use std::convert::TryInto;
use std::sync::Arc;

use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;

use crate::encoding::PyEncoding;
use crate::error::ToPyResult;
use serde::{Deserialize, Serialize};
use tk::processors::bert::BertProcessing;
use tk::processors::byte_level::ByteLevel;
use tk::processors::roberta::RobertaProcessing;
use tk::processors::sequence::Sequence;
use tk::processors::template::{SpecialToken, Template};
use tk::processors::PostProcessorWrapper;
use tk::{Encoding, PostProcessor};
use tokenizers as tk;

/// Base class for all post-processors
///
/// This class is not supposed to be instantiated directly. Instead, any implementation of
/// a PostProcessor will return an instance of this class when instantiated.
#[pyclass(
    dict,
    module = "tokenizers.processors",
    name = "PostProcessor",
    subclass
)]
#[derive(Clone, Deserialize, Serialize)]
#[serde(transparent)]
pub struct PyPostProcessor {
    pub processor: Arc<PostProcessorWrapper>,
}

impl PyPostProcessor {
    pub fn new(processor: Arc<PostProcessorWrapper>) -> Self {
        PyPostProcessor { processor }
    }

    pub(crate) fn get_as_subtype(&self, py: Python<'_>) -> PyResult<PyObject> {
        let base = self.clone();
        Ok(match self.processor.as_ref() {
            PostProcessorWrapper::ByteLevel(_) => Py::new(py, (PyByteLevel {}, base))?.into_py(py),
            PostProcessorWrapper::Bert(_) => Py::new(py, (PyBertProcessing {}, base))?.into_py(py),
            PostProcessorWrapper::Roberta(_) => {
                Py::new(py, (PyRobertaProcessing {}, base))?.into_py(py)
            }
            PostProcessorWrapper::Template(_) => {
                Py::new(py, (PyTemplateProcessing {}, base))?.into_py(py)
            }
            PostProcessorWrapper::Sequence(_) => Py::new(py, (PySequence {}, base))?.into_py(py),
        })
    }
}

impl PostProcessor for PyPostProcessor {
    fn added_tokens(&self, is_pair: bool) -> usize {
        self.processor.added_tokens(is_pair)
    }

    fn process_encodings(
        &self,
        encodings: Vec<Encoding>,
        add_special_tokens: bool,
    ) -> tk::Result<Vec<Encoding>> {
        self.processor
            .process_encodings(encodings, add_special_tokens)
    }
}

#[pymethods]
impl PyPostProcessor {
    fn __getstate__(&self, py: Python) -> PyResult<PyObject> {
        let data = serde_json::to_string(self.processor.as_ref()).map_err(|e| {
            exceptions::PyException::new_err(format!(
                "Error while attempting to pickle PostProcessor: {}",
                e
            ))
        })?;
        Ok(PyBytes::new_bound(py, data.as_bytes()).to_object(py))
    }

    fn __setstate__(&mut self, py: Python, state: PyObject) -> PyResult<()> {
        match state.extract::<&[u8]>(py) {
            Ok(s) => {
                self.processor = serde_json::from_slice(s).map_err(|e| {
                    exceptions::PyException::new_err(format!(
                        "Error while attempting to unpickle PostProcessor: {}",
                        e
                    ))
                })?;
                Ok(())
            }
            Err(e) => Err(e),
        }
    }

    /// Return the number of special tokens that would be added for single/pair sentences.
    ///
    /// Args:
    ///     is_pair (:obj:`bool`):
    ///         Whether the input would be a pair of sequences
    ///
    /// Returns:
    ///     :obj:`int`: The number of tokens to add
    #[pyo3(text_signature = "(self, is_pair)")]
    fn num_special_tokens_to_add(&self, is_pair: bool) -> usize {
        self.processor.added_tokens(is_pair)
    }

