'''
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 returns an
error if val is not the correct type.  The var_name parameter is used
to format error messages.  Validators return None 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']) is None

To extend this concept, it's simply a matter of writing your own validator
for any particular type of object.
'''
from django.utils.translation import ugettext as _
from django.core.exceptions import ValidationError
from django.core.validators import validate_email, URLValidator
from typing import Callable, Iterable, Optional, Tuple, TypeVar, Text

from zerver.lib.request import JsonableError

Validator = Callable[[str, object], Optional[str]]

def check_string(var_name: str, val: object) -> Optional[str]:
    if not isinstance(val, str):
        return _('%s is not a string') % (var_name,)
    return None

def check_short_string(var_name: str, val: object) -> Optional[str]:
    if not isinstance(val, str):
        return _('%s is not a string') % (var_name,)
    max_length = 200
    if len(val) >= max_length:
        return _("{var_name} is longer than {max_length}.".format(
            var_name=var_name, max_length=max_length))
    return None

def check_int(var_name: str, val: object) -> Optional[str]:
    if not isinstance(val, int):
        return _('%s is not an integer') % (var_name,)
    return None

def check_float(var_name: str, val: object) -> Optional[str]:
    if not isinstance(val, float):
        return _('%s is not a float') % (var_name,)
    return None

def check_bool(var_name: str, val: object) -> Optional[str]:
    if not isinstance(val, bool):
        return _('%s is not a boolean') % (var_name,)
    return None

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

def check_list(sub_validator: Optional[Validator], length: Optional[int]=None) -> Validator:
    def f(var_name: str, val: object) -> Optional[str]:
        if not isinstance(val, list):
            return _('%s is not a list') % (var_name,)

        if length is not None and length != len(val):
            return (_('%(container)s should have exactly %(length)s items') %
                    {'container': var_name, 'length': length})

        if sub_validator:
            for i, item in enumerate(val):
                vname = '%s[%d]' % (var_name, i)
                error = sub_validator(vname, item)
                if error:
                    return error

        return None
    return f

def check_dict(required_keys: Iterable[Tuple[str, Validator]],
               _allow_only_listed_keys: bool=False) -> Validator:
    def f(var_name: str, val: object) -> Optional[str]:
        if not isinstance(val, dict):
            return _('%s is not a dict') % (var_name,)

        for k, sub_validator in required_keys:
            if k not in val:
                return (_('%(key_name)s key is missing from %(var_name)s') %
                        {'key_name': k, 'var_name': var_name})
            vname = '%s["%s"]' % (var_name, k)
            error = sub_validator(vname, val[k])
            if error:
                return error

        if _allow_only_listed_keys:
            delta_keys = set(val.keys()) - set(x[0] for x in required_keys)
            if len(delta_keys) != 0:
                return _("Unexpected arguments: %s" % (", ".join(list(delta_keys))))

        return None

    return f

def check_dict_only(required_keys: Iterable[Tuple[str, Validator]]) -> Validator:
    return check_dict(required_keys, _allow_only_listed_keys=True)

def check_variable_type(allowed_type_funcs: Iterable[Validator]) -> Validator:
    """
    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) -> Optional[str]:
        for func in allowed_type_funcs:
            if not func(var_name, val):
                return None
        return _('%s is not an allowed_type') % (var_name,)
    return enumerated_type_check

def equals(expected_val: object) -> Validator:
    def f(var_name: str, val: object) -> Optional[str]:
        if val != expected_val:
            return (_('%(variable)s != %(expected_value)s (%(value)s is wrong)') %
                    {'variable': var_name,
                     'expected_value': expected_val,
                     'value': val})
        return None
    return f

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

def check_url(var_name: str, val: Text) -> None:
    validate = URLValidator()
    try:
        validate(val)
    except ValidationError as err:
        raise JsonableError(str(err.message))