"""
This module sets up a scheme for validating that arbitrary Python
objects are correctly typed.  It is totally decoupled from Django,
composable, easily wrapped, and easily extended.

A validator takes two parameters--var_name and val--and raises an
error if val is not the correct type.  The var_name parameter is used
to format error messages.  Validators return the validated value when
there are no errors.

Example primitive validators are check_string, check_int, and check_bool.

Compound validators are created by check_list and check_dict.  Note that
those functions aren't directly called for validation; instead, those
functions are called to return other functions that adhere to the validator
contract.  This is similar to how Python decorators are often parameterized.

The contract for check_list and check_dict is that they get passed in other
validators to apply to their items.  This allows you to build up validators
for arbitrarily complex validators.  See ValidatorTestCase for example usage.

A simple example of composition is this:

   check_list(check_string)('my_list', ['a', 'b', 'c'])

To extend this concept, it's simply a matter of writing your own validator
for any particular type of object.

"""
import re
from datetime import datetime
from typing import (
    Any,
    Callable,
    Collection,
    Dict,
    List,
    Optional,
    Set,
    Tuple,
    Union,
    cast,
    overload,
)

import orjson
from django.core.exceptions import ValidationError
from django.core.validators import URLValidator, validate_email
from django.utils.translation import gettext as _

from zerver.lib.request import JsonableError, ResultT
from zerver.lib.types import ProfileFieldData, Validator


def check_string(var_name: str, val: object) -> str:
    if not isinstance(val, str):
        raise ValidationError(_("{var_name} is not a string").format(var_name=var_name))
    return val


def check_required_string(var_name: str, val: object) -> str:
    s = check_string(var_name, val)
    if not s.strip():
        raise ValidationError(_("{item} cannot be blank.").format(item=var_name))
    return s


def check_string_in(possible_values: Union[Set[str], List[str]]) -> Validator[str]:
    def validator(var_name: str, val: object) -> str:
        s = check_string(var_name, val)
        if s not in possible_values:
            raise ValidationError(_("Invalid {var_name}").format(var_name=var_name))
        return s

    return validator


def check_short_string(var_name: str, val: object) -> str:
    return check_capped_string(50)(var_name, val)


def check_capped_string(max_length: int) -> Validator[str]:
    def validator(var_name: str, val: object) -> str:
        s = check_string(var_name, val)
        if len(s) > max_length:
            raise ValidationError(
                _("{var_name} is too long (limit: {max_length} characters)").format(
                    var_name=var_name,
                    max_length=max_length,
                )
            )
        return s

    return validator


def check_string_fixed_length(length: int) -> Validator[str]:
    def validator(var_name: str, val: object) -> str:
        s = check_string(var_name, val)
        if len(s) != length:
            raise ValidationError(
                _("{var_name} has incorrect length {length}; should be {target_length}").format(
                    var_name=var_name,
                    target_length=length,
                    length=len(s),
                )
            )
        return s

    return validator


def check_long_string(var_name: str, val: object) -> str:
    return check_capped_string(500)(var_name, val)


def check_date(var_name: str, val: object) -> str:
    if not isinstance(val, str):
        raise ValidationError(_("{var_name} is not a string").format(var_name=var_name))
    try:
        if datetime.strptime(val, "%Y-%m-%d").strftime("%Y-%m-%d") != val:
            raise ValidationError(_("{var_name} is not a date").format(var_name=var_name))
    except ValueError:
        raise ValidationError(_("{var_name} is not a date").format(var_name=var_name))
    return val


def check_int(var_name: str, val: object) -> int:
    if not isinstance(val, int):
        raise ValidationError(_("{var_name} is not an integer").format(var_name=var_name))
    return val


def check_int_in(possible_values: List[int]) -> Validator[int]:
    def validator(var_name: str, val: object) -> int:
        n = check_int(var_name, val)
        if n not in possible_values:
            raise ValidationError(_("Invalid {var_name}").format(var_name=var_name))
        return n

    return validator


def check_float(var_name: str, val: object) -> float:
    if not isinstance(val, float):
        raise ValidationError(_("{var_name} is not a float").format(var_name=var_name))
    return val


def check_bool(var_name: str, val: object) -> bool:
    if not isinstance(val, bool):
        raise ValidationError(_("{var_name} is not a boolean").format(var_name=var_name))
    return val


def check_color(var_name: str, val: object) -> str:
    s = check_string(var_name, val)
    valid_color_pattern = re.compile(r"^#([a-fA-F0-9]{3,6})$")
    matched_results = valid_color_pattern.match(s)
    if not matched_results:
        raise ValidationError(
            _("{var_name} is not a valid hex color code").format(var_name=var_name)
        )
    return s


def check_none_or(sub_validator: Validator[ResultT]) -> Validator[Optional[ResultT]]:
    def f(var_name: str, val: object) -> Optional[ResultT]:
        if val is None:
            return val
        else:
            return sub_validator(var_name, val)