    /// Post-process the given encodings, generating the final one
    ///
    /// Args:
    ///     encoding (:class:`~tokenizers.Encoding`):
    ///         The encoding for the first sequence
    ///
    ///     pair (:class:`~tokenizers.Encoding`, `optional`):
    ///         The encoding for the pair sequence
    ///
    ///     add_special_tokens (:obj:`bool`):
    ///         Whether to add the special tokens
    ///
    /// Return:
    ///     :class:`~tokenizers.Encoding`: The final encoding
    #[pyo3(signature = (encoding, pair = None, add_special_tokens = true))]
    #[pyo3(text_signature = "(self, encoding, pair=None, add_special_tokens=True)")]
    fn process(
        &self,
        encoding: &PyEncoding,
        pair: Option<&PyEncoding>,
        add_special_tokens: bool,
    ) -> PyResult<PyEncoding> {
        let final_encoding = ToPyResult(self.processor.process(
            encoding.encoding.clone(),
            pair.map(|e| e.encoding.clone()),
            add_special_tokens,
        ))
        .into_py()?;
        Ok(final_encoding.into())
    }

    fn __repr__(&self) -> PyResult<String> {
        crate::utils::serde_pyo3::repr(self)
            .map_err(|e| exceptions::PyException::new_err(e.to_string()))
    }

    fn __str__(&self) -> PyResult<String> {
        crate::utils::serde_pyo3::to_string(self)
            .map_err(|e| exceptions::PyException::new_err(e.to_string()))
    }
}

/// This post-processor takes care of adding the special tokens needed by
/// a Bert model:
///
///     - a SEP token
///     - a CLS token
///
/// Args:
///     sep (:obj:`Tuple[str, int]`):
///         A tuple with the string representation of the SEP token, and its id
///
///     cls (:obj:`Tuple[str, int]`):
///         A tuple with the string representation of the CLS token, and its id
#[pyclass(extends=PyPostProcessor, module = "tokenizers.processors", name = "BertProcessing")]
pub struct PyBertProcessing {}
#[pymethods]
impl PyBertProcessing {
    #[new]
    #[pyo3(text_signature = "(self, sep, cls)")]
    fn new(sep: (String, u32), cls: (String, u32)) -> (Self, PyPostProcessor) {
        (
            PyBertProcessing {},
            PyPostProcessor::new(Arc::new(BertProcessing::new(sep, cls).into())),
        )
    }

    fn __getnewargs__<'p>(&self, py: Python<'p>) -> Bound<'p, PyTuple> {
        PyTuple::new_bound(py, [("", 0), ("", 0)])
    }
}

/// This post-processor takes care of adding the special tokens needed by
/// a Roberta model:
///
///     - a SEP token
///     - a CLS token
///
/// It also takes care of trimming the offsets.
/// By default, the ByteLevel BPE might include whitespaces in the produced tokens. If you don't
/// want the offsets to include these whitespaces, then this PostProcessor should be initialized
/// with :obj:`trim_offsets=True`
///
/// Args:
///     sep (:obj:`Tuple[str, int]`):
///         A tuple with the string representation of the SEP token, and its id
///
///     cls (:obj:`Tuple[str, int]`):
///         A tuple with the string representation of the CLS token, and its id
///
///     trim_offsets (:obj:`bool`, `optional`, defaults to :obj:`True`):
///         Whether to trim the whitespaces from the produced offsets.
///
///     add_prefix_space (:obj:`bool`, `optional`, defaults to :obj:`True`):
///         Whether the add_prefix_space option was enabled during pre-tokenization. This
///         is relevant because it defines the way the offsets are trimmed out.
#[pyclass(extends=PyPostProcessor, module = "tokenizers.processors", name = "RobertaProcessing")]
pub struct PyRobertaProcessing {}
#[pymethods]
impl PyRobertaProcessing {
    #[new]
    #[pyo3(signature = (sep, cls, trim_offsets = true, add_prefix_space = true), text_signature = "(self, sep, cls, trim_offsets=True, add_prefix_space=True)")]
    fn new(
        sep: (String, u32),
        cls: (String, u32),
        trim_offsets: bool,
        add_prefix_space: bool,
    ) -> (Self, PyPostProcessor) {
        let proc = RobertaProcessing::new(sep, cls)
            .trim_offsets(trim_offsets)
            .add_prefix_space(add_prefix_space);
        (
            PyRobertaProcessing {},
            PyPostProcessor::new(Arc::new(proc.into())),
        )
    }

