✨ Python 3.11 compatible

.github/workflows/docker_push.yaml

@@ -7,7 +7,7 @@ on:
 
 env:
   DEFAULT_LINUX: "slim"
-  DEFAULT_PYTHON: "3.10"
+  DEFAULT_PYTHON: "3.11"
 
 jobs:
   docker_push:
@@ -19,7 +19,7 @@ jobs:
     strategy:
       matrix:
         linux: ["slim"]
-        python: ["3.7", "3.8", "3.9", "3.10"]
+        python: ["3.7", "3.8", "3.9", "3.10", "3.11"]
     steps:
       - name: Check out the repo
         uses: actions/checkout@master

.github/workflows/test_and_publish.yaml

@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python: [ "3.7", "3.8", "3.9", "3.10" ]
+        python: [ "3.7", "3.8", "3.9", "3.10", "3.11"]
     container:
       image: python:${{ matrix.python }}
     steps:
@@ -43,7 +43,7 @@ jobs:
         run: ./scripts/flake8
       - id: mypy
         name: Static types check
-        run: ./scripts/mypy
+        run: ./scripts/mypy .
       - id: tests
         name: Tests
         run: ./scripts/test

.github/workflows/test_pull_request_branch.yaml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python: ["3.7", "3.8", "3.9", "3.10"]
+        python: ["3.7", "3.8", "3.9", "3.10", "3.11"]
     container:
       image: python:${{ matrix.python }}
     steps:
@@ -39,7 +39,7 @@ jobs:
         run: ./scripts/flake8
       - id: mypy
         name: Static types check
-        run: ./scripts/mypy
+        run: ./scripts/mypy .
       - id: tests
         name: Tests
         run: ./scripts/test

.gitignore

@@ -26,6 +26,7 @@ var/
 *.egg
 *dist/
 pip-wheel-metadata/
+.python-version
 
 # Installer logs
 pip-log.txt

flama/models/components.py

@@ -2,12 +2,15 @@
 import json
 import typing
 
-import torch
-
 from flama import exceptions
 from flama.injection import Component
 from flama.serialize import ModelFormat, loads
 
+try:
+    import torch
+except Exception:  # pragma: no cover
+    torch = None  # type: ignore
+
 __all__ = ["Model", "PyTorchModel", "SKLearnModel", "TensorFlowModel", "ModelComponent", "ModelComponentBuilder"]
 
 
@@ -33,6 +36,8 @@ def inspect(self) -> typing.Any:
         }
 
     def predict(self, x: typing.List[typing.List[typing.Any]]) -> typing.Any:
+        assert torch is not None, "`torch` must be installed to use PyTorchModel."
+
         try:
             return self.model(torch.Tensor(x)).tolist()
         except ValueError as e:

pyproject.toml

@@ -26,7 +26,7 @@ include = ["flama/py.typed", "flama/templates/**/*"]
 exclude = []
 
 [tool.poetry.dependencies]
-python = "^3.7"
+python = ">=3.7,<3.12"
 starlette = ">=0.21.0,<1.0.0"
 click = "^8.1"
 uvicorn = "^0.18.3"
@@ -62,27 +62,41 @@ ipython = [
 isort = "^5.1"
 python-multipart = "^0.0.5"
 flake8 = "^5.0"
-black = { version = "^22.3", extras = ["d"]}
-uvicorn = {version = ">=0.18.3,<1.0.0", extras = ["standard"]}
-httpx = "^0.23.0"
+black = { version = "^22.3", extras = ["d"] }
+uvicorn = { version = ">=0.18.3,<1.0.0", extras = ["standard"] }
+httpx = ">=0.23,<1.0.0"
 aiosqlite = ">=0.11.0,<1.0.0"
-requests = "^2.22.0"
-Faker = "^8.2.0"
-marshmallow = "^3.0"
+requests = "^2.22"
+Faker = "^8.2"
 python-forge = "^18.6"
-apispec = "^5.0"
-typesystem = "^0.4.1"
 SQLAlchemy = { version = "^1.4", extras = ["asyncio"] }
-gevent = "^21.12.0"
+gevent = "^22.10"
 mypy = "^0.942"
+pre-commit = "^2.19"
+asyncmock = { version = "^0.4", python = ">=3.7,<3.8" }
+
+[tool.poetry.group.schemas]
+optional = true
+
+[tool.poetry.group.schemas.dependencies]
+marshmallow = "^3.0"
+apispec = "^5.0"
+typesystem = "^0.4"
+
+[tool.poetry.group.ml]
+optional = true
+
+[tool.poetry.group.ml.dependencies]
+numpy = [
+    { version = "^1.21.0", python = ">=3.7,<3.8" },
+    { version = "^1.23", python = ">=3.8" }
+]
 scikit-learn = [
     { version = "^1.0.0", python = ">=3.7,<3.8" },
-    { version = "^1.1.0", python = ">=3.8" }
+    { version = "^1.1", python = ">=3.8" }
 ]
-tensorflow-cpu = { version = "^2.9", python = ">=3.7,<3.11" }
-pre-commit = "^2.19.0"
-torch = "^1.12.1"
-asyncmock = { version = "^0.4.2", python = ">=3.7,<3.8" }
+tensorflow-cpu = { version = "^2.10", python = ">=3.7,<3.11" }
+torch = { version = "^1.12", python = ">=3.7,<3.11" }
 
