Files
NexQuant/test/utils/test_env.py
T
you-n-g 304d3fad2e feat: parallel loop running based on asyncio (#932)
* refactor: split workflow into pkg, add WorkflowTracker & wait_retry

* feat: add async LoopBase with parallel workers and step semaphores

* fix: replace pickle with dill and run blocking tasks via joblib wrapper

* feat: add log format settings, dynamic parallelism & pickle-based snapshot

* fix: default step semaphore to 1 and avoid subprocess when single worker

* merge bowen's changes

* merge tim's changes

* refactor: extract component task mapping, add conditional logger setup

* lint

* refactor: add type hints and safer remain_time metric logging in workflow

* lint

* fix: allow BadRequestError to be pickled via custom copyreg reducer

* fix: stop loop when LoopTerminationError is raised in LoopBase

* lint

* refactor: make log tag context-local using ContextVar for thread safety

* feat: add subproc_step flag and helper to decide subprocess execution

* fix: use ./cache path and normalize relative volume bind paths

* fix: reset loop_idx to 0 on loop restart/resume to ensure correct flow

* fix: avoid chmod on cache and input dirs in Env timeout wrapper

* fix: skip chmod on 'cache' and 'input' dirs using find -prune

* fix: restrict chmod to immediate mount dirs excluding cache/input

* fix: chmod cache and input dirs alongside their contents after entry run

* fix: guard chmod with directory checks for cache and input

* fix: prefix mount_path in chmod command for cache/input dirs

* fix: drop quotes from find exclude patterns to ensure chmod executes

* fix: skip chmod on cache/input directories to avoid warning spam

* feat: support string volume mappings and poll subprocess stdout/stderr

* support remove symbolic link

* test: use dynamic home path and code volume in LocalEnv local_simple

* fix: skip trace and progress update when loop step is withdrawn

* refactor: add clean_workspace util and non-destructive workspace backup

* fix: preserve symlinks when backing up workspace with copytree

* fix: prevent AttributeError when _pbar not yet initialized in LoopBase

* perf: replace shutil.copytree with rsync for faster workspace backup

* fix: cast log directory Path to str in tar command of data science loop

* fix: use portable 'cp -r -P' instead of rsync for workspace backup

* fix: add retry and logging to workspace backup for robustness

* refactor: extract backup_folder helper and reuse in DataScienceRDLoop

* fix: propagate backup errors & default _pbar getattr to avoid error

* fix the division by zero bug

* refactor: execute RD loops via asyncio.run and add necessary imports

* lint

* lint

* lint

---------

Co-authored-by: Xu <v-xuminrui@microsoft.com>
2025-06-12 11:44:14 +08:00

148 lines
6.1 KiB
Python

import os
import sys
import time
import unittest
from pathlib import Path
sys.path.append(str(Path(__file__).resolve().parent.parent))
import shutil
from rdagent.utils.env import (
CondaConf,
LocalConf,
LocalEnv,
QlibDockerConf,
QTDockerEnv,
)
DIRNAME = Path(__file__).absolute().resolve().parent
class QlibLocalEnv(LocalEnv):
def prepare(self) -> None:
if not (Path("~/.qlib/qlib_data/cn_data").expanduser().resolve().exists()):
self.run(
entry="python -m qlib.run.get_data qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn",
)
else:
print("Data already exists. Download skipped.")
class EnvUtils(unittest.TestCase):
def setUp(self):
self.test_workspace = DIRNAME / "test_workspace"
self.test_workspace.mkdir(exist_ok=True)
def tearDown(self):
if self.test_workspace.exists():
shutil.rmtree(self.test_workspace)
# NOTE: Since I don't know the exact environment in which it will be used, here's just an example.
# NOTE: Because you need to download the data during the prepare process. So you need to have pyqlib in your environment.
def test_local(self):
local_conf = LocalConf(
bin_path="/home/v-linlanglv/miniconda3/envs/RD-Agent-310/bin",
default_entry="qrun conf.yaml",
)
qle = QlibLocalEnv(conf=local_conf)
qle.prepare()
