Source code for minizinc.CLI.instance

#  This Source Code Form is subject to the terms of the Mozilla Public
#  License, v. 2.0. If a copy of the MPL was not distributed with this
#  file, You can obtain one at http://mozilla.org/MPL/2.0/.

import asyncio
import contextlib
import json
import os
import re
import sys
import tempfile
import warnings
from dataclasses import field, make_dataclass
from datetime import timedelta
from enum import EnumMeta
from keyword import iskeyword
from numbers import Number
from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, cast

import minizinc
from minizinc.error import MiniZincError, parse_error
from minizinc.instance import Instance
from minizinc.json import (
    MZNJSONDecoder,
    MZNJSONEncoder,
    decode_async_json_stream,
    decode_json_stream,
)
from minizinc.model import Method, Model, ParPath, UnknownExpression
from minizinc.result import Result, Status, parse_solution, set_stat
from minizinc.solver import Solver

from .driver import CLIDriver, to_python_type

if sys.version_info >= (3, 8):
    from typing import Final

    SEPARATOR: Final[bytes] = str.encode("----------" + os.linesep)
else:
    SEPARATOR: bytes = str.encode("----------" + os.linesep)


class _GeneratedSolution:
    pass


[docs]class CLIInstance(Instance): _driver: CLIDriver _solver: Solver _input: Optional[Dict[str, Type]] = None _output: Optional[Dict[str, Type]] = None _method: Optional[Method] = None _parent: Optional["CLIInstance"] = None _field_renames: List[Tuple[str, str]] def __init__( self, solver: Solver, model: Optional[Model] = None, driver: Optional[CLIDriver] = None, ): super().__init__(solver, model) self._solver = solver self._field_renames = [] if driver is not None: self._driver = driver elif minizinc.default_driver is not None and isinstance( minizinc.default_driver, CLIDriver ): self._driver = cast(CLIDriver, minizinc.default_driver) else: raise Exception("No compatible driver provided") if model is not None: self.output_type = model.output_type self._includes = model._includes.copy() self._code_fragments = model._code_fragments.copy() self._data = dict.copy(model._data) self._enum_map = dict.copy(model._enum_map) self._checker = True # Generate output_type to ensure the same type between different # instances of the same model if self.output_type is None: self.analyse() model.output_type = self.output_type
[docs] @contextlib.contextmanager def branch(self) -> Iterator[Instance]: # TODO: Self reference child = self.__class__(self._solver) child._parent = self # Copy current information from analysis child._method = self.method child.output_type = self.output_type child._output = self._output child._input = self.input with self._lock: yield child
@property def method(self) -> Method: if self._method is None: self.analyse() assert self._method is not None return self._method
[docs] @contextlib.contextmanager def files(self) -> Iterator[List[Path]]: """Gets list of files of the Instance Files will create a list of paths to the files that together form the Instance. Parts of the Instance might be saved to files and are only guaranteed to exist while within the created context. Yields: List of Path objects to existing and created files """ files: List[Path] = [] fragments: List[str] = [] data: Dict[str, Any] = {} inst: Optional["CLIInstance"] = self while inst is not None: for k, v in inst._data.items(): if isinstance(v, UnknownExpression) or k in data: fragments.append(f"{k} = {v};\n") elif isinstance(v, EnumMeta): fragments.append( f"{k} = {{{', '.join([i for i in v.__members__])}}};\n" ) else: data[k] = v fragments.extend(inst._code_fragments) files.extend(inst._includes) inst = inst._parent gen_files = [] try: if len(data) > 0: file = tempfile.NamedTemporaryFile( prefix="mzn_data", suffix=".json", delete=False ) gen_files.append(file) file.write(json.dumps(data, cls=MZNJSONEncoder).encode()) file.close() files.append(Path(file.name)) if len(fragments) > 0 or len(files) == 0: file = tempfile.NamedTemporaryFile( prefix="mzn_fragment", suffix=".mzn", delete=False ) gen_files.append(file) for code in fragments: file.write(code.encode()) file.close() files.append(Path(file.name)) yield files finally: for file in gen_files: file.close() os.remove(file.name)
@property def input(self): if self._input is None or self._method is None: self.analyse() return self._input @property def output(self): if self._output is None or self._method is None: self.analyse() return self._output