    return f


def check_list(
    sub_validator: Validator[ResultT], length: Optional[int] = None
) -> Validator[List[ResultT]]:
    def f(var_name: str, val: object) -> List[ResultT]:
        if not isinstance(val, list):
            raise ValidationError(_("{var_name} is not a list").format(var_name=var_name))

        if length is not None and length != len(val):
            raise ValidationError(
                _("{container} should have exactly {length} items").format(
                    container=var_name,
                    length=length,
                )
            )

        for i, item in enumerate(val):
            vname = f"{var_name}[{i}]"
            valid_item = sub_validator(vname, item)
            assert item is valid_item  # To justify the unchecked cast below

        return cast(List[ResultT], val)

    return f


def check_tuple(sub_validators: List[Validator[ResultT]]) -> Validator[Tuple[Any, ...]]:
    def f(var_name: str, val: object) -> Tuple[Any, ...]:
        if not isinstance(val, tuple):
            raise ValidationError(_("{var_name} is not a tuple").format(var_name=var_name))

        desired_len = len(sub_validators)
        if desired_len != len(val):
            raise ValidationError(
                _("{var_name} should have exactly {desired_len} items").format(
                    var_name=var_name,
                    desired_len=desired_len,
                )
            )

        for i, sub_validator in enumerate(sub_validators):
            vname = f"{var_name}[{i}]"
            sub_validator(vname, val[i])

        return val

    return f


# https://zulip.readthedocs.io/en/latest/testing/mypy.html#using-overload-to-accurately-describe-variations
@overload
def check_dict(
    required_keys: Collection[Tuple[str, Validator[object]]] = [],
    optional_keys: Collection[Tuple[str, Validator[object]]] = [],
    *,
    _allow_only_listed_keys: bool = False,
) -> Validator[Dict[str, object]]:
    ...


@overload
def check_dict(
    required_keys: Collection[Tuple[str, Validator[ResultT]]] = [],
    optional_keys: Collection[Tuple[str, Validator[ResultT]]] = [],
    *,
    value_validator: Validator[ResultT],
    _allow_only_listed_keys: bool = False,
) -> Validator[Dict[str, ResultT]]:
    ...


def check_dict(
    required_keys: Collection[Tuple[str, Validator[ResultT]]] = [],
    optional_keys: Collection[Tuple[str, Validator[ResultT]]] = [],
    *,
    value_validator: Optional[Validator[ResultT]] = None,
    _allow_only_listed_keys: bool = False,
) -> Validator[Dict[str, ResultT]]:
    def f(var_name: str, val: object) -> Dict[str, ResultT]:
        if not isinstance(val, dict):
            raise ValidationError(_("{var_name} is not a dict").format(var_name=var_name))

        for k in val:
            check_string(f"{var_name} key", k)

        for k, sub_validator in required_keys:
            if k not in val:
                raise ValidationError(
                    _("{key_name} key is missing from {var_name}").format(
                        key_name=k,
                        var_name=var_name,
                    )
                )
            vname = f'{var_name}["{k}"]'
            sub_validator(vname, val[k])

        for k, sub_validator in optional_keys:
            if k in val:
                vname = f'{var_name}["{k}"]'
                sub_validator(vname, val[k])

        if value_validator:
            for key in val:
                vname = f"{var_name} contains a value that"
                valid_value = value_validator(vname, val[key])
                assert val[key] is valid_value  # To justify the unchecked cast below

        if _allow_only_listed_keys:
            required_keys_set = {x[0] for x in required_keys}
            optional_keys_set = {x[0] for x in optional_keys}
            delta_keys = set(val.keys()) - required_keys_set - optional_keys_set
            if len(delta_keys) != 0:
                raise ValidationError(
                    _("Unexpected arguments: {}").format(", ".join(list(delta_keys)))
                )

        return cast(Dict[str, ResultT], val)

    return f


def check_dict_only(
    required_keys: Collection[Tuple[str, Validator[ResultT]]],
    optional_keys: Collection[Tuple[str, Validator[ResultT]]] = [],
) -> Validator[Dict[str, ResultT]]:
    return cast(
        Validator[Dict[str, ResultT]],
        check_dict(required_keys, optional_keys, _allow_only_listed_keys=True),
    )


def check_union(allowed_type_funcs: Collection[Validator[ResultT]]) -> Validator[ResultT]:
    """
    Use this validator if an argument is of a variable type (e.g. processing
    properties that might be strings or booleans).

