# Copyright (C) 2022 Anaconda, Inc # Copyright (C) 2023 conda # SPDX-License-Identifier: BSD-3-Clause """ This module collects examples of environments that were hard to solve, required workarounds or didn't meet users' expectations... specially if compared to conda classic. """ import json import os import pytest from conda.common.compat import on_linux from .repodata_time_machine import repodata_time_machine from .utils import conda_subprocess def test_pydantic_182_not_on_python_311(): """ See daico007's report on https://github.com/conda/conda-libmamba-solver/issues/115 - The original environment file didn't specify a Python version. - conda classic does find that Python 3.10 and pydantic 1.8.2 are compatible - libsolv has to try all Python versions, starting with 3.11 as of writing, and then tries different pydantic versions. It finds 0.18.2 is compatible, but because it's noarch with an open-ended upper bound. - If we do specify that we want a Python version for which pydantic 1.8.2 is available, libsolv correctly finds it. After #381, where stricter specs are ordered first in the solver task, the solver does find the correct pydantic as classic does. """ env = os.environ.copy() env["CONDA_SUBDIR"] = "linux-64" env["CONDA_OVERRIDE_CUDA"] = "12.0" args = ( "create", "-n", "unused", "--dry-run", "--override-channels", "-c", "conda-forge", "--json", ) pkgs = ( "numpy", "sympy", "unyt<=2.8", "boltons", "lxml", "pydantic<1.9.0", "networkx", "ele>=0.2.0", "forcefield-utilities", ) # p = conda_subprocess( # *args, # "--solver=classic", # *pkgs, # env=env, # ) # data = json.loads(p.stdout) # pydantic = next(pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "pydantic") # assert pydantic["version"] == "1.8.2" p = conda_subprocess( *args, "--solver=rattler", *pkgs, env=env, ) data = json.loads(p.stdout) pydantic = next(pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "pydantic") assert pydantic["version"] == "1.8.2" # this was the bug (not finding 1.8.2) p = conda_subprocess( *args, "--solver=rattler", *pkgs, "python<3.11", env=env, ) data = json.loads(p.stdout) pydantic = next(pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "pydantic") assert pydantic["version"] == "1.8.2" @pytest.mark.skipif(not on_linux, reason="Only relevant on Linux") def test_gpu_cpu_mutexes(): """ See: - https://github.com/conda/conda-libmamba-solver/issues/115#issuecomment-1399040871 - https://github.com/conda/conda-libmamba-solver/issues/115#issuecomment-1399040867 - https://github.com/conda/conda-libmamba-solver/issues/131 This behaviour difference is known and explained at https://github.com/conda/conda-libmamba-solver/issues/131#issuecomment-1440745813. If at some point this changes (e.g. rattler fix), this test will capture it. """ args = ( "create", "-n", "unused", "--dry-run", "--json", "--override-channels", "-c", "conda-forge", "-c", "pyg", "-c", "pytorch", ) pkgs = ( "cpuonly", "pyg=2.1.0", "python=3.9", "pytorch::pytorch=1.12", ) env = os.environ.copy() env["CONDA_SUBDIR"] = "linux-64" p = conda_subprocess( *args, "--solver=classic", *pkgs, env=env, ) data = json.loads(p.stdout) found = 0 target_pkgs = ("pytorch", "pyg") for pkg in data["actions"]["LINK"]: if pkg["name"] in target_pkgs: found += 1 assert "cpu" in pkg["build_string"] elif pkg["name"] == "cudatoolkit": raise AssertionError("CUDA shouldn't be installed due to 'cpuonly'") assert found == len(target_pkgs) p = conda_subprocess( *args, "--solver=rattler", *pkgs, env=env, ) data = json.loads(p.stdout) # This should not happen, but it does. See docstring. assert next(pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "cudatoolkit") # This was working correctly between Oct-Dec 2025, but broke again when # `__cuda=0=0` was removed from non-cuda systems # https://github.com/conda/conda/commit/8d36401a0c8b378720db1dc786c0e026bb621fb0 p = conda_subprocess( *args, "--solver=rattler", "cpuonly", "pyg=2.1.0", "python=3.9", "pytorch::pytorch", # more recent pytorch versions seem to be properly packaged env=env, ) data = json.loads(p.stdout) # This should not happen, but it does. See docstring. assert not next((pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "cudatoolkit"), None) @pytest.mark.skipif(not on_linux, reason="Slow. Running on Linux only.") def test_old_panel(tmp_path): """ https://github.com/conda/conda-libmamba-solver/issues/64 We could not reproduce this test until #381. Note this is not a problem in the non-time-machine'd repodata (as of 2023-11-16 at least). It got eventually fixed with https://github.com/conda/conda-libmamba-solver/pull/647. """ os.chdir(tmp_path) print("Patching repodata...") old_repodata = os.path.abspath( repodata_time_machine( channels=["conda-forge", "pyviz/label/dev"], timestamp_str="2022-06-16 12:31:00", subdirs=("osx-64", "noarch"), ) ) with open(f"{old_repodata}/conda-forge/osx-64/repodata.json") as f: for line in f: # Make sure we have patched the repodata correctly # Python 3.11 only appeared in October 2022 assert '"python-3.11.0-' not in line channel_prefix = f"file://{old_repodata}/" env = os.environ.copy() env["CONDA_SUBDIR"] = "osx-64" env["CONDA_REPODATA_THREADS"] = "1" env["CONDA_DEFAULT_THREADS"] = "1" env["CONDA_FETCH_THREADS"] = "1" env["CONDA_REMOTE_CONNECT_TIMEOUT_SECS"] = "1" env["CONDA_REMOTE_MAX_RETRIES"] = "1" env["CONDA_REMOTE_BACKOFF_FACTOR"] = "1" env["CONDA_REMOTE_READ_TIMEOUT_SECS"] = "1" args = ( "create", "-n", "unused", "--dry-run", "--json", "--override-channels", "-c", f"{channel_prefix}pyviz/label/dev", "-c", f"{channel_prefix}conda-forge", "--repodata-fn=repodata.json", ) pkgs = ( "python=3.8", "lumen", ) for solver in ("classic", "rattler"): print("Solving with", solver) p = conda_subprocess( *args, "--solver", solver, *pkgs, env=env, ) data = json.loads(p.stdout) panel = next(pkg for pkg in data["actions"]["LINK"] if pkg["name"] == "panel") if solver == "classic": assert panel["version"] == "0.14.0a2" else: # Rattler difference. Seems to run into the same problem libmamba had. assert panel["version"] == "0.1.0a14"