import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


UpperCAmelCase							=       get_logger(__name__)

# Datasets
UpperCAmelCase							=       "https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets"
UpperCAmelCase							=       "https://cdn-datasets.huggingface.co/datasets/datasets"
UpperCAmelCase							=       "https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}"

# Metrics
UpperCAmelCase							=       "https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics"
UpperCAmelCase							=       "https://cdn-datasets.huggingface.co/datasets/metric"
UpperCAmelCase							=       "https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}"

# Hub
UpperCAmelCase							=       os.environ.get("HF_ENDPOINT", "https://huggingface.co")
UpperCAmelCase							=       HF_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
UpperCAmelCase							=       "main"

UpperCAmelCase							=       version.parse(platform.python_version())

if PY_VERSION < version.parse("3.8"):
     import importlib_metadata
else:
     import importlib.metadata as importlib_metadata

# General environment variables accepted values for booleans
UpperCAmelCase							=       {"1", "ON", "YES", "TRUE"}
UpperCAmelCase							=       ENV_VARS_TRUE_VALUES.union({"AUTO"})


# Imports
UpperCAmelCase							=       version.parse(importlib_metadata.version("dill"))
UpperCAmelCase							=       version.parse(importlib_metadata.version("pandas"))
UpperCAmelCase							=       version.parse(importlib_metadata.version("pyarrow"))

UpperCAmelCase							=       os.environ.get("USE_TF", "AUTO").upper()
UpperCAmelCase							=       os.environ.get("USE_TORCH", "AUTO").upper()
UpperCAmelCase							=       os.environ.get("USE_JAX", "AUTO").upper()

UpperCAmelCase							=       "N/A"
UpperCAmelCase							=       False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase							=       importlib.util.find_spec("torch") is not None
     if TORCH_AVAILABLE:
          try:
               UpperCAmelCase							=       version.parse(importlib_metadata.version("torch"))
               logger.info(F"PyTorch version {TORCH_VERSION} available.")
          except importlib_metadata.PackageNotFoundError:
               pass
else:
     logger.info("Disabling PyTorch because USE_TF is set")

UpperCAmelCase							=       "N/A"
UpperCAmelCase							=       False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase							=       importlib.util.find_spec("tensorflow") is not None
     if TF_AVAILABLE:
          # For the metadata, we have to look for both tensorflow and tensorflow-cpu
          for package in [
              "tensorflow",
              "tensorflow-cpu",
              "tensorflow-gpu",
              "tf-nightly",
              "tf-nightly-cpu",
              "tf-nightly-gpu",
              "intel-tensorflow",
              "tensorflow-rocm",
              "tensorflow-macos",
          ]:
               try:
                    UpperCAmelCase							=       version.parse(importlib_metadata.version(package))
               except importlib_metadata.PackageNotFoundError:
                    continue
               else:
                    break
          else:
               UpperCAmelCase							=       False
     if TF_AVAILABLE:
          if TF_VERSION.major < 2:
               logger.info(F"TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.")
               UpperCAmelCase							=       False
          else:
               logger.info(F"TensorFlow version {TF_VERSION} available.")
else:
     logger.info("Disabling Tensorflow because USE_TORCH is set")


UpperCAmelCase							=       "N/A"
UpperCAmelCase							=       False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
     UpperCAmelCase							=       importlib.util.find_spec("jax") is not None and importlib.util.find_spec("jaxlib") is not None
     if JAX_AVAILABLE:
          try:
               UpperCAmelCase							=       version.parse(importlib_metadata.version("jax"))
               logger.info(F"JAX version {JAX_VERSION} available.")
          except importlib_metadata.PackageNotFoundError:
               pass
else:
     logger.info("Disabling JAX because USE_JAX is set to False")


UpperCAmelCase							=       os.environ.get("USE_BEAM", "AUTO").upper()
UpperCAmelCase							=       "N/A"
UpperCAmelCase							=       False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
     try:
          UpperCAmelCase							=       version.parse(importlib_metadata.version("apache_beam"))
          UpperCAmelCase							=       True
          logger.info(F"Apache Beam version {BEAM_VERSION} available.")
     except importlib_metadata.PackageNotFoundError:
          pass
else:
     logger.info("Disabling Apache Beam because USE_BEAM is set to False")


# Optional tools for data loading
UpperCAmelCase							=       importlib.util.find_spec("sqlalchemy") is not None

# Optional tools for feature decoding
UpperCAmelCase							=       importlib.util.find_spec("PIL") is not None
UpperCAmelCase							=       importlib.util.find_spec("soundfile") is not None and version.parse(
    importlib.import_module("soundfile").__libsndfile_version__
) >= version.parse("1.0.31")
UpperCAmelCase							=       importlib.util.find_spec("soundfile") is not None and version.parse(
    importlib.import_module("soundfile").__libsndfile_version__
) >= version.parse("1.1.0")