    `allowed_type_funcs`: the check_* validator functions for the possible data
    types for this variable.
    """

    def enumerated_type_check(var_name: str, val: object) -> ResultT:
        for func in allowed_type_funcs:
            try:
                return func(var_name, val)
            except ValidationError:
                pass
        raise ValidationError(_("{var_name} is not an allowed_type").format(var_name=var_name))

    return enumerated_type_check


def equals(expected_val: ResultT) -> Validator[ResultT]:
    def f(var_name: str, val: object) -> ResultT:
        if val != expected_val:
            raise ValidationError(
                _("{variable} != {expected_value} ({value} is wrong)").format(
                    variable=var_name,
                    expected_value=expected_val,
                    value=val,
                )
            )
        return cast(ResultT, val)

    return f


def validate_login_email(email: str) -> None:
    try:
        validate_email(email)
    except ValidationError as err:
        raise JsonableError(str(err.message))


def check_url(var_name: str, val: object) -> str:
    # First, ensure val is a string
    s = check_string(var_name, val)
    # Now, validate as URL
    validate = URLValidator()
    try:
        validate(s)
        return s
    except ValidationError:
        raise ValidationError(_("{var_name} is not a URL").format(var_name=var_name))


def check_external_account_url_pattern(var_name: str, val: object) -> str:
    s = check_string(var_name, val)

    if s.count("%(username)s") != 1:
        raise ValidationError(_("Malformed URL pattern."))
    url_val = s.replace("%(username)s", "username")

    check_url(var_name, url_val)
    return s


def validate_select_field_data(field_data: ProfileFieldData) -> Dict[str, Dict[str, str]]:
    """
    This function is used to validate the data sent to the server while
    creating/editing choices of the choice field in Organization settings.
    """
    validator = check_dict_only(
        [
            ("text", check_required_string),
            ("order", check_required_string),
        ]
    )

    for key, value in field_data.items():
        if not key.strip():
            raise ValidationError(_("'{item}' cannot be blank.").format(item="value"))

        valid_value = validator("field_data", value)
        assert value is valid_value  # To justify the unchecked cast below

    return cast(Dict[str, Dict[str, str]], field_data)


def validate_select_field(var_name: str, field_data: str, value: object) -> str:
    """
    This function is used to validate the value selected by the user against a
    choice field. This is not used to validate admin data.
    """
    s = check_string(var_name, value)
    field_data_dict = orjson.loads(field_data)
    if s not in field_data_dict:
        msg = _("'{value}' is not a valid choice for '{field_name}'.")
        raise ValidationError(msg.format(value=value, field_name=var_name))
    return s


def check_widget_content(widget_content: object) -> Dict[str, Any]:
    if not isinstance(widget_content, dict):
        raise ValidationError("widget_content is not a dict")

    if "widget_type" not in widget_content:
        raise ValidationError("widget_type is not in widget_content")

    if "extra_data" not in widget_content:
        raise ValidationError("extra_data is not in widget_content")

    widget_type = widget_content["widget_type"]
    extra_data = widget_content["extra_data"]

    if not isinstance(extra_data, dict):
        raise ValidationError("extra_data is not a dict")

    if widget_type == "zform":

        if "type" not in extra_data:
            raise ValidationError("zform is missing type field")

        if extra_data["type"] == "choices":
            check_choices = check_list(
                check_dict(
                    [
                        ("short_name", check_string),
                        ("long_name", check_string),
                        ("reply", check_string),
                    ]
                ),
            )

            # We re-check "type" here just to avoid it looking
            # like we have extraneous keys.
            checker = check_dict(
                [
                    ("type", equals("choices")),
                    ("heading", check_string),
                    ("choices", check_choices),
                ]
            )

            checker("extra_data", extra_data)

            return widget_content

        raise ValidationError("unknown zform type: " + extra_data["type"])

    raise ValidationError("unknown widget type: " + widget_type)


# Converter functions for use with has_request_variables
def to_non_negative_int(s: str, max_int_size: int = 2 ** 32 - 1) -> int:
    x = int(s)
    if x < 0:
        raise ValueError("argument is negative")
    if x > max_int_size:
        raise ValueError(f"{x} is too large (max {max_int_size})")
    return x


def to_positive_or_allowed_int(allowed_integer: Optional[int] = None) -> Callable[[str], int]:
    def converter(s: str) -> int:
        x = int(s)
        if allowed_integer is not None and x == allowed_integer:
            return x
        if x == 0:
            raise ValueError("argument is 0")
        return to_non_negative_int(s)

    return converter


def check_string_or_int_list(var_name: str, val: object) -> Union[str, List[int]]:
    if isinstance(val, str):
        return val

    if not isinstance(val, list):
        raise ValidationError(
            _("{var_name} is not a string or an integer list").format(var_name=var_name)
        )

    return check_list(check_int)(var_name, val)


def check_string_or_int(var_name: str, val: object) -> Union[str, int]:
    if isinstance(val, (str, int)):
        return val

    raise ValidationError(_("{var_name} is not a string or integer").format(var_name=var_name))