"""Functions for initializing the Julia environment and installing deps.""" import sys import subprocess import warnings from pathlib import Path import os from julia.api import JuliaError from .version import __version__, __symbolic_regression_jl_version__ juliainfo = None julia_initialized = False julia_kwargs_at_initialization = None julia_activated_env = None def _load_juliainfo(): """Execute julia.core.JuliaInfo.load(), and store as juliainfo.""" global juliainfo if juliainfo is None: from julia.core import JuliaInfo try: juliainfo = JuliaInfo.load(julia="julia") except FileNotFoundError: env_path = os.environ["PATH"] raise FileNotFoundError( f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", ) return juliainfo def _get_julia_env_dir(): # Have to manually get env dir: try: julia_env_dir_str = subprocess.run( ["julia", "-e using Pkg; print(Pkg.envdir())"], capture_output=True, env=os.environ, ).stdout.decode() except FileNotFoundError: env_path = os.environ["PATH"] raise FileNotFoundError( f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", ) return Path(julia_env_dir_str) def _set_julia_project_env(julia_project, is_shared): if is_shared: if is_julia_version_greater_eq(version=(1, 7, 0)): os.environ["JULIA_PROJECT"] = "@" + str(julia_project) else: julia_env_dir = _get_julia_env_dir() os.environ["JULIA_PROJECT"] = str(julia_env_dir / julia_project) else: os.environ["JULIA_PROJECT"] = str(julia_project) def _get_io_arg(quiet): io = "devnull" if quiet else "stderr" io_arg = f"io={io}" if is_julia_version_greater_eq(version=(1, 6, 0)) else "" return io_arg def install(julia_project=None, quiet=False, precompile=None): # pragma: no cover """ Install PyCall.jl and all required dependencies for SymbolicRegression.jl. Also updates the local Julia registry. """ import julia _julia_version_assertion() # Set JULIA_PROJECT so that we install in the pysr environment processed_julia_project, is_shared = _process_julia_project(julia_project) _set_julia_project_env(processed_julia_project, is_shared) if precompile == False: os.environ["JULIA_PKG_PRECOMPILE_AUTO"] = "0" try: julia.install(quiet=quiet) except julia.tools.PyCallInstallError: # Attempt to reset PyCall.jl's build: subprocess.run( [ "julia", "-e", f'ENV["PYTHON"] = "{sys.executable}"; import Pkg; Pkg.build("PyCall")', ], ) # Try installing again: julia.install(quiet=quiet) Main, init_log = init_julia(julia_project, quiet=quiet, return_aux=True) io_arg = _get_io_arg(quiet) if precompile is None: precompile = init_log["compiled_modules"] if not precompile: Main.eval('ENV["JULIA_PKG_PRECOMPILE_AUTO"] = 0') if is_shared: # Install SymbolicRegression.jl: _add_sr_to_julia_project(Main, io_arg) Main.eval("using Pkg") Main.eval(f"Pkg.instantiate({io_arg})") if precompile: Main.eval(f"Pkg.precompile({io_arg})") if not quiet: warnings.warn( "It is recommended to restart Python after installing PySR's dependencies," " so that the Julia environment is properly initialized." ) def _import_error(): return """ Required dependencies are not installed or built. Run the following command in your terminal: python3 -m pysr install """ def _process_julia_project(julia_project): if julia_project is None: is_shared = True processed_julia_project = f"pysr-{__version__}" elif julia_project[0] == "@": is_shared = True processed_julia_project = julia_project[1:] else: is_shared = False processed_julia_project = Path(julia_project) return processed_julia_project, is_shared def is_julia_version_greater_eq(juliainfo=None, version=(1, 6, 0)): """Check if Julia version is greater than specified version.""" if juliainfo is None: juliainfo = _load_juliainfo() current_version = ( juliainfo.version_major, juliainfo.version_minor, juliainfo.version_patch, ) return current_version >= version def _check_for_conflicting_libraries(): # pragma: no cover """Check whether there are conflicting modules, and display warnings.""" # See https://github.com/pytorch/pytorch/issues/78829: importing # pytorch before running `pysr.fit` causes a segfault. torch_is_loaded = "torch" in sys.modules if torch_is_loaded: warnings.warn( "`torch` was loaded before the Julia instance started. " "This may cause a segfault when running `PySRRegressor.fit`. " "To avoid this, please run `pysr.julia_helpers.init_julia()` *before* " "importing `torch`. " "For updates, see https://github.com/pytorch/pytorch/issues/78829" ) def init_julia(julia_project=None, quiet=False, julia_kwargs=None, return_aux=False): """Initialize julia binary, turning off compiled modules if needed.""" global julia_initialized global julia_kwargs_at_initialization global julia_activated_env if not julia_initialized: _check_for_conflicting_libraries() if julia_kwargs is None: julia_kwargs = {"optimize": 3} from julia.core import JuliaInfo, UnsupportedPythonError _julia_version_assertion() processed_julia_project, is_shared = _process_julia_project(julia_project) _set_julia_project_env(processed_julia_project, is_shared) try: info = JuliaInfo.load(julia="julia") except FileNotFoundError: env_path = os.environ["PATH"] raise FileNotFoundError( f"Julia is not installed in your PATH. Please install Julia and add it to your PATH.