import logging
import struct
import zlib

from kafka.codec import (
    gzip_encode, gzip_decode, snappy_encode, snappy_decode
)
from kafka.common import (
    BrokerMetadata, PartitionMetadata, Message, OffsetAndMessage,
    ProduceResponse, FetchResponse, OffsetResponse,
    OffsetCommitResponse, OffsetFetchResponse
)
from kafka.util import (
    read_short_string, read_int_string, relative_unpack,
    write_short_string, write_int_string, group_by_topic_and_partition,
    BufferUnderflowError, ChecksumError
)

log = logging.getLogger("kafka")

class KafkaProtocol(object):
    """
    Class to encapsulate all of the protocol encoding/decoding. This class does not
    have any state associated with it, it is purely for organization.
    """
    PRODUCE_KEY       = 0
    FETCH_KEY         = 1
    OFFSET_KEY        = 2
    METADATA_KEY      = 3
    OFFSET_COMMIT_KEY = 6
    OFFSET_FETCH_KEY  = 7

    ATTRIBUTE_CODEC_MASK = 0x03
    CODEC_NONE = 0x00
    CODEC_GZIP = 0x01
    CODEC_SNAPPY = 0x02

    ###################
    #   Private API   #
    ###################

    @classmethod
    def _encode_message_header(cls, client_id, correlation_id, request_key):
        """
        Encode the common request envelope
        """
        return struct.pack('>hhih%ds' % len(client_id), 
                           request_key,          # ApiKey
                           0,                    # ApiVersion
                           correlation_id,       # CorrelationId
                           len(client_id),       #
                           client_id)            # ClientId

    @classmethod
    def _encode_message_set(cls, messages):
        """
        Encode a MessageSet. Unlike other arrays in the protocol, MessageSets are 
        not length-prefixed

        Format
        ======
        MessageSet => [Offset MessageSize Message]
          Offset => int64
          MessageSize => int32
        """
        message_set = ""
        for message in messages:
            encoded_message = KafkaProtocol._encode_message(message)
            message_set += struct.pack('>qi%ds' % len(encoded_message), 0, len(encoded_message), encoded_message)
        return message_set

    @classmethod
    def _encode_message(cls, message):
        """
        Encode a single message.

        The magic number of a message is a format version number. The only supported
        magic number right now is zero

        Format 
        ======
        Message => Crc MagicByte Attributes Key Value
          Crc => int32
          MagicByte => int8
          Attributes => int8
          Key => bytes
          Value => bytes
        """
        if message.magic == 0:
            msg = struct.pack('>BB', message.magic, message.attributes)
            msg += write_int_string(message.key)
            msg += write_int_string(message.value)
            crc = zlib.crc32(msg)
            msg = struct.pack('>i%ds' % len(msg), crc, msg)
        else:
            raise Exception("Unexpected magic number: %d" % message.magic)
        return msg


    @classmethod
    def _decode_message_set_iter(cls, data):
        """
        Iteratively decode a MessageSet

        Reads repeated elements of (offset, message), calling decode_message to decode a
        single message. Since compressed messages contain futher MessageSets, these two methods
        have been decoupled so that they may recurse easily.
        """
        cur = 0
        while cur < len(data):
            try:
                ((offset, ), cur) = relative_unpack('>q', data, cur)
                (msg, cur) = read_int_string(data, cur)
                for (offset, message) in KafkaProtocol._decode_message(msg, offset):
                    yield OffsetAndMessage(offset, message)
            except BufferUnderflowError: # If we get a partial read of a message, stop
                raise StopIteration()

    @classmethod
    def _decode_message(cls, data, offset):
        """
        Decode a single Message

        The only caller of this method is decode_message_set_iter. They are decoupled to 
        support nested messages (compressed MessageSets). The offset is actually read from
        decode_message_set_iter (it is part of the MessageSet payload).
        """
        ((crc, magic, att), cur) = relative_unpack('>iBB', data, 0)
        if crc != zlib.crc32(data[4:]):
            raise ChecksumError("Message checksum failed")