conf_path = str(DIRNAME / "env_tpl" / "conf.yaml")
qle.run(entry="qrun " + conf_path)
mlrun_p = DIRNAME / "env_tpl" / "mlruns"
self.assertTrue(mlrun_p.exists(), f"Expected output file {mlrun_p} not found")
def test_local_simple(self):
code_path = DIRNAME / "tmp_code"
code_path.mkdir(exist_ok=True)
# Get user home dynamically
home_bin = str(Path.home() / "miniconda3/bin/")
local_conf = LocalConf(bin_path=home_bin, default_entry="which python")
local_conf.extra_volumes = {str(code_path): "./code"}
print(local_conf)
le = LocalEnv(conf=local_conf)
le.prepare()
res, code = le.run_ret_code(local_path=str(code_path))
print(res, code)
def test_conda_simple(self):
conda_conf = CondaConf(default_entry="which python", conda_env_name="MLE")
le = LocalEnv(conf=conda_conf)
le.prepare()
code_path = DIRNAME / "tmp_code"
code_path.mkdir(exist_ok=True)
res, code = le.run_ret_code(local_path=str(code_path))
print(res, code)
def test_conda_error(self):
conda_conf = CondaConf(conda_env_name="MLE")
le = LocalEnv(conf=conda_conf)
le.prepare()
file_name = f"{time.time()}.py"
with open(self.test_workspace / file_name, "w") as f:
f.write('import json \njson.loads(b\'{"name": "\xa1"}\')')
res, code = le.run_ret_code(local_path=str(self.test_workspace), entry=f"python {file_name}")
assert code == 1
assert "bytes can only contain ASCII literal characters" in res
def test_docker(self):
"""We will mount `env_tpl` into the docker image.
And run the docker image with `qrun conf.yaml`
"""
qtde = QTDockerEnv()
qtde.prepare() # you can prepare for multiple times. It is expected to handle it correctly
# qtde.run("nvidia-smi") # NOTE: you can check your GPU with this command
# the stdout are returned as result
result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry="qrun conf.yaml")
mlrun_p = DIRNAME / "env_tpl" / "mlruns"
self.assertTrue(mlrun_p.exists(), f"Expected output file {mlrun_p} not found")
# read experiment
result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry="python read_exp_res.py")
print(result)
def test_run_ret_code(self):
"""Test the run_ret_code method of QTDockerEnv with both valid and invalid commands."""
qtde = QTDockerEnv()
qtde.prepare()
# Test with a valid command
result, return_code = qtde.run_ret_code(entry='echo "Hello, World!"', local_path=str(self.test_workspace))
print(return_code)
assert return_code == 0, f"Expected return code 0, but got {return_code}"
assert "Hello, World!" in result, "Expected output not found in result"
# Test with an invalid command
_, return_code = qtde.run_ret_code(entry="invalid_command", local_path=str(self.test_workspace))
print(return_code)
assert return_code != 0, "Expected non-zero return code for invalid command"
dc = QlibDockerConf()
dc.running_timeout_period = 1
qtde = QTDockerEnv(dc)
result, return_code = qtde.run_ret_code(entry="sleep 2", local_path=str(self.test_workspace))
print(result)
assert return_code == 124, "Expected return code 124 for timeout"
def test_docker_mem(self):
cmd = 'python -c \'print("start"); import numpy as np; size_mb = 500; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); print("success")\''
qtde = QTDockerEnv(QlibDockerConf(mem_limit="10m"))
qtde.prepare()
result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry=cmd)
self.assertTrue(not result.strip().endswith("success"))
qtde = QTDockerEnv(QlibDockerConf(mem_limit="1g"))
qtde.prepare()
result = qtde.run(local_path=str(DIRNAME / "env_tpl"), entry=cmd)
self.assertTrue(result.strip().endswith("success"))
# The above command equals to the follow commands with dockr cli.sh
# docker run --memory=10m -it --rm local_qlib:latest python -c 'import numpy as np; print(123); size_mb = 1; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); array[0], array[-1] = 1.0, 1.0; print(321)'
# docker run --memory=10g -it --rm local_qlib:latest python -c 'import numpy as np; print(123); size_mb = 1; size = size_mb * 1024 * 1024 // 8; array = np.random.randn(size).astype(np.float64); array[0], array[-1] = 1.0, 1.0; print(321)'
if __name__ == "__main__":
unittest.main()