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import re
from abc import ABC, abstractmethod
from contextlib import contextmanager, suppress
from copy import deepcopy
from functools import partial
from os import linesep
from pathlib import Path
from haddock import EmptyPath, log, modules_defaults_path
from haddock.core.defaults import MODULE_IO_FILE, INTERACTIVE_RE_SUFFIX
from haddock.core.exceptions import ConfigurationError
from haddock.core.typing import (
Any,
Container,
FilePath,
Generator,
Literal,
Optional,
ParamDict,
Union,
)
from haddock.gear import config
from haddock.gear.clean_steps import clean_output
from haddock.gear.known_cns_errors import find_all_cns_errors
from haddock.gear.parameters import config_mandatory_general_parameters
from haddock.gear.yaml2cfg import read_from_yaml_config, find_incompatible_parameters
from haddock.libs.libhpc import HPCScheduler
from haddock.libs.libgrid import GRIDScheduler, ping_dirac
from haddock.libs.libio import folder_exists, working_directory
from haddock.libs.libmpi import MPIScheduler
from haddock.libs.libontology import ModuleIO, PDBFile
from haddock.libs.libparallel import Scheduler
from haddock.libs.libtimer import log_time
from haddock.libs.libutil import recursive_dict_update
modules_folder = Path(__file__).resolve().parent
_folder_match_regex = "[a-zA-Z]*/"
modules_category = {
module.name: category.name
for category in modules_folder.glob(_folder_match_regex)
for module in category.glob(_folder_match_regex)
}
"""Indexes each module in its specific category. Keys are Paths to the module,
values are their categories. Categories are the modules parent folders."""
modules_names = set(modules_category.keys())
category_hierarchy = [
"topology",
"sampling",
"refinement",
"scoring",
"analysis",
"extras",
]
# this dictionary defines non-mandatory general parameters that can be defined
# as global parameters thus affect all modules, or, instead, can be defined per
# module where the module definition overwrites global definition. Not all
# modules will use these parameters. It is the responsibility of the module to
# extract the parameters it needs.
# the config file is in modules/defaults.cfg
non_mandatory_general_parameters_defaults = read_from_yaml_config(modules_defaults_path) # noqa : E501
incompatible_defaults_params = find_incompatible_parameters(modules_defaults_path)
config_readers = {
".yaml": read_from_yaml_config,
# module params are internally generated as a mix of toml and cfg format
# set strict to false
".cfg": partial(config.load, strict=False),
}
_step_folder_regex = tuple(
r"[0-9]+_" + mod_name for mod_name in modules_category.keys()
)
step_folder_regex = "(" + "|".join(_step_folder_regex) + ")"
"""
String for regular expression to match module folders in a run directory.
It will match folders with a numeric prefix followed by underscore ("_")
followed by the name of a module.
Example: https://regex101.com/r/roHls9/1
"""
step_folder_regex_re = re.compile(step_folder_regex)
"""
Compiled regular expression from :py:const:`step_folder_regex`.
It will match folders with a numeric prefix followed by underscore ("_")
followed by the name of a module.
Example: https://regex101.com/r/roHls9/1
"""
@contextmanager
def _not_valid_config() -> Generator[None, None, None]:
try:
yield
except KeyError as err:
emsg = (
"The configuration file extension is not supported. "
f"Supported types are {', '.join(config_readers.keys())}."
)
raise ConfigurationError(emsg) from err
class BaseHaddockModule(ABC):
"""HADDOCK3 module's base class."""
name: str
def __init__(self, order: int, path: Path, params_fname: FilePath) -> None:
"""
HADDOCK3 modules base class.
Parameters
----------
params : dict or path to HADDOCK3 configuration file
A dictionary or a path to a HADDOCK3 configuration file
containing the initial module parameters. Usually this is
defined by the default params.
"""
self.order = order
self.path = path
self.previous_io = self._load_previous_io()
# instantiate module's parameters
self._origignal_config_file = params_fname
with _not_valid_config():
extension = Path(params_fname).suffix
self._original_params = config_readers[extension](params_fname)
self._params: ParamDict = {}
self.update_params(update_from_cfg_file=params_fname)
# Some modules might need to overwrite parameters defined by the user
# This can be done via `_output_params` - whatever the module adds to this
# variable, will be propagated down to other modules.
# For example: `topoaa` needs to pass `ligand_param_fname` to `rigidbody` module
# so somewhere in the `topoaa` module we need to set: `self._output_params[VALUE] = VAR`
# IMPORANT: This will be propagated to ALL modules and can have unexpected effects
self._output_params: dict = {}
@property
def params(self) -> ParamDict:
"""Configuration parameters.""" # noqa: D401
return self._params
def reset_params(self) -> None:
"""Reset parameters to the ones used to instantiate the class."""
self._params.clear()
self.update_params(**self._original_params)
def update_params(
self,
update_from_cfg_file: Optional[FilePath] = None,
**params: Any,
) -> None:
"""
Update the modules parameters.