# Optional compression tools
UpperCAmelCase							=       importlib.util.find_spec("rarfile") is not None
UpperCAmelCase							=       importlib.util.find_spec("zstandard") is not None
UpperCAmelCase							=       importlib.util.find_spec("lz4") is not None
UpperCAmelCase							=       importlib.util.find_spec("py7zr") is not None


# Cache location
UpperCAmelCase							=       "~/.cache"
UpperCAmelCase							=       os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME)
UpperCAmelCase							=       os.path.join(XDG_CACHE_HOME, "huggingface")
UpperCAmelCase							=       os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME))

UpperCAmelCase							=       os.path.join(HF_CACHE_HOME, "datasets")
UpperCAmelCase							=       Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE))

UpperCAmelCase							=       os.path.join(HF_CACHE_HOME, "metrics")
UpperCAmelCase							=       Path(os.getenv("HF_METRICS_CACHE", DEFAULT_HF_METRICS_CACHE))

UpperCAmelCase							=       os.path.join(HF_CACHE_HOME, "modules")
UpperCAmelCase							=       Path(os.getenv("HF_MODULES_CACHE", DEFAULT_HF_MODULES_CACHE))

UpperCAmelCase							=       "downloads"
UpperCAmelCase							=       os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
UpperCAmelCase							=       Path(os.getenv("HF_DATASETS_DOWNLOADED_DATASETS_PATH", DEFAULT_DOWNLOADED_DATASETS_PATH))

UpperCAmelCase							=       "extracted"
UpperCAmelCase							=       os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
UpperCAmelCase							=       Path(os.getenv("HF_DATASETS_EXTRACTED_DATASETS_PATH", DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
UpperCAmelCase							=       (
    os.environ.get("HF_UPDATE_DOWNLOAD_COUNTS", "AUTO").upper() in ENV_VARS_TRUE_AND_AUTO_VALUES
)

# Batch size constants. For more info, see:
# https://github.com/apache/arrow/blob/master/docs/source/cpp/arrays.rst#size-limitations-and-recommendations)
UpperCAmelCase							=       1_0_0_0

# Size of the preloaded record batch in `Dataset.__iter__`
UpperCAmelCase							=       1_0

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
UpperCAmelCase							=       4 << 3_0

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
UpperCAmelCase							=       "500MB"

# Parquet configuration
UpperCAmelCase							=       1_0_0
UpperCAmelCase							=       1_0_0
UpperCAmelCase							=       1_0_0

# Offline mode
UpperCAmelCase							=       os.environ.get("HF_DATASETS_OFFLINE", "AUTO").upper() in ENV_VARS_TRUE_VALUES

# In-memory
UpperCAmelCase							=       0  # Disabled
UpperCAmelCase							=       float(os.environ.get("HF_DATASETS_IN_MEMORY_MAX_SIZE", DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
UpperCAmelCase							=       "dataset.arrow"
UpperCAmelCase							=       "indices.arrow"
UpperCAmelCase							=       "state.json"
UpperCAmelCase							=       "dataset_info.json"
UpperCAmelCase							=       "dataset_infos.json"
UpperCAmelCase							=       "LICENSE"
UpperCAmelCase							=       "metric_info.json"
UpperCAmelCase							=       "dataset_dict.json"

UpperCAmelCase							=       "datasets_modules"

UpperCAmelCase							=       2_5_5

# Streaming
UpperCAmelCase							=       2_0
UpperCAmelCase							=       5

# Datasets without script
UpperCAmelCase							=       2_0_0
UpperCAmelCase							=       1_0
UpperCAmelCase							=       2_0_0

# Progress bars
UpperCAmelCase							=       0.05  # 20 progress updates per sec




import requests
from bsa import BeautifulSoup






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: int ,	lowerCAmelCase_: str     ):
      snake_case_     :			Optional[int]       =       (
          "https://www.horoscope.com/us/horoscopes/general/"
          f"horoscope-general-daily-{day}.aspx?sign={zodiac_sign}"
      )
      snake_case_     :			int       =       BeautifulSoup(requests.get(lowerCAmelCase_     ).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",
     )
     UpperCAmelCase							=       int(input("number> ").strip())
     print("choose some day:\n", "yesterday\n", "today\n", "tomorrow\n")
     UpperCAmelCase							=       input("enter the day> ")
     UpperCAmelCase							=       horoscope(zodiac_sign, day)
     print(horoscope_text)



