from typing import Dict, Any, List

import datasets


class ScirepevalConfig(datasets.BuilderConfig):
    """BuilderConfig for SuperGLUE."""

    def __init__(self, task_type: str, features: Dict[str, Any]=None, url="", **kwargs):
        """BuilderConfig for SuperGLUE.

        Args:
        features: *list[string]*, list of the features that will appear in the
            feature dict. Should not include "label".
        data_url: *string*, url to download the zip file from.
        citation: *string*, citation for the data set.
        url: *string*, url for information about the data set.
        label_classes: *list[string]*, the list of classes for the label if the
            label is present as a string. Non-string labels will be cast to either
            'False' or 'True'.
        **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(version=datasets.Version("1.1.0"), **kwargs)
        self.features = features
        self.task_type = task_type
        self.url = url


SCIREPEVAL_CONFIGS = [
    ScirepevalConfig(name="fos", features={"paper_id": datasets.Value("string"),
         "label": datasets.Sequence(datasets.Value("int32"))}, task_type="classification"),

    ScirepevalConfig(name="mesh_descriptors", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("int32")}, task_type="classification"),
    
    ScirepevalConfig(name="biomimicry", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("int32")}, task_type="classification"),

    ScirepevalConfig(name="cite_count", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("float64")}, task_type="regression"),

    ScirepevalConfig(name="pub_year", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("float64")}, task_type="regression"),

    ScirepevalConfig(name="high_influence_cite", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),

    ScirepevalConfig(name="same_author", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),

    ScirepevalConfig(name="search", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="search"),

    ScirepevalConfig(name="drsm", task_type="classification", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("int32")}),

    ScirepevalConfig(name="relish", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),

    ScirepevalConfig(name="nfcorpus", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="search"),

    ScirepevalConfig(name="peer_review_score", task_type="regression", url="peer_review_score_hIndex/peer_review_score", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("float64")}),
    
    ScirepevalConfig(name="hIndex", task_type="regression", url="peer_review_score_hIndex/hIndex", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("float64")}),

    ScirepevalConfig(name="trec_covid", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("int8")}, task_type="search"),

    ScirepevalConfig(name="tweet_mentions", task_type="regression", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("float64")}),

    ScirepevalConfig(name="scidocs_mag", task_type="classification", url="scidocs/mag_mesh/mag", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("int32")}),
    
    ScirepevalConfig(name="scidocs_mesh", task_type="classification", url="scidocs/mag_mesh/mesh", features={"paper_id": datasets.Value("string"),
         "label": datasets.Value("int32")}),

    ScirepevalConfig(name="scidocs_view", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/coview"),
    
    ScirepevalConfig(name="scidocs_cite", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/cite"),
    
    ScirepevalConfig(name="scidocs_cocite", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/cocite"),
    
    ScirepevalConfig(name="scidocs_read", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/coread"),

    ScirepevalConfig(name="reviewers", task_type="metadata", url="paper_reviewer_matching", features={"r_id": datasets.Value("string"),
         "papers": datasets.Sequence(datasets.Value("string"))}),
    
    ScirepevalConfig(name="paper_reviewer_matching", features={"query_id": datasets.Value("string"),
         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),

]