[docs] def analyse(self): """Discovers basic information about a CLIInstance Analyses a given instance and discovers basic information about set model such as the solving method, the input parameters, and the output parameters. The information found will be stored among the attributes of the instance. """ with self.files() as files: assert len(files) > 0 output = self._driver.run(["--model-interface-only"] + files, self._solver) if self._driver.parsed_version >= (2, 6, 0): interface = None for obj in decode_json_stream(output.stdout): if obj["type"] == "interface": interface = obj break else: interface = json.loads(output.stdout) old_method = self._method self._method = Method.from_string(interface["method"]) self._input = {} for key, value in interface["input"].items(): self._input[key] = to_python_type(value) old_output = self._output self._output = {} for (key, value) in interface["output"].items(): self._output[key] = to_python_type(value) if interface.get("has_output_item", True): self._output["_output_item"] = str if self._checker: self._output["_checker"] = str if self.output_type is None or ( issubclass(self.output_type, _GeneratedSolution) and (self._output != old_output or self._method != old_method) ): fields = [] self._field_renames = [] if self._method is not Method.SATISFY and "objective" not in self._output: fields.append(("objective", Number)) for k, v in self._output.items(): if k in ["_output_item", "_checker"]: fields.append((k, str, field(default=""))) elif iskeyword(k): warnings.warn( f"MiniZinc field '{k}' is a Python keyword. It has been " f"renamed to 'mzn_{k}'", SyntaxWarning, ) self._field_renames.append((k, "mzn_" + k)) fields.append(("mzn_" + k, v)) else: fields.append((k, v)) minizinc.logger.debug( f"CLIInstance:analyse -> output fields: " f"{[f[0:2] for f in fields]}" ) methods = {} if interface.get("has_output_item", True): methods["__str__"] = ( lambda myself: myself.__repr__() if myself._output_item == "" else myself._output_item ) if self._checker: methods["check"] = lambda myself: myself._checker self.output_type = make_dataclass( "Solution", fields, bases=(_GeneratedSolution,), namespace=methods, frozen=True, )
def _reset_analysis(self): self._method = None
[docs] async def solutions( self, timeout: Optional[timedelta] = None, nr_solutions: Optional[int] = None, processes: Optional[int] = None, random_seed: Optional[int] = None, all_solutions=False, intermediate_solutions=False, free_search: bool = False, optimisation_level: Optional[int] = None, verbose: bool = False, debug_output: Optional[Path] = None, **kwargs, ): method = self.method # Ensure self.analyse() has been executed # Set standard command line arguments cmd: List[Any] = [ "--output-mode", "json", "--output-time", "--output-objective", "--output-output-item", "--statistics", # Enable statistics # Enable intermediate solutions # (ensure that solvers always output their best solution) "--intermediate-solutions", ] # Process number of solutions to be generated if all_solutions: if nr_solutions is not None: raise ValueError( "The number of solutions cannot be limited when looking " "for all solutions" ) if method != Method.SATISFY: raise NotImplementedError( "Finding all optimal solutions is not yet implemented" ) if "-a" not in self._solver.stdFlags: raise NotImplementedError("Solver does not support the -a flag") cmd.append("--all-solutions") elif nr_solutions is not None: if nr_solutions <= 0: raise ValueError( "The number of solutions can only be set to a positive " "integer number" ) if self.method != Method.SATISFY: raise NotImplementedError( "Finding multiple optimal solutions is not yet implemented" ) if "-n" not in self._solver.stdFlags: raise NotImplementedError("Solver does not support the -n flag") cmd.extend(["--num-solutions", str(nr_solutions)]) # Set number of processes to be used if processes is not None: cmd.extend(["--parallel", str(processes)]) # Set random seed to be used if random_seed is not None: cmd.extend(["--random-seed", str(random_seed)]) # Enable free search if specified if free_search: cmd.append("--free-search") # Set compiler optimisation level if specified if optimisation_level is not None: cmd.extend(["-O", str(optimisation_level)]) # Set time limit for the MiniZinc solving if timeout is not None: cmd.extend(["--time-limit", str(int(timeout.total_seconds() * 1000))]) if verbose: cmd.append("--verbose") for flag, value in kwargs.items(): if not flag.startswith("-"): flag = "--" + flag if type(value) is bool: if value: cmd.append(flag) else: cmd.extend([flag, value]) # Add files as last arguments with self.files() as files, self._solver.configuration() as solver: assert self.output_type is not None cmd.extend(files) status = Status.UNKNOWN last_status = Status.UNKNOWN code = 0 statistics: Dict[str, Any] = {} try: # Run the MiniZinc process proc = await self._driver.create_process(cmd, solver=solver) assert isinstance(proc.stderr, asyncio.StreamReader) assert isinstance(proc.stdout, asyncio.StreamReader) # Python 3.7+: replace with asyncio.create_task read_stderr = asyncio.ensure_future(_read_all(proc.stderr)) if self._driver.parsed_version >= (2, 6, 0): async for obj in decode_async_json_stream( proc.stdout, cls=MZNJSONDecoder, enum_map=self._enum_map ): solution, new_status, statistics = self._parse_stream_obj( obj, statistics ) if new_status is not None: status = new_status elif solution is not None: if status == Status.UNKNOWN: status = Status.SATISFIED yield Result(status, solution, statistics) last_status = status solution = None statistics = {} else: async for raw_sol in _seperate_solutions(proc.stdout): status = Status.SATISFIED solution, statistics = parse_solution( raw_sol, self.output_type, self._enum_map, self._field_renames, ) yield Result(Status.SATISFIED, solution, statistics) code = await proc.wait() except asyncio.IncompleteReadError as err: # End of Stream has been reached # Read remaining text in buffer code = await proc.wait() remainder = err.partial # Parse and output the remaining statistics and status messages if self._driver.parsed_version >= (2, 6, 0): for obj in decode_json_stream( remainder, cls=MZNJSONDecoder, enum_map=self._enum_map ): solution, new_status, statistics = self._parse_stream_obj( obj, statistics ) if new_status is not None: status = new_status elif solution is not None: if status == Status.UNKNOWN: status = Status.SATISFIED yield Result(status, solution, statistics) solution = None statistics = {} else: for res in filter(None, remainder.split(SEPARATOR)): new_status = Status.from_output(res, method) if new_status is not None: status = new_status solution, statistics = parse_solution( res, self.output_type, self._enum_map, self._field_renames, ) yield Result(status, solution, statistics) except (asyncio.CancelledError, MiniZincError, Exception): # Process was cancelled by the user, a MiniZincError occurred, or # an unexpected Python exception occurred # First, terminate the process proc.terminate() _ = await proc.wait() # Then, reraise the error that occurred raise if self._driver.parsed_version >= (2, 6, 0) and ( status != last_status or statistics != {} ): yield Result(status, None, statistics) # Raise error if required stderr = await read_stderr if code != 0 or status == Status.ERROR: raise parse_error(stderr) if debug_output is not None: debug_output.write_bytes(stderr)
[docs] @contextlib.contextmanager def flat( self, timeout: Optional[timedelta] = None, optimisation_level: Optional[int] = None, **kwargs, ): """Produce a FlatZinc file for the instance. Args: timeout (Optional[timedelta]): Set the time limit for the process of flattening the instance. TODO: An exception is raised if the timeout is reached. optimisation_level (Optional[int]): Set the MiniZinc compiler optimisation level. - 0: Disable optimisation - 1: Single pass optimisation (default) - 2: Flatten twice to improve flattening decisions - 3: Perform root-node-propagation - 4: Probe bounds of all variables at the root node - 5: Probe values of all variables at the root node **kwargs: Other flags to be passed to the compiler. ``--`` can be omitted in the name of the flag. If the type of the flag is Boolean, then its value signifies its occurrence. Yields: Tuple containing the files of the FlatZinc model, the output model and a dictionary the statistics of flattening """ cmd: List[Any] = ["--compile", "--statistics"] fzn = tempfile.NamedTemporaryFile(prefix="fzn_", suffix=".fzn", delete=False) cmd.extend(["--fzn", fzn.name]) fzn.close() ozn = tempfile.NamedTemporaryFile(prefix="ozn_", suffix=".fzn", delete=False) cmd.extend(["--ozn", ozn.name]) ozn.close() if timeout is not None: cmd.extend(["--time-limit", str(int(timeout.total_seconds() * 1000))]) # Set compiler optimisation level if specified if optimisation_level is not None: cmd.extend(["-O", str(optimisation_level)]) for flag, value in kwargs.items(): if not flag.startswith("-"): flag = "--" + flag if type(value) is bool: if value: cmd.append(flag) else: cmd.extend([flag, value]) # Add files as last arguments with self.files() as files: cmd.extend(files) # Run the MiniZinc process output = self._driver.run(cmd, solver=self._solver) statistics: Dict[str, Any] = {} matches = re.findall(rb"%%%mzn-stat:? (\w*)=([^\r\n]*)", output.stdout) for m in matches: set_stat(statistics, m[0].decode(), m[1].decode()) try: yield fzn, ozn, statistics finally: os.remove(fzn.name) os.remove(ozn.name)
[docs] def add_file(self, file: ParPath, parse_data: bool = True) -> None: self._reset_analysis() return super().add_file(file, parse_data)
[docs] def add_string(self, code: str) -> None: self._reset_analysis() return super().add_string(code)
def _parse_stream_obj(self, obj, statistics): solution = None status = None if obj["type"] == "solution": tmp = obj["output"]["json"] if "_objective" in tmp: tmp["objective"] = tmp.pop("_objective") if "_output" in tmp: tmp["_output_item"] = tmp.pop("_output") for before, after in self._field_renames: tmp[after] = tmp.pop(before) if "_checker" in statistics: tmp["_checker"] = statistics.pop("_checker") solution = self.output_type(**tmp) statistics["time"] = obj["time"] elif obj["type"] == "time": statistics["time"] = obj["time"] elif obj["type"] == "statistics": statistics.update(obj["statistics"]) elif obj["type"] == "status": status = Status.from_str(obj["status"]) elif obj["type"] == "checker": if "raw" in obj["output"]: statistics["_checker"] = obj["output"]["raw"] else: # TODO: can we ensure this is made JSON? statistics["_checker"] = obj["output"]["dzn"] return solution, status, statistics
async def _seperate_solutions(stream: asyncio.StreamReader): solution: bytes = b"" while not stream.at_eof(): try: solution += await stream.readuntil(SEPARATOR) yield solution solution = b"" except asyncio.LimitOverrunError as err: solution += await stream.readexactly(err.consumed) async def _read_all(stream: asyncio.StreamReader): output: bytes = b"" while not stream.at_eof(): try: output += await stream.read() return output except asyncio.LimitOverrunError as err: output += await stream.readexactly(err.consumed) return output