





import os
import shutil
import unittest
from unittest.mock import patch

from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch





class 	lowerCAmelCase__(       unittest.TestCase			):






       '''simple docstring'''


       @patch("sys.argv"			,  ["fakeprogrampath", "env"]							)
       def 			UpperCamelCase_	(					self							)	->   List[Any]:
            # test transformers-cli env
            import transformers.commands.transformers_cli

            with CaptureStd() as cs:
                 transformers.commands.transformers_cli.main()
            self.assertIn("Python version"			,  cs.out							)
            self.assertIn("Platform"			,  cs.out							)
            self.assertIn("Using distributed or parallel set-up in script?"			,  cs.out							)




       @is_pt_tf_cross_test
       @patch(
           "sys.argv"			,  ["fakeprogrampath", "pt-to-tf", "--model-name", "hf-internal-testing/tiny-random-gptj", "--no-pr"]							)
       def 			UpperCamelCase_	(					self							)	->   int:
            import transformers.commands.transformers_cli

            shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj"			,  ignore_errors=__lowerCamelCase							)  # cleans potential past runs
            transformers.commands.transformers_cli.main()

            # The original repo has no TF weights -- if they exist, they were created by the CLI
            self.assertTrue(os.path.exists("/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5"							)							)




       @require_torch
       @patch("sys.argv"			,  ["fakeprogrampath", "download", "hf-internal-testing/tiny-random-gptj", "--cache-dir", "/tmp"]							)
       def 			UpperCamelCase_	(					self							)	->   Any:
            import transformers.commands.transformers_cli

            # # remove any previously downloaded model to start clean
            shutil.rmtree("/tmp/models--hf-internal-testing--tiny-random-gptj"			,  ignore_errors=__lowerCamelCase							)

            # run the command
            transformers.commands.transformers_cli.main()

            # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
            self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/blobs"							)							)
            self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/refs"							)							)
            self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots"							)							)







       @require_torch
       @patch(
           "sys.argv"			,  [
               "fakeprogrampath",
               "download",
               "hf-internal-testing/test_dynamic_model_with_tokenizer",
               "--trust-remote-code",
               "--cache-dir",
               "/tmp",
           ]			,  )
       def 			UpperCamelCase_	(					self							)	->   List[Any]:
            import transformers.commands.transformers_cli

            # # remove any previously downloaded model to start clean
            shutil.rmtree("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer"			,  ignore_errors=__lowerCamelCase							)

            # run the command
            transformers.commands.transformers_cli.main()

            # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
            self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs"							)							)
            self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs"							)							)
            self.assertTrue(
                os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots"							)							)







"""simple docstring"""



import requests
from bsa import BeautifulSoup


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      int       , snake_case    :      str							)->						str:






     '''simple docstring'''



     UpperCAmelCase__		:  Union[str, Any]				=				(
         "https://www.horoscope.com/us/horoscopes/general/"
         f'horoscope-general-daily-{day}.aspx?sign={zodiac_sign}'
     )
     UpperCAmelCase__		:  List[str]				=				BeautifulSoup(requests.get(snake_case							).content       , "html.parser"							)
     return soup.find("div"       , class_="main-horoscope"							).p.text


if __name__ == "__main__":
 print("""Daily Horoscope. \n""")
 print(
     """enter your Zodiac sign number:\n""",
     """1. Aries\n""",
     """2. Taurus\n""",
     """3. Gemini\n""",
     """4. Cancer\n""",
     """5. Leo\n""",
     """6. Virgo\n""",
     """7. Libra\n""",
     """8. Scorpio\n""",
     """9. Sagittarius\n""",
     """10. Capricorn\n""",
     """11. Aquarius\n""",
     """12. Pisces\n""",
 )
 _lowerCAmelCase     :     List[str]            =	int(input("""number> """).strip())
 print("""choose some day:\n""", """yesterday\n""", """today\n""", """tomorrow\n""")
 _lowerCAmelCase     :     int            =	input("""enter the day> """)
 _lowerCAmelCase     :     Any            =	horoscope(zodiac_sign, day)
 print(horoscope_text)


