamp of the operation.",
"type": "string",
"format": "int64"
},
"payload": {
"description": "The payload of the operation.",
"type": "object"
},
"entity_type": {
"description": "The type of the entity that the operation is performed on.",
"type": "string"
},
"entity_id": {
"description": "The unique identifier of the entity that the operation is performed on.",
"type": "string"
}
}
}
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{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://sadtech.ir/schemas/snapshot.schema.json",
"title": "Snapshot",
"description": "A snapshot is a complete copy of the database on the server. It is sent to the device when the device's local database is out of sync with the server's database.",
"type": "object",
"properties": {
"id": {
"description": "The unique identifier of the snapshot.",
"type": "string"
},
"cursor": {
"description": "The cursor is a string that represents the last known state of the database on the device. It is used to determine which operations need to be sent to the device.",
"type": "integer"
},
"data": {
"description": "The data is a complete copy of the database on the server. It is sent to the device when the device's local database is out of sync with the server's database.",
"type": "object"
},
"timestamp": {
"description": "The timestamp of the snapshot.",
"type": "string",
"format": "int64"
}
}
}
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{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://sadtech.ir/schemas/sync-request.schema.json",
"title": "SyncRequest",
"description": "A sync request is a request sent by a device to the server to synchronize its local database with the server's database.",
"type": "object",
"properties": {
"device_id": {
"description": "The unique identifier of the device that is sending the sync request.",
"type": "string"
},
"cursor": {
"description": "The cursor is a string that represents the last known state of the database on the device. It is used to determine which operations need to be sent to the device.",
"type": "integer"
},
"operations": {
"description": "The operations are the changes that have been made to the database on the device since the last sync. They are sent to the server to be applied to the server's database.",
"type": "array",
"items": {
"$ref": "operation.schema.json"
}
}
},
"required": [
"device_id",
"cursor",
"operations"
]
}
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{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://sadtech.ir/schemas/sync-response.schema.json",
"title": "SyncResponse",
"description": "A sync response is a response sent by the server to a device to synchronize its local database with the server's database.",
"type": "object",
"properties": {
"cursor": {
"description": "The cursor is a string that represents the last known state of the database on the device. It is used to determine which operations need to be sent to the device.",
"type": "integer"
},
"operations": {
"description": "The operations are the changes that have been made to the database on the device since the last sync. They are sent to the server to be applied to the server's database.",
"type": "array",
"items": {
"$ref": "operation.schema.json"
}
},
"snapshot": {
"description": "The snapshot is a complete copy of the database on the server. It is sent to the device when the device's local database is out of sync with the server's database.",
"$ref": "snapshot.schema.json"
}
},
"required": [
"cursor",
"operations"
]
}
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from .python import PythonGenerator
from .base import BaseGenerator
language_registry: dict[str, BaseGenerator] = {"python": PythonGenerator}
__all__ = ["language_registery"]
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from abc import ABC, abstractmethod
from pathlib import Path
import json
from jinja2 import Environment, FileSystemLoader
class BaseGenerator(ABC):
def __init__(self, schema_dir: str | Path):
self.schema_dir = Path(schema_dir)
lanaguges_dir = Path(__file__).parent
template_dir = lanaguges_dir / "templates"
self.env = Environment(
loader=FileSystemLoader(template_dir),
trim_blocks=True,
lstrip_blocks=True,
)
self.schemas: dict[str, dict] = {}
self._load_schemas()
@property
def interface_name(self):
return self.schema.get("title")
@abstractmethod
def generate(self): ...
def _load_schemas(self):
for path in self.schema_dir.glob("*.json"):
with path.open() as f:
schema = json.load(f)
self.schemas[path.name] = schema
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from dataclasses import dataclass
from pathlib import Path
from .base import BaseGenerator
@dataclass
class TypeInfo:
type: str
imports: set[str]
@dataclass
class Field:
name: str
type: str
description: str | None = None
imports: set[str] | None = None
@dataclass
class Model:
name: str
description: str
fields: list[Field]
class PythonGenerator(BaseGenerator):
TYPE_MAP = {
"string": "str",
"integer": "int",
"number": "float",
"boolean": "bool",
"object": "dict",
}
FORMAT_MAP = {
"int64": "int",
}
def generate(self, output_dir: str | Path, make_all: bool, schema_file: str | None):
output_dir = Path(output_dir)
output_dir.mkdir(
parents=True,
exist_ok=True,
)
generated = set()
if make_all:
for schema_file in self.schemas:
self._generate_schema(
schema_file=schema_file,
output_dir=output_dir,
generated=generated,
)
return
self._generate_schema(
schema_file=schema_file,
output_dir=output_dir,
generated=generated,
)
def _generate_schema(
self,
schema_file: str,
output_dir: Path,
generated: set[str],
):
# Already generated
if schema_file in generated:
return
schema = self.schemas.get(schema_file)
if schema is None:
raise ValueError(f"Schema not found: {schema_file}")
