from datetime import datetime
from typing import NamedTuple

from autotui.shortcuts import load_prompt_and_writeback

class Water(NamedTuple):
    at: datetime
    glass_count: float

if __name__ == "__main__":
    load_prompt_and_writeback(Water, "~/.local/share/water.json")

from autotui.shortcuts import load_from

class Water(NamedTuple):
    #... (same as above)

if __name__ == "__main__":
    print(load_from(Water, "~/.local/share/water.json"))

#[Water(at=datetime.datetime(2020, 8, 31, 6, 53, 6, tzinfo=datetime.timezone.utc), glass_count=2.0),
# Water(at=datetime.datetime(2020, 8, 31, 6, 53, 20, tzinfo=datetime.timezone.utc), glass_count=1.0)]

import autotui

with autotui.options("LIVE_DATETIME"):
    autotui.prompt_namedtuple(...)

# water-now script -- set any datetime values to now
from datetime import datetime
from typing import NamedTuple

from autotui import prompt_namedtuple
from autotui.shortcuts import load_prompt_and_writeback

class Water(NamedTuple):
    at: datetime
    glass_count: float

load_prompt_and_writeback(Water, "./water.json", type_use_values={datetime: datetime.now()})
# or specify it with a function (don't call datetime.now, just pass the function)
# so its called when its needed
val = prompt_namedtuple(Water, attr_use_values={"at": datetime.now})

from datetime import datetime
from typing import NamedTuple, List, Optional

from autotui.shortcuts import load_prompt_and_writeback

import click


def edit_in_vim() -> str:
    m = click.edit(text=None, editor="vim")
    return m if m is None else m.strip()


class JournalEntry(NamedTuple):
    creation_date: datetime
    tags: Optional[List[str]]  # one or more tags to tag this journal entry with
    content: str


if __name__ == "__main__":
    load_prompt_and_writeback(
        JournalEntry,
        "~/Documents/journal.json",
        attr_use_values={"content": edit_in_vim},
    )

class JournalEntry(NamedTuple):
    ...

    @staticmethod
    def attr_use_values() -> Dict:
        return {"content": edit_in_vim}


# pulls attr_use_values from the function
prompt_namedtuple(JournalEntry, "~/Documents/journal.json")

# using the water example above
if __name__ == "__main__":
    load_prompt_and_writeback(Water, "~/.local/share/water.yaml")

from autotui import pick_namedtuple
from autotui.shortcuts import load_from

picked = pick_namedtuple(load_from(Water, "~/.local/share/water.json"))
print(picked)

from autotui.edit import edit_namedtuple

water = edit_namedtuple(water, print_namedtuple=True)
# can also 'loop', to edit multiple fields
water = edit_namedtuple(water, print_namedtuple=True, loop=True)

# see examples/timedelta_serializer.py for imports

# handle validating the user input interactively
# can throw a ValueError
def _timedelta(user_input: str) -> timedelta:
    if len(user_input.strip()) == 0:
        raise ValueError("Not enough input!")
    minutes, _, seconds = user_input.partition(":")
    # could throw ValueError
    return timedelta(minutes=float(minutes), seconds=float(seconds))


# serializer for timedelta, converts to JSON-compatible integer
def to_seconds(t: timedelta) -> int:
    return int(t.total_seconds())


# deserializer from integer to timedelta
def from_seconds(seconds: int) -> timedelta:
    return timedelta(seconds=seconds)


# The data we want to persist to the file
class Action(NamedTuple):
    name: str
    duration: timedelta


# AutoHandler describes what function to use to validate
# user input, and which errors to wrap while validating
timedelta_handler = AutoHandler(
    func=_timedelta,  # accepts the string the user is typing as input
    catch_errors=[ValueError],
)

# Note: validators are of type
# Dict[Type, AutoHandler]
# serializer/deserializers are
# Dict[Type, Callable]
# the Callable accepts one argument,
# which is either the python value being serialized
# or the JSON value being deserialized

# use the validator to prompt the user for the NamedTuple data
# name: str automatically uses a generic string prompt
# duration: timedelta gets handled by the type_validator
a = prompt_namedtuple(
    Action,
    type_validators={
        timedelta: timedelta_handler,
    },
)


# Note: this specifies timedelta as the type,
# not int. It uses what the NamedTuple
# specifies as the type for that field, not
# the type of the value that's loaded from JSON

# dump to JSON
a_str: str = namedtuple_sequence_dumps(
    [a],
    type_serializers={
        timedelta: to_seconds,
    },
    indent=None,
)

# load from JSON
a_load = namedtuple_sequence_loads(
    a_str,
    to=Action,
    type_deserializers={
        timedelta: from_seconds,
    },
)[0]

# can also specify with attributes instead of types
a_load2 = namedtuple_sequence_loads(
    a_str,
    to=Action,
    attr_deserializers={
        "duration": from_seconds,
    },
)[0]

print(a)
print(a_str)
print(a_load)
print(a_load2)