import copy
import datetime
import logging
import math
import operator
import traceback
from collections import namedtuple
from typing import Any, Dict, Optional, Tuple

from pyparsing import (
    CaselessKeyword,
    Combine,
    Forward,
    Group,
    Literal,
    ParseException,
    Regex,
    Suppress,
    Word,
    alphanums,
    alphas,
    delimitedList,
    dictOf,
)

from great_expectations.core.urn import ge_urn
from great_expectations.core.util import convert_to_json_serializable
from great_expectations.exceptions import EvaluationParameterError

logger = logging.getLogger(__name__)
_epsilon = 1e-12


class EvaluationParameterParser:
    """
    This Evaluation Parameter Parser uses pyparsing to provide a basic expression language capable of evaluating
    parameters using values available only at run time.

    expop   :: '^'
    multop  :: '*' | '/'
    addop   :: '+' | '-'
    integer :: ['+' | '-'] '0'..'9'+
    atom    :: PI | E | real | fn '(' expr ')' | '(' expr ')'
    factor  :: atom [ expop factor ]*
    term    :: factor [ multop factor ]*
    expr    :: term [ addop term ]*

    The parser is modified from: https://github.com/pyparsing/pyparsing/blob/master/examples/fourFn.py
    """

    # map operator symbols to corresponding arithmetic operations
    opn = {
        "+": operator.add,
        "-": operator.sub,
        "*": operator.mul,
        "/": operator.truediv,
        "^": operator.pow,
    }

    fn = {
        "sin": math.sin,
        "cos": math.cos,
        "tan": math.tan,
        "exp": math.exp,
        "abs": abs,
        "trunc": lambda a: int(a),
        "round": round,
        "sgn": lambda a: -1 if a < -_epsilon else 1 if a > _epsilon else 0,
        "now": datetime.datetime.now,
        "datetime": datetime.datetime,
        "timedelta": datetime.timedelta,
    }

    def __init__(self):
        self.exprStack = []
        self._parser = None

    def push_first(self, toks):
        self.exprStack.append(toks[0])

    def push_unary_minus(self, toks):
        


    def clear_stack(self):
        del self.exprStack[:]

    def get_parser(self):
        self.clear_stack()
        if not self._parser:
            # use CaselessKeyword for e and pi, to avoid accidentally matching
            # functions that start with 'e' or 'pi' (such as 'exp'); Keyword
            # and CaselessKeyword only match whole words
            e = CaselessKeyword("E")
            pi = CaselessKeyword("PI")
            # fnumber = Combine(Word("+-"+nums, nums) +
            #                    Optional("." + Optional(Word(nums))) +
            #                    Optional(e + Word("+-"+nums, nums)))
            # or use provided pyparsing_common.number, but convert back to str:
            # fnumber = ppc.number().addParseAction(lambda t: str(t[0]))
            fnumber = Regex(r"[+-]?(?:\d+|\.\d+)(?:\.\d+)?(?:[eE][+-]?\d+)?")
            ge_urn = Combine(
                Literal("urn:great_expectations:")
                + Word(alphas, f"{alphanums}_$:?=%.&")
            )
            variable = Word(alphas, f"{alphanums}_$")
            ident = ge_urn | variable

            plus, minus, mult, div = map(Literal, "+-*/")
            lpar, rpar = map(Suppress, "()")
            addop = plus | minus
            multop = mult | div
            expop = Literal("^")

            expr = Forward()
            expr_list = delimitedList(Group(expr))

            # We will allow functions either to accept *only* keyword
            # expressions or *only* non-keyword expressions
            # define function keyword arguments
            key = Word(f"{alphas}_") + Suppress("=")
            # value = (fnumber | Word(alphanums))
            value = expr
            keyval = dictOf(key.setParseAction(self.push_first), value)
            kwarglist = delimitedList(keyval)

            # add parse action that replaces the function identifier with a (name, number of args, has_fn_kwargs) tuple
            # 20211009 - JPC - Note that it's important that we consider kwarglist
            # first as part of disabling backtracking for the function's arguments
            fn_call = (ident + lpar + rpar).setParseAction(
                lambda t: t.insert(0, (t.pop(0), 0, False))
            ) | (
                (ident + lpar - Group(expr_list) + rpar).setParseAction(
                    lambda t: t.insert(0, (t.pop(0), len(t[0]), False))
                )
                ^ (ident + lpar - Group(kwarglist) + rpar).setParseAction(
                    lambda t: t.insert(0, (t.pop(0), len(t[0]), True))
                )
            )
            atom = (
                addop[...]
                + (
                    (fn_call | pi | e | fnumber | ident).setParseAction(self.push_first)
                    | Group(lpar + expr + rpar)
                )
            ).setParseAction(self.push_unary_minus)