# Mark as generated before resolving dependencies.
#
# This also prevents infinite recursion if schemas
# eventually reference each other.
generated.add(schema_file)
# First generate all referenced schemas.
for ref in self._find_refs(schema):
ref_file = self._ref_to_filename(ref)
self._generate_schema(
schema_file=ref_file,
output_dir=output_dir,
generated=generated,
)
# Now generate this schema itself.
model = self._parse_model(schema)
imports = self._collect_imports([model])
template = self.env.get_template("python.jinja2")
content = template.render(
model=model,
imports=sorted(imports),
)
module_name = self._schema_to_module(schema_file)
output_file = output_dir / f"{module_name}.py"
output_file.write_text(
content,
encoding="utf-8",
)
def _find_refs(self, schema: dict) -> list[str]:
"""
Recursively find all $ref values inside a schema.
"""
refs = []
if "$ref" in schema:
refs.append(schema["$ref"])
for value in schema.values():
if isinstance(value, dict):
refs.extend(self._find_refs(value))
elif isinstance(value, list):
for item in value:
if isinstance(item, dict):
refs.extend(self._find_refs(item))
return refs
def _ref_to_filename(self, ref: str) -> str:
"""
Convert:
operation.schema.json
into:
operation.schema.json
Also handles:
./operation.schema.json
"""
return Path(ref).name
def _parse_model(
self,
schema: dict,
) -> Model:
name = schema["title"]
fields = []
required = set(schema.get("required", []))
for (
field_name,
field_schema,
) in schema.get(
"properties",
{},
).items():
type_info = self._resolve_type(field_schema)
field_type = type_info.type
if field_name not in required:
field_type = f"{field_type} | None"
fields.append(
Field(
name=field_name,
type=field_type,
description=field_schema.get("description"),
imports=type_info.imports,
)
)
return Model(
name=name,
description=schema.get(
"description",
"",
),
fields=fields,
)
def _resolve_type(
self,
schema: dict,
) -> TypeInfo:
# $ref
if "$ref" in schema:
return self._resolve_ref(schema["$ref"])
# array
if schema.get("type") == "array":
item = self._resolve_type(schema["items"])
return TypeInfo(
type=f"list[{item.type}]",
imports=item.imports,
)
# format
schema_format = schema.get("format")
if schema_format in self.FORMAT_MAP:
return TypeInfo(
type=self.FORMAT_MAP[schema_format],
imports=set(),
)
# primitive
json_type = schema.get("type")
if json_type in self.TYPE_MAP:
return TypeInfo(
type=self.TYPE_MAP[json_type],
imports=set(),
)
raise ValueError(f"Unsupported schema: {schema}")
def _resolve_ref(
self,
ref: str,
) -> TypeInfo:
filename = self._ref_to_filename(ref)
schema = self.schemas.get(filename)
if schema is None:
raise ValueError(f"Referenced schema not found: {filename}")
model_name = schema["title"]
module_name = self._schema_to_module(filename)
return TypeInfo(
type=model_name,
imports={f"from .{module_name} import {model_name}"},
)
def _schema_to_module(
self,
filename: str,
) -> str:
return filename.removesuffix(".schema.json").replace("-", "_")
def _collect_imports(
self,
models: list[Model],
) -> set[str]:
imports = set()
for model in models:
for field in model.fields:
if field.imports:
imports.update(field.imports)
return imports
@@ -0,0 +1,12 @@
from pydantic import BaseModel
{% for import in imports %}
{{ import }}
{% endfor %}
class {{ model.name }}(BaseModel):
"""{{ model.description }}"""
{% for field in model.fields %}
{{ field.name }}: {{ field.type }}
{% endfor %}
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from .languages import language_registry
import json
from typing import Any, Optional
import click
@click.group()
def cli():
pass
def _generate(generator, schema_name, output_dir, make_all):
generator.generate(output_dir, schema_file=schema_name, make_all=make_all)
@cli.command()
@click.option("--schema-dir", default="./schema", help="Schema directory")
@click.option("--language", required=False, help="Schema directory")
@click.option("--output-dir", default="generated", help="Schema directory")
@click.option("--all", is_flag=True, help="Schema directory")
@click.argument("schema", default=None)
def generate(schema, schema_dir, all, output_dir, language: Optional[str] = None):
if schema is None and not all:
raise ValueError()
if language:
generator_cls = language_registry.get(language)
if generator_cls is None:
raise ValueError()
generator = generator_cls(schema_dir)
_generate(generator, schema, output_dir, make_all=all)
else:
for generator_cls in language_registry.values():
generator = generator_cls(schema_dir)
_generate(generator, schema, output_dir, make_all=all)
if __name__ == "__main__":
cli()
Generated
+114
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@@ -0,0 +1,114 @@
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revision = 3
requires-python = ">=3.12"
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