Add/update to the current modules parameters the ones given in
the function call. If you want to enterily replace the modules
parameters to their default values use the `reset_params()`
method.
Update takes places recursively, that is, nested dictionaries
will be updated accordingly.
To update the current config with the parameters defined in an
HADDOCK3 configuration file use the `update_from_cfg_file`
parameter.
To update from a JSON file, first load the JSON into a
dictionary and unpack the dictionary to the function call.
Examples
--------
>>> m.update_params(param1=value1, param2=value2)
>>> m.update_params(**param_dict)
>>> m.update_params(update_from_cfg_file=path_to_file)
# if you wish to start from scratch
>>> m.reset_params()
>>> m.update_params(...)
"""
if update_from_cfg_file and params:
_msg = "You can not provide both `update_from_cfg_file` and key arguments."
raise TypeError(_msg)
if update_from_cfg_file:
with _not_valid_config():
extension = Path(update_from_cfg_file).suffix
params = config_readers[extension](update_from_cfg_file)
# the updating order is relevant
_n = recursive_dict_update(
non_mandatory_general_parameters_defaults, self._params
)
self._params = recursive_dict_update(_n, params)
self._fill_emptypaths()
self._confirm_fnames_exist()
def save_config(self, path: FilePath) -> None:
"""Save current parameters to a HADDOCK3 config file."""
# creates this dictionary for the config to have the module name
# key in brackets, for example:
#
# [topoaa]
# ...
ignore = config_mandatory_general_parameters.union(
non_mandatory_general_parameters_defaults
) # noqa: 501
params = deepcopy(self.params)
with suppress(KeyError):
for key in list(ignore):
params.pop(key)
config.save({self.name: params}, path)
def add_parent_to_paths(self) -> None:
"""Add parent path to paths."""
# convert paths to relative by appending parent
for key, value in self.params.items():
if value and key.endswith("_fname"):
if not Path(value).is_absolute():
self.params[key] = Path("..", value)
return
@abstractmethod
def _run(self) -> None: ...
def run(self, **params: Any) -> None:
"""Execute the module."""
log.info(f"Running [{self.name}] module")
self.update_params(**params)
self.add_parent_to_paths()
with working_directory(self.path):
self._run()
log.info(f"Module [{self.name}] finished.")
def clean_output(self) -> None:
"""
Clean module output folder.
See Also
--------
:py:func:`haddock.gear.clean_steps.clean_output`
"""
with log_time("cleaning output files took"):
clean_output(self.path, self.params["ncores"])
@classmethod
@abstractmethod
def confirm_installation(cls) -> None:
"""
Confirm the third-party software needed for the module is installed.
HADDOCK3's own modules should just return.
"""
return
def export_io_models(self, faulty_tolerance: float = 0.0) -> None:
"""
Export input/output to the ModuleIO interface.
Modules that do not perform any operation on PDB files should have
input = output.
This function implements a common interface for all modules.
Parameters
----------
faulty_tolerance : int, default 0
The percentage of missing output allowed. If 20 is given,
raises an error if 20% of the expected output is missing (not
saved to disk).
"""
self.output_models: Union[list[PDBFile], dict[int, PDBFile]]
assert self.output_models, "`self.output_models` cannot be empty."
io = ModuleIO()
# add the input models
io.add(self.previous_io.output, "i")
# add the output models
io.add(self.output_models, "o")
# Removes un-generated outputs and compute percentage of ungenerated
faulty = io.check_faulty()
# Save outputs
io.save()
# Check if number of generated outputs is under the tolerance threshold
if faulty > faulty_tolerance:
_msg = (
f"{faulty:.2f}% of output was not generated for this module "
f"and tolerance was set to {faulty_tolerance:.2f}%."
)
# Try to detect CNS errors
if detected_errors := find_all_cns_errors(self.path):
_msg += linesep
for error in detected_errors.values():
_msg += f"{str(error['error'])}{linesep}"
# Show final error message
self.finish_with_error(_msg)
def finish_with_error(self, reason: object = "Module has failed.") -> None:
"""Finish with error message."""
if isinstance(reason, Exception):
raise RuntimeError("Module has failed.") from reason
else:
raise RuntimeError(reason)
def _load_previous_io(
self,
filename: FilePath = MODULE_IO_FILE,
) -> ModuleIO:
if self.order == 0:
self._num_of_input_molecules = 0
return ModuleIO()
io = ModuleIO()
previous_io = Path(self.previous_path(), filename)
if previous_io.is_file():
io.load(previous_io)
self._num_of_input_molecules = len(io.output)
return io
def previous_path(self) -> Path:
"""Give the path from the previous calculation."""
