



from __future__ import annotations

import requests

def    lowerCamelCase_(lowerCamelCase_    ) ->       dict:

						'''simple docstring'''





						UpperCAmelCase         =     F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
						return requests.get(lowerCamelCase_    ).json()

def    lowerCamelCase_(lowerCamelCase_ = 10    ) ->       list[dict]:

						'''simple docstring'''





						UpperCAmelCase         =     "https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"
						UpperCAmelCase         =     requests.get(lowerCamelCase_    ).json()[:max_stories]
						return [get_hackernews_story(lowerCamelCase_    ) for story_id in story_ids]

def    lowerCamelCase_(lowerCamelCase_ = 10    ) ->       str:

						'''simple docstring'''





						UpperCAmelCase         =     hackernews_top_stories(lowerCamelCase_    )
						return "\n".join("* [{title}]({url})".format(**lowerCamelCase_    ) for story in stories    )


if __name__ == "__main__":
		print(hackernews_top_stories_as_markdown())








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowerCamelCase     :							Any  							=				{
    "configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase     :							Optional[int]  							=				[
		    "MEGA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "MegaForCausalLM",
		    "MegaForMaskedLM",
		    "MegaForMultipleChoice",
		    "MegaForQuestionAnswering",
		    "MegaForSequenceClassification",
		    "MegaForTokenClassification",
		    "MegaModel",
		    "MegaPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mega import (
				    MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MegaForCausalLM,
				    MegaForMaskedLM,
				    MegaForMultipleChoice,
				    MegaForQuestionAnswering,
				    MegaForSequenceClassification,
				    MegaForTokenClassification,
				    MegaModel,
				    MegaPreTrainedModel,
				)

else:
		import sys

		__lowerCamelCase     :							int  							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