            # by defining exponentiation as "atom [ ^ factor ]..." instead of "atom [ ^ atom ]...", we get right-to-left
            # exponents, instead of left-to-right that is, 2^3^2 = 2^(3^2), not (2^3)^2.
            factor = Forward()
            factor <<= atom + (expop + factor).setParseAction(self.push_first)[...]
            term = factor + (multop + factor).setParseAction(self.push_first)[...]
            expr <<= term + (addop + term).setParseAction(self.push_first)[...]
            self._parser = expr
        return self._parser

    def evaluate_stack(self, s):
        op, num_args, has_fn_kwargs = s.pop(), 0, False
        if isinstance(op, tuple):
            op, num_args, has_fn_kwargs = op
        if op == "unary -":
            return -self.evaluate_stack(s)
        if op in "+-*/^":
            # note: operands are pushed onto the stack in reverse order
            op2 = self.evaluate_stack(s)
            op1 = self.evaluate_stack(s)
            return self.opn[op](op1, op2)
        elif op == "PI":
            return math.pi  # 3.1415926535
        elif op == "E":
            return math.e  # 2.718281828
        elif op in self.fn:
            # note: args are pushed onto the stack in reverse order
            if has_fn_kwargs:
                kwargs = dict()
                for _ in range(num_args):
                    v = self.evaluate_stack(s)
                    k = s.pop()
                    kwargs.update({k: v})
                return self.fn[op](**kwargs)
            else:
                args = reversed([self.evaluate_stack(s) for _ in range(num_args)])
                return self.fn[op](*args)
        else:
            # try to evaluate as int first, then as float if int fails
            # NOTE: JPC - 20200403 - Originally I considered returning the raw op here if parsing as float also
            # fails, but I decided against it to instead require that the *entire* expression evaluates
            # numerically UNLESS there is *exactly one* expression to substitute (see cases where len(L) == 1 in the
            # parse_evaluation_parameter method.
            try:
                return int(op)
            except ValueError:
                return float(op)


def build_evaluation_parameters(
    expectation_args: dict,
    evaluation_parameters: Optional[dict] = None,
    interactive_evaluation: bool = True,
    data_context=None,
) -> Tuple[dict, dict]:
    """Build a dictionary of parameters to evaluate, using the provided evaluation_parameters,
    AND mutate expectation_args by removing any parameter values passed in as temporary values during
    exploratory work.
    """
    evaluation_args = copy.deepcopy(expectation_args)
    substituted_parameters = {}

    # Iterate over arguments, and replace $PARAMETER-defined args with their
    # specified parameters.
    for key, value in evaluation_args.items():
        if isinstance(value, dict) and "$PARAMETER" in value:
            # We do not even need to search for a value if we are not going to do interactive evaluation
            if not interactive_evaluation:
                continue

            # First, check to see whether an argument was supplied at runtime
            # If it was, use that one, but remove it from the stored config
            param_key = f"$PARAMETER.{value['$PARAMETER']}"
            if param_key in value:
                evaluation_args[key] = evaluation_args[key][param_key]
                del expectation_args[key][param_key]

            # If not, try to parse the evaluation parameter and substitute, which will raise
            # an exception if we do not have a value
            else:
                raw_value = value["$PARAMETER"]
                parameter_value = parse_evaluation_parameter(
                    raw_value,
                    evaluation_parameters=evaluation_parameters,
                    data_context=data_context,
                )
                evaluation_args[key] = parameter_value
                # Once we've substituted, we also track that we did so
                substituted_parameters[key] = parameter_value

    return evaluation_args, substituted_parameters


expr = EvaluationParameterParser()


def find_evaluation_parameter_dependencies(parameter_expression):
    """Parse a parameter expression to identify dependencies including GE URNs.

    Args:
        parameter_expression: the parameter to parse

    Returns:
        a dictionary including:
          - "urns": set of strings that are valid GE URN objects
          - "other": set of non-GE URN strings that are required to evaluate the parameter expression

    """
    expr = EvaluationParameterParser()

    dependencies = {"urns": set(), "other": set()}
    # Calling get_parser clears the stack
    parser = expr.get_parser()
    try:
        _ = parser.parseString(parameter_expression, parseAll=True)
    except ParseException as err:
        raise EvaluationParameterError(
            f"Unable to parse evaluation parameter: {str(err)} at line {err.line}, column {err.column}"
        )
    except AttributeError as err:
        raise EvaluationParameterError(
            f"Unable to parse evaluation parameter: {str(err)}"
        )

    for word in expr.exprStack:
        if isinstance(word, (int, float)):
            continue

        if not isinstance(word, str):
            # If we have a function that itself is a tuple (e.g. (trunc, 1))
            continue

        if word in expr.opn or word in expr.fn or word == "unary -":
            # operations and functions
            continue

        # if this is parseable as a number, then we do not include it
        try:
            _ = float(word)
            continue
        except ValueError:
            pass

        try:
            _ = ge_urn.parseString(word)
            dependencies["urns"].add(word)
            continue
        except ParseException:
            # This particular evaluation_parameter or operator is not a valid URN
            pass

        # If we got this far, it's a legitimate "other" evaluation parameter
        dependencies["other"].add(word)

    return dependencies


def parse_evaluation_parameter(
    parameter_expression: str,
    evaluation_parameters: Optional[Dict[str, Any]] = None,
    data_context: Optional[Any] = None,  # Cannot type 'DataContext' due to import cycle
) -> Any:
    """Use the provided evaluation_parameters dict to parse a given parameter expression.

