import os

import pyarrow as pa
import pyarrow.parquet as pq
import datasets

_REPO_NAME = 'Fsoft-AIC/the-vault'

_LANG_TO_TEXT = {
    "python": "python",
    "c": "c",
    # "c#": "c_sharp",
    # "c++": "cpp",
    # "go": "go",
    # "Java": "java",
    # "javascript": "javascript",
    # "php": "php",
    # "ruby": "ruby",
    # "rust": "rust",
}


_DESCRIPTION = """The Vault"""

_HOMEPAGE = "https://huggingface.co/Fsoft-AIC"


_TEXT_TO_LANG = {}
for lang in _LANG_TO_TEXT:
    _TEXT_TO_LANG[_LANG_TO_TEXT[lang]] = lang


        
_LANG_CONFIGS = ["all"] + list(_TEXT_TO_LANG.keys())

num_shard_split = {
    'train/small/python': 1,
    'train/medium/python': 1,
    'train/small/c': 1,
    'train/medium/c': 1
}  
_SPLIT_CONFIGS = ["all", "train", "train/small", "train/medium"]

class TheVaultFunctionConfig(datasets.BuilderConfig):
    """BuilderConfig for The Vault dataset."""

    def __init__(self, *args, languages=["all"], split_set= ["all"], **kwargs):
        """BuilderConfig for the GitHub Code dataset.
        Args:
            split_set (:obj:`List[str]`): List of split set to load.
            languages (:obj:`List[str]`): List of languages to load.
            **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(
            *args,
            name= "+".join([split.replace("/", "_") for split in split_set]) + "-" + "+".join(languages),
            **kwargs,
        )
        
        languages = set([lang.lower() for lang in languages])
        split_set = set([split.lower() for split in split_set]) 
        
        assert all([language in _LANG_CONFIGS for language in languages]), f"languages {languages} contains language not in {_LANG_CONFIGS}."
        assert all([split in _SPLIT_CONFIGS for split in split_set]), f"split_set {split_set} contains element not in {_SPLIT_CONFIGS}."
        
        if "all" in split_set:
            assert len(split_set)==1, f"Passed 'all' together with other split sets. {split_set}"
        elif "train" in split_set:
            for split in split_set:
                if "train" in split and split != "train":
                    raise ValueError(f"Split set 'train' already contains '{split}'. Please only include one.")

        if "all" in languages:
            assert len(languages)==1, f"Passed 'all' together with other languages. {languages}"
        #     self.filter_languages = False
        # else:
        #     self.filter_languages = True
        
        self.languages = set(languages)
        self.split_set= split_set


class TheVaultFunction(datasets.GeneratorBasedBuilder):
    """The Vault dataset."""

    VERSION = datasets.Version("1.0.0")
    
    BUILDER_CONFIG_CLASS = TheVaultFunctionConfig
    BUILDER_CONFIGS = [TheVaultFunctionConfig(languages=[lang], split_set=[spl]) for lang in _LANG_CONFIGS for spl in _SPLIT_CONFIGS]
    DEFAULT_CONFIG_NAME = "all-all"

    
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                                            "repo": datasets.Value("string"),
                                            "path": datasets.Value("string"), 
                                            "license": datasets.Value("string"),
                                            "language": datasets.Value("string"),
                                            "identifier": datasets.Value("string"),
                                            "return_type": datasets.Value("string"),
                                            # "original_string": datasets.Value("string"),
                                            "original_docstring": datasets.Value("string"),
                                            "docstring": datasets.Value("string"),
                                            "code": datasets.Value("string"),
                                            "code_tokens": datasets.Value("string"),
                                            "docstring_tokens": datasets.Value("string"),
                                            "short_docstring": datasets.Value("string"),
                                            "short_docstring_tokens": datasets.Value("string"),
                                            "comment": datasets.Value("string"),
                                        }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            
        )

    def _split_generators(self, dl_manager):
        generators = []
        split_set = list(self.config.split_set)
        languages = list(self.config.languages)

        if "all" in split_set:
            split_set = _SPLIT_CONFIGS[1:]

        if "train" in split_set:
            split_set.remove('train')
            split_set.extend(["train/small", "train/medium"])
        
        if "all" in languages:
            languages = _LANG_CONFIGS[1:]

        for split in split_set:
            split_files = []
            for language in languages:
                num_shards = num_shard_split[f"{split}/{language}"]
                data_files = [
                    f"data/{split}/{language}-{_index:05d}-of-{num_shards:05d}.parquet"
                    for _index in range(num_shards)
                ]
                files = dl_manager.download(data_files)
                split_files.extend(files)

            generators.append(
                datasets.SplitGenerator(
                    name=split.replace("/", "_"),
                    gen_kwargs={
                        "files": split_files,
                    },
                ),
            )
        return generators

    def _generate_examples(self, files):
        key = 0
        for file_idx, file in enumerate(files):
            with open(file, "rb") as f:
                parquet_file = pq.ParquetFile(f)
                for batch_idx, record_batch in enumerate(parquet_file.iter_batches(batch_size=10_000)):
                    pa_table = pa.Table.from_batches([record_batch])
                    for row_index in range(pa_table.num_rows):
                        row = pa_table.slice(row_index, 1).to_pydict()
                        
                        # lang = row['language'][0]
                        
                        # if self.config.filter_languages and not lang in self.config.languages:
                        #     continue
                        
                        yield key, {
                                        "repo": row['repo'][0],
                                        "path": row['path'][0], 
                                        "license": row['license'][0], 
                                        "language": row['language'][0],
                                        "identifier": row['identifier'][0],
                                        "return_type": row['return_type'][0],
                                        # "original_string": row['original_string'][0],
                                        "original_docstring": row['original_docstring'][0],
                                        "docstring": row['docstring'][0],
                                        "docstring_tokens": row['docstring_tokens'][0],
                                        "code": row['code'][0],
                                        "code_tokens": row['code_tokens'][0],
                                        "short_docstring": row['short_docstring'][0],
                                        "short_docstring_tokens": row['short_docstring_tokens'][0],
                                        "comment": row['comment'][0]
                                    } 
                        key += 1