 [tool.black]
 line-length = 120

scripts/install

@@ -3,7 +3,7 @@
 install_pkg()
 {
   echo "🔥 Install python requirements..."
-  poetry install --with dev "$@"
+  poetry install --with dev,schemas,ml "$@"
   cd templates
   echo "🔥 Install js requirements..."
   npm i

tests/asserts.py

@@ -0,0 +1,28 @@
+from time import sleep
+
+
+def assert_recursive_contains(first, second):
+    if isinstance(first, dict) and isinstance(second, dict):
+        assert first.keys() <= second.keys()
+
+        for k, v in first.items():
+            assert_recursive_contains(v, second[k])
+    elif isinstance(first, (list, set, tuple)) and isinstance(second, (list, set, tuple)):
+        assert len(first) <= len(second)
+
+        for i, _ in enumerate(first):
+            assert_recursive_contains(first[i], second[i])
+    else:
+        assert first == second
+
+
+def assert_read_from_file(file_path, value, max_sleep=10):
+    read_value = None
+    i = 0
+    while not read_value and i < max_sleep:
+        sleep(i)
+        with open(file_path) as f:
+            read_value = f.read()
+        i += 0.1
+
+    assert read_value == value

tests/conftest.py

@@ -1,8 +1,7 @@
 import asyncio
 import sys
-import typing
 from contextlib import ExitStack
-from time import sleep
+from pathlib import Path
 
 import marshmallow
 import pytest
@@ -13,12 +12,29 @@
 from flama import Flama
 from flama.sqlalchemy import metadata
 from flama.testclient import TestClient
+from tests.utils import ExceptionContext, check_param_lib_installed
 
 if sys.version_info >= (3, 8):  # PORT: Remove when stop supporting 3.7 # pragma: no cover
     from unittest.mock import AsyncMock
 else:  # pragma: no cover
     from asyncmock import AsyncMock
 
+try:
+    import sklearn
+    from sklearn.linear_model import LogisticRegression
+except Exception:
+    sklearn = None
+
+try:
+    import tensorflow as tf
+except Exception:
+    tf = None
+
+try:
+    import torch
+except Exception:
+    torch = None
+
 DATABASE_URL = "sqlite+aiosqlite://"
 
 
@@ -30,18 +46,6 @@ def event_loop():
     loop.close()
 
 
-class ExceptionContext:
-    def __init__(self, context, exception: typing.Optional[Exception] = None):
-        self.context = context
-        self.exception = exception
-
-    def __enter__(self):
-        return self.context.__enter__()
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        return self.context.__exit__(exc_type, exc_val, exc_tb)
-
-
 @pytest.fixture(scope="function")
 def exception(request):
     if request.param is None:
@@ -149,28 +153,55 @@ def asgi_send():
     return AsyncMock()
 
 
-def assert_recursive_contains(first, second):
-    if isinstance(first, dict) and isinstance(second, dict):
-        assert first.keys() <= second.keys()
+def sklearn_model():
+    return LogisticRegression(), LogisticRegression
 
-        for k, v in first.items():
-            assert_recursive_contains(v, second[k])
-    elif isinstance(first, (list, set, tuple)) and isinstance(second, (list, set, tuple)):
-        assert len(first) <= len(second)
 
-        for i, _ in enumerate(first):
-            assert_recursive_contains(first[i], second[i])
-    else:
-        assert first == second
+def tensorflow_model():
+    tf_model = tf.keras.models.Sequential(
+        [
+            tf.keras.layers.Flatten(input_shape=(28, 28)),
+            tf.keras.layers.Dense(128, activation="relu"),
+            tf.keras.layers.Dropout(0.2),
+            tf.keras.layers.Dense(10, activation="softmax"),
+        ]
+    )
+
+    tf_model.compile(optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"])
+
+    return tf_model, tf.keras.models.Sequential
+
+
+def torch_model():
+    class Model(torch.nn.Module):
+        def forward(self, x):
+            return x + 10
 
+    return Model(), torch.jit.RecursiveScriptModule
 
-def assert_read_from_file(file_path, value, max_tries=10):
-    read_value = None
-    i = 0
-    while not read_value and i < max_tries:
-        sleep(i)
-        with open(file_path) as f:
-            read_value = f.read()
-        i += 1
 
-    assert read_value == value
+@pytest.fixture(scope="function")
+@check_param_lib_installed
+def model(request):
+    return {"sklearn": sklearn_model, "tensorflow": tensorflow_model, "torch": torch_model}[request.param]()[0]
+
+
+@pytest.fixture(scope="function")
+@check_param_lib_installed
+def serialized_model_class(request):
+    return {"sklearn": sklearn_model, "tensorflow": tensorflow_model, "torch": torch_model}[request.param]()[1]
+
+
+@pytest.fixture(scope="session")
+def model_paths():
+    return {
+        "sklearn": Path("tests/data/sklearn_model.flm"),
+        "tensorflow": Path("tests/data/tensorflow_model.flm"),
+        "torch": Path("tests/data/pytorch_model.flm"),
+    }
+
+
+@pytest.fixture(scope="function")
+@check_param_lib_installed
+def model_path(request, model_paths):
+    return model_paths[request.param]