    Args:
        parameter_expression (str): A string, potentially containing basic arithmetic operations and functions,
            and variables to be substituted
        evaluation_parameters (dict): A dictionary of name-value pairs consisting of values to substitute
        data_context (DataContext): A data context to use to obtain metrics, if necessary

    The parser will allow arithmetic operations +, -, /, *, as well as basic functions, including trunc() and round() to
    obtain integer values when needed for certain expectations (e.g. expect_column_value_length_to_be_between).

    Valid variables must begin with an alphabetic character and may contain alphanumeric characters plus '_' and '$',
    EXCEPT if they begin with the string "urn:great_expectations" in which case they may also include additional
    characters to support inclusion of GE URLs (see :ref:`evaluation_parameters` for more information).
    """
    if evaluation_parameters is None:
        evaluation_parameters = {}

    # Calling get_parser clears the stack
    parser = expr.get_parser()
    try:
        L = parser.parseString(parameter_expression, parseAll=True)
    except ParseException as err:
        L = ["Parse Failure", parameter_expression, (str(err), err.line, err.column)]

    # Represents a valid parser result of a single function that has no arguments
    if len(L) == 1 and isinstance(L[0], tuple) and L[0][2] is False:
        # Necessary to catch `now()` (which only needs to be evaluated with `expr.exprStack`)
        # NOTE: 20211122 - Chetan - Any future built-ins that are zero arity functions will match this behavior
        pass

    elif len(L) == 1 and L[0] not in evaluation_parameters:
        # In this special case there were no operations to find, so only one value, but we don't have something to
        # substitute for that value
        try:
            res = ge_urn.parseString(L[0])
            if res["urn_type"] == "stores":
                store = data_context.stores.get(res["store_name"])
                return store.get_query_result(
                    res["metric_name"], res.get("metric_kwargs", {})
                )
            else:
                logger.error(
                    "Unrecognized urn_type in ge_urn: must be 'stores' to use a metric store."
                )
                raise EvaluationParameterError(
                    f"No value found for $PARAMETER {str(L[0])}"
                )
        except ParseException as e:
            logger.debug(
                f"Parse exception while parsing evaluation parameter: {str(e)}"
            )
            raise EvaluationParameterError(f"No value found for $PARAMETER {str(L[0])}")
        except AttributeError:
            logger.warning("Unable to get store for store-type valuation parameter.")
            raise EvaluationParameterError(f"No value found for $PARAMETER {str(L[0])}")

    elif len(L) == 1:
        # In this case, we *do* have a substitution for a single type. We treat this specially because in this
        # case, we allow complex type substitutions (i.e. do not coerce to string as part of parsing)
        # NOTE: 20201023 - JPC - to support MetricDefinition as an evaluation parameter type, we need to handle that
        # case here; is the evaluation parameter provided here in fact a metric definition?
        return evaluation_parameters[L[0]]

    elif len(L) == 0 or L[0] != "Parse Failure":
        for i, ob in enumerate(expr.exprStack):
            if isinstance(ob, str) and ob in evaluation_parameters:
                expr.exprStack[i] = str(evaluation_parameters[ob])

    else:
        err_str, err_line, err_col = L[-1]
        raise EvaluationParameterError(
            f"Parse Failure: {err_str}\nStatement: {err_line}\nColumn: {err_col}"
        )

    try:
        result = expr.evaluate_stack(expr.exprStack)
        result = convert_to_json_serializable(result)
    except Exception as e:
        exception_traceback = traceback.format_exc()
        exception_message = (
            f'{type(e).__name__}: "{str(e)}".  Traceback: "{exception_traceback}".'
        )
        logger.debug(exception_message, e, exc_info=True)
        raise EvaluationParameterError(
            f"Error while evaluating evaluation parameter expression: {str(e)}"
        )

    return result


def _deduplicate_evaluation_parameter_dependencies(dependencies: dict) -> dict:
    deduplicated = {}
    for suite_name, required_metrics in dependencies.items():
        deduplicated[suite_name] = []
        metrics = set()
        metric_kwargs = {}
        for metric in required_metrics:
            if isinstance(metric, str):
                metrics.add(metric)
            elif isinstance(metric, dict):
                # There is a single metric_kwargs_id object in this construction
                for kwargs_id, metric_list in metric["metric_kwargs_id"].items():
                    if kwargs_id not in metric_kwargs:
                        metric_kwargs[kwargs_id] = set()
                    for metric_name in metric_list:
                        metric_kwargs[kwargs_id].add(metric_name)
        deduplicated[suite_name] = list(metrics)
        if len(metric_kwargs) > 0:
            deduplicated[suite_name] = deduplicated[suite_name] + [
                {
                    "metric_kwargs_id": {
                        metric_kwargs: list(metrics_set)
                        for (metric_kwargs, metrics_set) in metric_kwargs.items()
                    }
                }
            ]

    return deduplicated


EvaluationParameterIdentifier = namedtuple(
    "EvaluationParameterIdentifier",
    ["expectation_suite_name", "metric_name", "metric_kwargs_id"],
)

for t in toks:
            if t == "-":
                self.exprStack.append("unary -")
            else:
                break