    fn __getnewargs__<'p>(&self, py: Python<'p>) -> Bound<'p, PyTuple> {
        PyTuple::new_bound(py, [("", 0), ("", 0)])
    }
}

/// This post-processor takes care of trimming the offsets.
///
/// By default, the ByteLevel BPE might include whitespaces in the produced tokens. If you don't
/// want the offsets to include these whitespaces, then this PostProcessor must be used.
///
/// Args:
///     trim_offsets (:obj:`bool`):
///         Whether to trim the whitespaces from the produced offsets.
#[pyclass(extends=PyPostProcessor, module = "tokenizers.processors", name = "ByteLevel")]
pub struct PyByteLevel {}
#[pymethods]
impl PyByteLevel {
    #[new]
    #[pyo3(signature = (trim_offsets = None, **_kwargs), text_signature = "(self, trim_offsets=True)")]
    fn new(
        trim_offsets: Option<bool>,
        _kwargs: Option<&Bound<'_, PyDict>>,
    ) -> (Self, PyPostProcessor) {
        let mut byte_level = ByteLevel::default();

        if let Some(to) = trim_offsets {
            byte_level = byte_level.trim_offsets(to);
        }

        (
            PyByteLevel {},
            PyPostProcessor::new(Arc::new(byte_level.into())),
        )
    }
}

#[derive(Clone, Debug)]
pub struct PySpecialToken(SpecialToken);

impl From<PySpecialToken> for SpecialToken {
    fn from(v: PySpecialToken) -> Self {
        v.0
    }
}

impl FromPyObject<'_> for PySpecialToken {
    fn extract_bound(ob: &Bound<'_, PyAny>) -> PyResult<Self> {
        if let Ok(v) = ob.extract::<(String, u32)>() {
            Ok(Self(v.into()))
        } else if let Ok(v) = ob.extract::<(u32, String)>() {
            Ok(Self(v.into()))
        } else if let Ok(d) = ob.downcast::<PyDict>() {
            let id = d
                .get_item("id")?
                .ok_or_else(|| exceptions::PyValueError::new_err("`id` must be specified"))?
                .extract::<String>()?;
            let ids = d
                .get_item("ids")?
                .ok_or_else(|| exceptions::PyValueError::new_err("`ids` must be specified"))?
                .extract::<Vec<u32>>()?;
            let tokens = d
                .get_item("tokens")?
                .ok_or_else(|| exceptions::PyValueError::new_err("`tokens` must be specified"))?
                .extract::<Vec<String>>()?;

            Ok(Self(
                ToPyResult(SpecialToken::new(id, ids, tokens)).into_py()?,
            ))
        } else {
            Err(exceptions::PyTypeError::new_err(
                "Expected Union[Tuple[str, int], Tuple[int, str], dict]",
            ))
        }
    }
}

#[derive(Clone, Debug)]
pub struct PyTemplate(Template);

impl From<PyTemplate> for Template {
    fn from(v: PyTemplate) -> Self {
        v.0
    }
}

impl FromPyObject<'_> for PyTemplate {
    fn extract_bound(ob: &Bound<'_, PyAny>) -> PyResult<Self> {
        if let Ok(s) = ob.extract::<&str>() {
            Ok(Self(
                s.try_into().map_err(exceptions::PyValueError::new_err)?,
            ))
        } else if let Ok(s) = ob.extract::<Vec<String>>() {
            Ok(Self(
                s.try_into().map_err(exceptions::PyValueError::new_err)?,
            ))
        } else {
            Err(exceptions::PyTypeError::new_err(
                "Expected Union[str, List[str]]",
            ))
        }
    }
}

