chore: import upstream snapshot with attribution

tests/projects/test_projects_cli.py

@@ -0,0 +1,244 @@
+import hashlib
+import json
+import logging
+import os
+import shutil
+from pathlib import Path
+from unittest import mock
+
+import pytest
+from click.testing import CliRunner
+
+from mlflow import MlflowClient, cli
+from mlflow.utils import process
+from mlflow.utils.environment import _PythonEnv
+from mlflow.utils.virtualenv import _get_mlflow_virtualenv_root, _get_virtualenv_name
+
+from tests.integration.utils import invoke_cli_runner
+from tests.projects.utils import (
+    GIT_PROJECT_URI,
+    SSH_PROJECT_URI,
+    TEST_DOCKER_PROJECT_DIR,
+    TEST_PROJECT_DIR,
+    TEST_VIRTUALENV_PROJECT_DIR,
+    docker_example_base_image,  # noqa: F401
+)
+
+_logger = logging.getLogger(__name__)
+
+skip_if_skinny = pytest.mark.skipif(
+    "MLFLOW_SKINNY" in os.environ,
+    reason="MLflow skinny does not have dependencies to run this test",
+)
+
+
+@pytest.mark.parametrize("name", ["friend", "friend=you", "='friend'"])
+def test_run_local_params(name):
+    excitement_arg = 2
+    invoke_cli_runner(
+        cli.run,
+        [
+            TEST_PROJECT_DIR,
+            "-e",
+            "greeter",
+            "-P",
+            "greeting=hi",
+            "-P",
+            f"name={name}",
+            "-P",
+            f"excitement={excitement_arg}",
+        ],
+    )
+
+
+@skip_if_skinny
+def test_run_local_with_docker_args(docker_example_base_image):
+    # Verify that Docker project execution is successful when Docker flag and string
+    # commandline arguments are supplied (`tty` and `name`, respectively)
+    invoke_cli_runner(cli.run, [TEST_DOCKER_PROJECT_DIR, "-A", "tty", "-A", "name=mycontainer"])
+
+
+@pytest.mark.parametrize("experiment_name", [b"test-experiment".decode("utf-8"), "test-experiment"])
+def test_run_local_experiment_specification(experiment_name):
+    invoke_cli_runner(
+        cli.run,
+        [
+            TEST_PROJECT_DIR,
+            "-e",
+            "greeter",
+            "-P",
+            "name=test",
+            "--experiment-name",
+            experiment_name,
+        ],
+    )
+
+    client = MlflowClient()
+    experiment_id = client.get_experiment_by_name(experiment_name).experiment_id
+
+    invoke_cli_runner(
+        cli.run,
+        [TEST_PROJECT_DIR, "-e", "greeter", "-P", "name=test", "--experiment-id", experiment_id],
+    )
+
+
+@pytest.fixture(scope="module", autouse=True)
+def clean_mlruns_dir():
+    yield
+    dir_path = os.path.join(TEST_PROJECT_DIR, "mlruns")
+    if os.path.exists(dir_path):
+        shutil.rmtree(dir_path)
+
+
+@skip_if_skinny
+def test_run_local_conda_env():
+    with open(os.path.join(TEST_PROJECT_DIR, "conda.yaml")) as handle:
+        conda_env_contents = handle.read()
+    expected_env_name = "mlflow-{}".format(
+        hashlib.sha1(conda_env_contents.encode("utf-8"), usedforsecurity=False).hexdigest()
+    )
+    try:
+        process._exec_cmd(cmd=["conda", "env", "remove", "--name", expected_env_name])
+    except process.ShellCommandException:
+        _logger.error(
+            "Unable to remove conda environment %s. The environment may not have been present, "
+            "continuing with running the test.",
+            expected_env_name,
+        )
+    invoke_cli_runner(
+        cli.run,
+        [TEST_PROJECT_DIR, "-e", "check_conda_env", "-P", f"conda_env_name={expected_env_name}"],
+    )
+
+
+@skip_if_skinny
+def test_run_uv_python_env():
+    python_env_path = os.path.join(TEST_VIRTUALENV_PROJECT_DIR, "python_env.yaml")
+    python_env_contents = _PythonEnv.from_yaml(python_env_path)
+
+    work_dir_path = Path(TEST_VIRTUALENV_PROJECT_DIR)
+    virtualenv_root = Path(_get_mlflow_virtualenv_root())
+    env_name = _get_virtualenv_name(python_env_contents, work_dir_path)
+    env_dir = virtualenv_root / env_name
+
+    if env_dir.exists():
+        shutil.rmtree(env_dir)
+
+    invoke_cli_runner(
+        cli.run,
+        [TEST_VIRTUALENV_PROJECT_DIR, "-e", "test", "--env-manager", "uv"],
+        env={"UV_PRERELEASE": "allow"},
+    )
+
+
+@skip_if_skinny
+def test_run_git_https():
+    # Invoke command twice to ensure we set Git state in an isolated manner (e.g. don't attempt to
+    # create a git repo in the same directory twice, etc)
+    assert GIT_PROJECT_URI.startswith("https")
+    invoke_cli_runner(cli.run, [GIT_PROJECT_URI, "--env-manager", "local", "-P", "alpha=0.5"])
+    invoke_cli_runner(cli.run, [GIT_PROJECT_URI, "--env-manager", "local", "-P", "alpha=0.5"])
+
+
+@pytest.mark.skipif(
+    "GITHUB_ACTIONS" in os.environ, reason="SSH keys are unavailable in GitHub Actions"
+)
+def test_run_git_ssh():
+    # Note: this test requires SSH authentication to GitHub, and so is disabled in GitHub Actions,
+    # where SSH keys are unavailable. However it should be run locally whenever logic related to
+    # running Git projects is modified.