        (key, cur) = read_int_string(data, cur)
        (value, cur) = read_int_string(data, cur)
        if att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_NONE:
            yield (offset, Message(magic, att, key, value))
        elif att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_GZIP:
            gz = gzip_decode(value)
            for (offset, message) in KafkaProtocol._decode_message_set_iter(gz):
                yield (offset, message)
        elif att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_SNAPPY:
            snp = snappy_decode(value)
            for (offset, message) in KafkaProtocol._decode_message_set_iter(snp):
                yield (offset, message)

    ##################
    #   Public API   #
    ##################

    @classmethod
    def encode_produce_request(cls, client_id, correlation_id, payloads=[], acks=1, timeout=1000):
        """
        Encode some ProduceRequest structs

        Params
        ======
        client_id: string
        correlation_id: string
        payloads: list of ProduceRequest
        acks: How "acky" you want the request to be
            0: immediate response
            1: written to disk by the leader
            2+: waits for this many number of replicas to sync
            -1: waits for all replicas to be in sync
        timeout: Maximum time the server will wait for acks from replicas. This is _not_ a socket timeout
        """
        grouped_payloads = group_by_topic_and_partition(payloads)
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.PRODUCE_KEY)
        message += struct.pack('>hii', acks, timeout, len(grouped_payloads))
        for topic, topic_payloads in grouped_payloads.items():
            message += struct.pack('>h%dsi' % len(topic), len(topic), topic, len(topic_payloads))
            for partition, payload in topic_payloads.items():
                message_set = KafkaProtocol._encode_message_set(payload.messages)
                message += struct.pack('>ii%ds' % len(message_set), partition, len(message_set), message_set)
        return struct.pack('>i%ds' % len(message), len(message), message)

    @classmethod
    def decode_produce_response(cls, data):
        """
        Decode bytes to a ProduceResponse 

        Params
        ======
        data: bytes to decode
        """
        ((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
        for i in range(num_topics):
            ((strlen,), cur) = relative_unpack('>h', data, cur)
            topic = data[cur:cur+strlen]
            cur += strlen
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            for i in range(num_partitions):
                ((partition, error, offset), cur) = relative_unpack('>ihq', data, cur)
                yield ProduceResponse(topic, partition, error, offset)

    @classmethod
    def encode_fetch_request(cls, client_id, correlation_id, payloads=[], max_wait_time=100, min_bytes=4096):
        """
        Encodes some FetchRequest structs

        Params
        ======
        client_id: string
        correlation_id: string
        payloads: list of FetchRequest
        max_wait_time: int, how long to block waiting on min_bytes of data
        min_bytes: int, the minimum number of bytes to accumulate before returning the response
        """
        
        grouped_payloads = group_by_topic_and_partition(payloads)
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.FETCH_KEY)
        message += struct.pack('>iiii', -1, max_wait_time, min_bytes, len(grouped_payloads)) # -1 is the replica id
        for topic, topic_payloads in grouped_payloads.items():
            message += write_short_string(topic)
            message += struct.pack('>i', len(topic_payloads))
            for partition, payload in topic_payloads.items():
                message += struct.pack('>iqi', partition, payload.offset, payload.max_bytes)
        return struct.pack('>i%ds' % len(message), len(message), message)

    @classmethod
    def decode_fetch_response(cls, data):
        """
        Decode bytes to a FetchResponse

        Params
        ======
        data: bytes to decode
        """
        ((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
        for i in range(num_topics):
            (topic, cur) = read_short_string(data, cur)
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            for i in range(num_partitions):
                ((partition, error, highwater_mark_offset), cur) = relative_unpack('>ihq', data, cur)
                (message_set, cur) = read_int_string(data, cur)
                yield FetchResponse(topic, partition, error, highwater_mark_offset,
                        KafkaProtocol._decode_message_set_iter(message_set))