/// Provides a way to specify templates in order to add the special tokens to each
/// input sequence as relevant.
///
/// Let's take :obj:`BERT` tokenizer as an example. It uses two special tokens, used to
/// delimitate each sequence. :obj:`[CLS]` is always used at the beginning of the first
/// sequence, and :obj:`[SEP]` is added at the end of both the first, and the pair
/// sequences. The final result looks like this:
///
///     - Single sequence: :obj:`[CLS] Hello there [SEP]`
///     - Pair sequences: :obj:`[CLS] My name is Anthony [SEP] What is my name? [SEP]`
///
/// With the type ids as following::
///
///     [CLS]   ...   [SEP]   ...   [SEP]
///       0      0      0      1      1
///
/// You can achieve such behavior using a TemplateProcessing::
///
///     TemplateProcessing(
///         single="[CLS] $0 [SEP]",
///         pair="[CLS] $A [SEP] $B:1 [SEP]:1",
///         special_tokens=[("[CLS]", 1), ("[SEP]", 0)],
///     )
///
/// In this example, each input sequence is identified using a ``$`` construct. This identifier
/// lets us specify each input sequence, and the type_id to use. When nothing is specified,
/// it uses the default values. Here are the different ways to specify it:
///
///     - Specifying the sequence, with default ``type_id == 0``: ``$A`` or ``$B``
///     - Specifying the `type_id` with default ``sequence == A``: ``$0``, ``$1``, ``$2``, ...
///     - Specifying both: ``$A:0``, ``$B:1``, ...
///
/// The same construct is used for special tokens: ``<identifier>(:<type_id>)?``.
///
/// **Warning**: You must ensure that you are giving the correct tokens/ids as these
/// will be added to the Encoding without any further check. If the given ids correspond
/// to something totally different in a `Tokenizer` using this `PostProcessor`, it
/// might lead to unexpected results.
///
/// Args:
///     single (:obj:`Template`):
///         The template used for single sequences
///
///     pair (:obj:`Template`):
///         The template used when both sequences are specified
///
///     special_tokens (:obj:`Tokens`):
///         The list of special tokens used in each sequences
///
/// Types:
///
///     Template (:obj:`str` or :obj:`List`):
///         - If a :obj:`str` is provided, the whitespace is used as delimiter between tokens
///         - If a :obj:`List[str]` is provided, a list of tokens
///
///     Tokens (:obj:`List[Union[Tuple[int, str], Tuple[str, int], dict]]`):
///         - A :obj:`Tuple` with both a token and its associated ID, in any order
///         - A :obj:`dict` with the following keys:
///             - "id": :obj:`str` => The special token id, as specified in the Template
///             - "ids": :obj:`List[int]` => The associated IDs
///             - "tokens": :obj:`List[str]` => The associated tokens
///
///          The given dict expects the provided :obj:`ids` and :obj:`tokens` lists to have
///          the same length.
#[pyclass(extends=PyPostProcessor, module = "tokenizers.processors", name = "TemplateProcessing")]
pub struct PyTemplateProcessing {}
#[pymethods]
impl PyTemplateProcessing {
    #[new]
    #[pyo3(signature = (single = None, pair = None, special_tokens = None), text_signature = "(self, single, pair, special_tokens)")]
    fn new(
        single: Option<PyTemplate>,
        pair: Option<PyTemplate>,
        special_tokens: Option<Vec<PySpecialToken>>,
    ) -> PyResult<(Self, PyPostProcessor)> {
        let mut builder = tk::processors::template::TemplateProcessing::builder();

        if let Some(seq) = single {
            builder.single(seq.into());
        }
        if let Some(seq) = pair {
            builder.pair(seq.into());
        }
        if let Some(sp) = special_tokens {
            builder.special_tokens(sp);
        }
        let processor = builder
            .build()
            .map_err(|e| exceptions::PyValueError::new_err(e.to_string()))?;