previous = get_module_steps_folders(self.path.resolve().parent)
try:
# return Path(previous[self.order - 1])
return self.last_step_folder(previous, self.order - 1)
except IndexError:
return self.path
@staticmethod
def last_step_folder(folders, index):
"""Retrieve last step folder."""
with_ind = [folder for folder in folders if int(folder.split("_")[0]) == index]
nb_with_ind = len(with_ind)
# No matching index
if nb_with_ind == 0:
raise IndexError
# Only one matching index
elif nb_with_ind == 1:
return with_ind[0]
# Case of multiple matching index
else:
for folder in with_ind:
if folder.split("_")[-1] != INTERACTIVE_RE_SUFFIX:
return folder
return with_ind[0]
def log(self, msg: str, level: str = "info") -> None:
"""
Log a message with a common header.
Currently the header is the [MODULE NAME] in square brackets.
Parameters
----------
msg : str
The log message.
level : str
The level log: 'debug', 'info', ...
Defaults to 'info'.
"""
getattr(log, level)(f"[{self.name}] {msg}")
def _confirm_fnames_exist(self) -> None:
for param, value in self._params.items():
if param.endswith("_fname") and value:
if not Path(value).exists():
raise FileNotFoundError(f"File not found: {str(value)!r}")
def _fill_emptypaths(self) -> None:
"""Fill empty paths."""
for param, value in list(self._params.items()):
if param.endswith("_fname") and not value:
self._params[param] = EmptyPath()
EngineMode = Literal["batch", "local", "mpi", "grid"]
def get_engine(
mode: str,
params: dict[Any, Any],
) -> partial[Union[HPCScheduler, Scheduler, MPIScheduler, GRIDScheduler]]:
"""
Create an engine to run the jobs.
Parameters
----------
mode : str
The type of engine to create
params : dict
A dictionary containing parameters for the engine.
`get_engine` will retrieve from `params` only those parameters
needed and ignore the others.
"""
# a bit of a factory pattern here
# this might end up in another module but for now its fine here
if mode == "batch":
return partial( # type: ignore
HPCScheduler,
target_queue=params["queue"],
queue_limit=params["queue_limit"],
concat=params["concat"],
)
elif mode == "local":
return partial( # type: ignore
Scheduler,
ncores=params["ncores"],
max_cpus=params["max_cpus"],
)
elif mode == "mpi":
return partial(MPIScheduler, ncores=params["ncores"]) # type: ignore
elif mode == "grid":
# `grid` mode should only be used IF the grid is reachable,
# if not it should fallback to `local`
grid_available = ping_dirac()
if grid_available:
return partial(GRIDScheduler, params=params) # type: ignore
else:
log.warning("GRID is not available, activating fallback using `mode=local`")
return partial( # type: ignore
Scheduler,
ncores=params["ncores"],
max_cpus=params["max_cpus"],
)
else:
available_engines = ("batch", "local", "mpi", "grid")
raise ValueError(
f"Scheduler `mode` {mode!r} not recognized. "
f"Available options are {', '.join(available_engines)}"
)
def get_module_steps_folders(
folder: FilePath,
modules: Optional[Container[int]] = None,
) -> list[str]:
"""
Return a sorted list of the step folders in a running directory.
Example
-------
Consider the folder structure:
run_dir/
0_topoaa/
1_rigidbody/
2_caprieval/
3_bad_module_name/
data/
>>> get_module_steps_folders("run_dir")
>>> ["0_topoaa", "1_rigidbody", "2_caprieval"]
Parameters
----------
folder : str or Path
Path to the run directory, or to the folder containing the step
folders.
Returns
-------
list of str
List containing strings with the names of the step folders.
"""
# Make sure the folder exists, otherwise this might throw an error
if not Path(folder).exists():
return []
folders = (p.name for p in Path(folder).iterdir() if p.is_dir())
steps = sorted(
(f for f in folders if step_folder_regex_re.search(f)),
key=lambda x: int(x.split("_")[0]),
)
if modules:
steps = [
st
for st in steps
if all(
[
int(st.split("_")[0]) in modules,
st.split("_")[1] in modules_names,
]
)
]
return steps
def is_step_folder(path: FilePath) -> bool:
"""
Assess whether a folder is a possible step folder.
The folder is considered a step folder if has a zero or positive
integer index followed by a name of a module.
Parameters
----------
path : str or pathlib.Path
The path to the folder.
Returns
-------
bool
Whether the folder is a step folder or not.
"""
path = Path(path)
folder_exists(path)
main_folder_name = path.name
parts = main_folder_name.split("_")
if len(parts) == 2 and parts[0].isdigit() and parts[1] in modules_category:
return True
else:
return False
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