    @classmethod
    def encode_offset_request(cls, client_id, correlation_id, payloads=[]):
        grouped_payloads = group_by_topic_and_partition(payloads)
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_KEY)
        message += struct.pack('>ii', -1, len(grouped_payloads)) # -1 is the replica id
        for topic, topic_payloads in grouped_payloads.items():
            message += write_short_string(topic)
            message += struct.pack('>i', len(topic_payloads))
            for partition, payload in topic_payloads.items():
                message += struct.pack('>iqi', partition, payload.time, payload.max_offsets)
        return struct.pack('>i%ds' % len(message), len(message), message)

    @classmethod
    def decode_offset_response(cls, data):
        """
        Decode bytes to an OffsetResponse

        Params
        ======
        data: bytes to decode
        """
        ((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
        for i in range(num_topics):
            (topic, cur) = read_short_string(data, cur)
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            for i in range(num_partitions):
                ((partition, error, num_offsets,), cur) = relative_unpack('>ihi', data, cur)
                offsets = []
                for j in range(num_offsets):
                    ((offset,), cur) = relative_unpack('>q', data, cur)
                    offsets.append(offset)
                yield OffsetResponse(topic, partition, error, tuple(offsets))

    @classmethod
    def encode_metadata_request(cls, client_id, correlation_id, topics=[]):
        """
        Encode a MetadataRequest

        Params
        ======
        client_id: string
        correlation_id: string
        topics: list of strings
        """
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.METADATA_KEY)
        message += struct.pack('>i', len(topics))
        for topic in topics:
            message += struct.pack('>h%ds' % len(topic), len(topic), topic)
        return write_int_string(message)

    @classmethod
    def decode_metadata_response(cls, data):
        """
        Decode bytes to a MetadataResponse

        Params
        ======
        data: bytes to decode
        """
        ((correlation_id, numBrokers), cur) = relative_unpack('>ii', data, 0)

        # Broker info
        brokers = {}
        for i in range(numBrokers):
            ((nodeId, ), cur) = relative_unpack('>i', data, cur)
            (host, cur) = read_short_string(data, cur)
            ((port,), cur) = relative_unpack('>i', data, cur)
            brokers[nodeId] = BrokerMetadata(nodeId, host, port)

        # Topic info
        ((num_topics,), cur) = relative_unpack('>i', data, cur)
        topicMetadata = {}
        for i in range(num_topics):
            ((topicError,), cur) = relative_unpack('>h', data, cur)
            (topicName, cur) = read_short_string(data, cur)
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            partitionMetadata = {}
            for j in range(num_partitions):
                ((partitionErrorCode, partition, leader, numReplicas), cur) = relative_unpack('>hiii', data, cur)
                (replicas, cur) = relative_unpack('>%di' % numReplicas, data, cur)
                ((numIsr,), cur) = relative_unpack('>i', data, cur)
                (isr, cur) = relative_unpack('>%di' % numIsr, data, cur)
                partitionMetadata[partition] = PartitionMetadata(topicName, partition, leader, replicas, isr)
            topicMetadata[topicName] = partitionMetadata
        return (brokers, topicMetadata)

    @classmethod
    def encode_offset_commit_request(cls, client_id, correlation_id, group, payloads):
        """
        Encode some OffsetCommitRequest structs

        Params
        ======
        client_id: string
        correlation_id: string
        group: string, the consumer group you are committing offsets for
        payloads: list of OffsetCommitRequest
        """
        grouped_payloads= group_by_topic_and_partition(payloads)
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_COMMIT_KEY)
        message += write_short_string(group)
        message += struct.pack('>i', len(grouped_payloads))
        for topic, topic_payloads in grouped_payloads.items():
            message += write_short_string(topic)
            message += struct.pack('>i', len(topic_payloads))
            for partition, payload in topic_payloads.items():
                message += struct.pack('>iq', partition, payload.offset)
                message += write_short_string(payload.metadata)
        return struct.pack('>i%ds' % len(message), len(message), message)