+    assert SSH_PROJECT_URI.startswith("git@")
+    invoke_cli_runner(cli.run, [SSH_PROJECT_URI, "--env-manager", "local", "-P", "alpha=0.5"])
+    invoke_cli_runner(cli.run, [SSH_PROJECT_URI, "--env-manager", "local", "-P", "alpha=0.5"])
+
+
+@pytest.mark.skipif(
+    "GITHUB_ACTIONS" in os.environ, reason="SSH keys are unavailable in GitHub Actions"
+)
+def test_run_git_ssh_from_release_version():
+    # Note: this test requires SSH authentication to GitHub, and so is disabled in GitHub Actions,
+    # where SSH keys are unavailable. However it should be run locally whenever logic related to
+    # running Git projects is modified.
+    assert SSH_PROJECT_URI.startswith("git@")
+    invoke_cli_runner(
+        cli.run, [SSH_PROJECT_URI, "--no-conda", "-P", "alpha=0.5", "-v", "version_testing"]
+    )
+    invoke_cli_runner(
+        cli.run, [SSH_PROJECT_URI, "--no-conda", "-P", "alpha=0.5", "-v", "version_testing"]
+    )
+
+
+@pytest.mark.notrackingurimock
+def test_run_databricks_cluster_spec(tmp_path):
+    cluster_spec = {
+        "spark_version": "5.0.x-scala2.11",
+        "num_workers": 2,
+        "node_type_id": "i3.xlarge",
+    }
+    cluster_spec_path = tmp_path.joinpath("cluster-spec.json")
+    with open(cluster_spec_path, "w") as handle:
+        json.dump(cluster_spec, handle)
+
+    with mock.patch("mlflow.projects._run") as run_mock:
+        for cluster_spec_arg in [json.dumps(cluster_spec), cluster_spec_path]:
+            invoke_cli_runner(
+                cli.run,
+                [
+                    TEST_PROJECT_DIR,
+                    "-b",
+                    "databricks",
+                    "--backend-config",
+                    cluster_spec_arg,
+                    "-e",
+                    "greeter",
+                    "-P",
+                    "name=hi",
+                ],
+                env={"MLFLOW_TRACKING_URI": "databricks://profile"},
+            )
+            assert run_mock.call_count == 1
+            _, run_kwargs = run_mock.call_args_list[0]
+            assert run_kwargs["backend_config"] == cluster_spec
+            run_mock.reset_mock()
+        res = CliRunner().invoke(
+            cli.run,
+            [
+                TEST_PROJECT_DIR,
+                "-m",
+                "databricks",
+                "--cluster-spec",
+                json.dumps(cluster_spec) + "JUNK",
+                "-e",
+                "greeter",
+                "-P",
+                "name=hi",
+            ],
+            env={"MLFLOW_TRACKING_URI": "databricks://profile"},
+        )
+        assert res.exit_code != 0
+
+
+def test_mlflow_run():
+    with mock.patch("mlflow.cli.projects") as mock_projects:
+        result = CliRunner().invoke(cli.run)
+        mock_projects.run.assert_not_called()
+        assert "Missing argument 'URI'" in result.output
+
+    with mock.patch("mlflow.cli.projects") as mock_projects:
+        CliRunner().invoke(cli.run, ["project_uri"])
+        mock_projects.run.assert_called_once()
+
+    with mock.patch("mlflow.cli.projects") as mock_projects:
+        CliRunner().invoke(cli.run, ["--experiment-id", "5", "project_uri"])
+        mock_projects.run.assert_called_once()
+
+    with mock.patch("mlflow.cli.projects") as mock_projects:
+        CliRunner().invoke(cli.run, ["--experiment-name", "random name", "project_uri"])
+        mock_projects.run.assert_called_once()
+
+    with mock.patch("mlflow.cli.projects") as mock_projects:
+        result = CliRunner().invoke(
+            cli.run, ["--experiment-id", "51", "--experiment-name", "name blah", "uri"]
+        )
+        mock_projects.run.assert_not_called()
+        assert "Specify only one of 'experiment-name' or 'experiment-id' options." in result.output