        Ok((
            PyTemplateProcessing {},
            PyPostProcessor::new(Arc::new(processor.into())),
        ))
    }
}

/// Sequence Processor
///
/// Args:
///     processors (:obj:`List[PostProcessor]`)
///         The processors that need to be chained
#[pyclass(extends=PyPostProcessor, module = "tokenizers.processors", name = "Sequence")]
pub struct PySequence {}
#[pymethods]
impl PySequence {
    #[new]
    #[pyo3(signature = (processors_py), text_signature = "(self, processors)")]
    fn new(processors_py: &Bound<'_, PyList>) -> (Self, PyPostProcessor) {
        let mut processors: Vec<PostProcessorWrapper> = Vec::with_capacity(processors_py.len());
        for n in processors_py.iter() {
            let processor: PyRef<PyPostProcessor> = n.extract().unwrap();
            let processor = processor.processor.as_ref();
            processors.push(processor.clone());
        }
        let sequence_processor = Sequence::new(processors);
        (
            PySequence {},
            PyPostProcessor::new(Arc::new(PostProcessorWrapper::Sequence(sequence_processor))),
        )
    }

    fn __getnewargs__<'p>(&self, py: Python<'p>) -> Bound<'p, PyTuple> {
        PyTuple::new_bound(py, [PyList::empty_bound(py)])
    }
}

/// Processors Module
#[pymodule]
pub fn processors(m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<PyPostProcessor>()?;
    m.add_class::<PyBertProcessing>()?;
    m.add_class::<PyRobertaProcessing>()?;
    m.add_class::<PyByteLevel>()?;
    m.add_class::<PyTemplateProcessing>()?;
    m.add_class::<PySequence>()?;
    Ok(())
}

#[cfg(test)]
mod test {
    use std::sync::Arc;

    use pyo3::prelude::*;
    use tk::processors::bert::BertProcessing;
    use tk::processors::PostProcessorWrapper;

    use crate::processors::PyPostProcessor;

    #[test]
    fn get_subtype() {
        Python::with_gil(|py| {
            let py_proc = PyPostProcessor::new(Arc::new(
                BertProcessing::new(("SEP".into(), 0), ("CLS".into(), 1)).into(),
            ));
            let py_bert = py_proc.get_as_subtype(py).unwrap();
            assert_eq!(
                "BertProcessing",
                py_bert.bind(py).get_type().qualname().unwrap()
            );
        })
    }

    #[test]
    fn serialize() {
        let rs_processing = BertProcessing::new(("SEP".into(), 0), ("CLS".into(), 1));
        let rs_wrapper: PostProcessorWrapper = rs_processing.clone().into();
        let rs_processing_ser = serde_json::to_string(&rs_processing).unwrap();
        let rs_wrapper_ser = serde_json::to_string(&rs_wrapper).unwrap();

        let py_processing = PyPostProcessor::new(Arc::new(rs_wrapper));
        let py_ser = serde_json::to_string(&py_processing).unwrap();
        assert_eq!(py_ser, rs_processing_ser);
        assert_eq!(py_ser, rs_wrapper_ser);

        let py_processing: PyPostProcessor = serde_json::from_str(&rs_processing_ser).unwrap();
        match py_processing.processor.as_ref() {
            PostProcessorWrapper::Bert(_) => (),
            _ => panic!("Expected Bert postprocessor."),
        }

        let py_processing: PyPostProcessor = serde_json::from_str(&rs_wrapper_ser).unwrap();
        match py_processing.processor.as_ref() {
            PostProcessorWrapper::Bert(_) => (),
            _ => panic!("Expected Bert postprocessor."),
        }
    }
}