    @classmethod
    def decode_offset_commit_response(cls, data):
        """
        Decode bytes to an OffsetCommitResponse

        Params
        ======
        data: bytes to decode
        """
        ((correlation_id,), cur) = relative_unpack('>i', data, 0)
        (client_id, cur) = read_short_string(data, cur)
        ((num_topics,), cur) = relative_unpack('>i', data, cur)
        for i in xrange(num_topics):
            (topic, cur) = read_short_string(data, cur)
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            for i in xrange(num_partitions):
                ((partition, error), cur) = relative_unpack('>ih', data, cur)
                yield OffsetCommitResponse(topic, partition, error)

    @classmethod
    def encode_offset_fetch_request(cls, client_id, correlation_id, group, payloads):
        """
        Encode some OffsetFetchRequest structs

        Params
        ======
        client_id: string
        correlation_id: string
        group: string, the consumer group you are fetching offsets for
        payloads: list of OffsetFetchRequest
        """
        grouped_payloads = group_by_topic_and_partition(payloads)
        message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_FETCH_KEY)
        message += write_short_string(group)
        message += struct.pack('>i', len(grouped_payloads))
        for topic, topic_payloads in grouped_payloads.items():
            message += write_short_string(topic)
            message += struct.pack('>i', len(topic_payloads))
            for partition, payload in topic_payloads.items():
                message += struct.pack('>i', partition)
        return struct.pack('>i%ds' % len(message), len(message), message)

    @classmethod
    def decode_offset_fetch_response(cls, data):
        """
        Decode bytes to an OffsetFetchResponse

        Params
        ======
        data: bytes to decode
        """

        ((correlation_id,), cur) = relative_unpack('>i', data, 0)
        (client_id, cur) = read_short_string(data, cur)
        ((num_topics,), cur) = relative_unpack('>i', data, cur)
        for i in range(num_topics):
            (topic, cur) = read_short_string(data, cur)
            ((num_partitions,), cur) = relative_unpack('>i', data, cur)
            for i in range(num_partitions):
                ((partition, offset), cur) = relative_unpack('>iq', data, cur)
                (metadata, cur) = read_short_string(data, cur)
                ((error,), cur) = relative_unpack('>h', data, cur)
                yield OffsetFetchResponse(topic, partition, offset, metadata, error)

def create_message(payload, key=None):
    """
    Construct a Message

    Params
    ======
    payload: bytes, the payload to send to Kafka
    key: bytes, a key used for partition routing (optional)
    """
    return Message(0, 0, key, payload)

def create_gzip_message(payloads, key=None):
    """
    Construct a Gzipped Message containing multiple Messages

    The given payloads will be encoded, compressed, and sent as a single atomic
    message to Kafka.

    Params
    ======
    payloads: list(bytes), a list of payload to send be sent to Kafka
    key: bytes, a key used for partition routing (optional)
    """
    message_set = KafkaProtocol._encode_message_set(
            [create_message(payload) for payload in payloads])
    gzipped = gzip_encode(message_set) 
    return Message(0, 0x00 | (KafkaProtocol.ATTRIBUTE_CODEC_MASK & KafkaProtocol.CODEC_GZIP), key, gzipped)

def create_snappy_message(payloads, key=None):
    """
    Construct a Snappy Message containing multiple Messages

    The given payloads will be encoded, compressed, and sent as a single atomic
    message to Kafka.

    Params
    ======
    payloads: list(bytes), a list of payload to send be sent to Kafka
    key: bytes, a key used for partition routing (optional)
    """
    message_set = KafkaProtocol._encode_message_set(
            [create_message(payload) for payload in payloads])
    snapped = snappy_encode(message_set) 
    return Message(0, 0x00 | (KafkaProtocol.ATTRIBUTE_CODEC_MASK & KafkaProtocol.CODEC_SNAPPY), key, snapped)