\n\nCurrent PATH: {env_path}", ) if not info.is_pycall_built(): raise ImportError(_import_error()) from julia.core import Julia try: Julia(**julia_kwargs) except UnsupportedPythonError: # Static python binary, so we turn off pre-compiled modules. julia_kwargs = {**julia_kwargs, "compiled_modules": False} Julia(**julia_kwargs) warnings.warn( "Your system's Python library is static (e.g., conda), so precompilation will be turned off. For a dynamic library, try using `pyenv` and installing with `--enable-shared`: https://github.com/pyenv/pyenv/blob/master/plugins/python-build/README.md#building-with---enable-shared." ) using_compiled_modules = (not "compiled_modules" in julia_kwargs) or julia_kwargs[ "compiled_modules" ] from julia import Main as _Main Main = _Main if julia_activated_env is None: julia_activated_env = processed_julia_project if julia_initialized and julia_kwargs_at_initialization is not None: # Check if the kwargs are the same as the previous initialization init_set = set(julia_kwargs_at_initialization.items()) new_set = set(julia_kwargs.items()) set_diff = new_set - init_set # Remove the `compiled_modules` key, since it is not a user-specified kwarg: set_diff = {k: v for k, v in set_diff if k != "compiled_modules"} if len(set_diff) > 0: warnings.warn( "Julia has already started. The new Julia options " + str(set_diff) + " will be ignored." ) if julia_initialized and julia_activated_env != processed_julia_project: Main.eval("using Pkg") io_arg = _get_io_arg(quiet) # Can't pass IO to Julia call as it evaluates to PyObject, so just directly # use Main.eval: Main.eval( f'Pkg.activate("{_escape_filename(processed_julia_project)}",' f"shared = Bool({int(is_shared)}), " f"{io_arg})" ) julia_activated_env = processed_julia_project if not julia_initialized: julia_kwargs_at_initialization = julia_kwargs julia_initialized = True if return_aux: return Main, {"compiled_modules": using_compiled_modules} return Main def _add_sr_to_julia_project(Main, io_arg): Main.eval("using Pkg") Main.sr_spec = Main.PackageSpec( name="SymbolicRegression", url="https://github.com/MilesCranmer/SymbolicRegression.jl", rev="v" + __symbolic_regression_jl_version__, ) Main.clustermanagers_spec = Main.PackageSpec( name="ClusterManagers", url="https://github.com/JuliaParallel/ClusterManagers.jl", rev="14e7302f068794099344d5d93f71979aaf4fbeb3", ) Main.eval(f"Pkg.add([sr_spec, clustermanagers_spec], {io_arg})") def _escape_filename(filename): """Turn a path into a string with correctly escaped backslashes.""" str_repr = str(filename) str_repr = str_repr.replace("\\", "\\\\") return str_repr def _julia_version_assertion(): if not is_julia_version_greater_eq(version=(1, 6, 0)): raise NotImplementedError( "PySR requires Julia 1.6.0 or greater. " "Please update your Julia installation." ) def _backend_version_assertion(Main): try: backend_version = Main.eval("string(SymbolicRegression.PACKAGE_VERSION)") expected_backend_version = __symbolic_regression_jl_version__ if backend_version != expected_backend_version: # pragma: no cover warnings.warn( f"PySR backend (SymbolicRegression.jl) version {backend_version} " f"does not match expected version {expected_backend_version}. " "Things may break. " "Please update your PySR installation with " "`python3 -m pysr install`." ) except JuliaError: # pragma: no cover warnings.warn( "You seem to have an outdated version of SymbolicRegression.jl. " "Things may break. " "Please update your PySR installation with " "`python3 -m pysr install`." ) def _load_cluster_manager(Main, cluster_manager): Main.eval(f"import ClusterManagers: addprocs_{cluster_manager}") return Main.eval(f"addprocs_{cluster_manager}") def _update_julia_project(Main, is_shared, io_arg): try: if is_shared: _add_sr_to_julia_project(Main, io_arg) Main.eval("using Pkg") Main.eval(f"Pkg.resolve({io_arg})") except (JuliaError, RuntimeError) as e: raise ImportError(_import_error()) from e def _load_backend(Main): try: # Load namespace, so that various internal operators work: Main.eval("using SymbolicRegression") except (JuliaError, RuntimeError) as e: raise ImportError(_import_error()) from e _backend_version_assertion(Main) # Load Julia package SymbolicRegression.jl from julia import SymbolicRegression return SymbolicRegression