# Path: datarobot_batch_scoring/consts.py
# SENTINEL = Batch(-1, 0, None, '', -1)
# ERROR_SENTINEL = Batch(-1, 1, None, '', -1)
# REPORT_INTERVAL = 5
# DEPRECATION_WARNING = (
#     '{yellow}{bold}Deprecation Warning!{reset} '
#     'The Batch Scoring script is deprecated. It will continue functioning '
#     'indefinitely, but it will not receive any new bug fixes and new '
#     'functionality. Please, use the Batch Prediction command-line tools '
#     'instead: '
#     '({underline}https://app.datarobot.com/docs/predictions'
#     '/batch/cli-scripts.html{reset}).'
#     .format(
#         yellow='\033[93m',
#         bold='\033[1m',
#         reset='\033[0m',
#         underline='\033[4m'
#     )
#    )
#     CTX_WARNING = 'CTX_WARNING'
#     CTX_ERROR = 'CTX_ERROR'
#     RESPONSE = 'RESPONSE'
#     SENTINEL = 'SENTINEL'
#     SHOVEL_DONE = 'SHOVEL_DONE'
#     SHOVEL_ERROR = 'SHOVEL_ERROR'
#     SHOVEL_CSV_ERROR = 'SHOVEL_CSV_ERROR'
#     SHOVEL_PROGRESS = 'SHOVEL_PROGRESS'
#     NETWORK_DONE = 'NETWORK_DONE'
#     NETWORK_ERROR = 'NETWORK_ERROR'
#     NETWORK_PROGRESS = 'NETWORK_PROGRESS'
#     WRITER_DONE = 'WRITER_DONE'
#     WRITER_ERROR = 'WRITER_ERROR'
#     WRITER_PROGRESS = 'WRITER_PROGRESS'
#     REGRESSION = 'Regression'
#     BINARY = 'Binary'
# class WriterQueueMsg(object):
# class ProgressQueueMsg(object):
# class TargetType(object):
# 
# Path: datarobot_batch_scoring/reader.py
# def fast_to_csv_chunk(data, header):
#     """Fast routine to format data for prediction api.
# 
#     Returns data in unicode.
#     """
#     header = ','.join(header)
#     chunk = ''.join(chain((header, os.linesep), data))
#     if six.PY3:
#         return chunk.encode('utf-8')
#     else:
#         return chunk
# 
# def slow_to_csv_chunk(data, header):
#     """Slow routine to format data for prediction api.
#     Returns data in unicode.
#     """
#     if six.PY3:
#         buf = io.StringIO()
#     else:
#         buf = io.BytesIO()
# 
#     writer = csv.writer(buf)
#     writer.writerow(header)
#     writer.writerows(data)
#     if six.PY3:
#         return buf.getvalue().encode('utf-8')
#     else:
#         return buf.getvalue()
# 
# Path: datarobot_batch_scoring/utils.py
# def compress(data):
#     buf = io.BytesIO()
#     with GzipFile(fileobj=buf, mode='wb', compresslevel=2) as f:
#         f.write(data)
#     return buf.getvalue()
# 
# def get_rusage():
#     usage = resource.getrusage(resource.RUSAGE_SELF)
#     return {
#         "utime": usage.ru_utime,
#         "stime": usage.ru_stime,
#         "rss": usage.ru_maxrss,
#     }
# 
# class Worker(object):
#     state_names = {}
# 
#     def __init__(self, status_value):
#         self.status_value = status_value
# 
#     @property
#     def state(self):
#         return self.status_value.value
# 
#     @state.setter
#     def state(self, status):
#         self.ui.debug('state: {} -> {}'
#                       ''.format(self.state_name(), self.state_name(status)))
#         self.status_value.value = status
# 
#     def state_name(self, s=None):
#         return self.state_names[s or self.state]


import collections
import logging
import os
import sys
from datarobot_batch_scoring.consts import (WriterQueueMsg, Batch,
                                            ProgressQueueMsg)
from datarobot_batch_scoring.reader import (fast_to_csv_chunk,
                                            slow_to_csv_chunk)
from datarobot_batch_scoring.utils import compress, get_rusage, Worker
                        'batch {}-{} transmitting {} byte - space savings '
                        '{}%'.format(batch.id, batch.rows,
                                     sys.getsizeof(data),
                                     '%.2f' % float(1 -
                                                    (sys.getsizeof(data) /
                                                     starting_size))))
                else:
                    self.ui.debug('batch {}-{} transmitting {} bytes'
                                  ''.format(batch.id, batch.rows,
                                            starting_size))

                yield (batch, data)
            else:
                if batch.rows < 2:
                    msg = ('batch {} is single row but bigger '
                           'than limit, skipping. We lost {} '
                           'records'.format(batch.id,
                                            len(batch.data)))
                    self.ui.error(msg)
                    self.send_error_to_ctx(batch, msg)
                    continue

                msg = ('batch {}-{} is too long: {} bytes,'
                       ' splitting'.format(batch.id, batch.rows,
                                           len(data)))
                self.ui.debug(msg)
                self.send_warning_to_ctx(batch, msg)
                split_point = int(batch.rows/2)

                data1 = batch.data[:split_point]

# Path: datarobot_batch_scoring/consts.py
# SENTINEL = Batch(-1, 0, None, '', -1)
# ERROR_SENTINEL = Batch(-1, 1, None, '', -1)
# REPORT_INTERVAL = 5
# DEPRECATION_WARNING = (
#     '{yellow}{bold}Deprecation Warning!{reset} '
#     'The Batch Scoring script is deprecated. It will continue functioning '
#     'indefinitely, but it will not receive any new bug fixes and new '
#     'functionality. Please, use the Batch Prediction command-line tools '
#     'instead: '
#     '({underline}https://app.datarobot.com/docs/predictions'
#     '/batch/cli-scripts.html{reset}).'
#     .format(
#         yellow='\033[93m',
#         bold='\033[1m',
#         reset='\033[0m',
#         underline='\033[4m'
#     )
#    )
#     CTX_WARNING = 'CTX_WARNING'
#     CTX_ERROR = 'CTX_ERROR'
#     RESPONSE = 'RESPONSE'
#     SENTINEL = 'SENTINEL'
#     SHOVEL_DONE = 'SHOVEL_DONE'
#     SHOVEL_ERROR = 'SHOVEL_ERROR'
#     SHOVEL_CSV_ERROR = 'SHOVEL_CSV_ERROR'
#     SHOVEL_PROGRESS = 'SHOVEL_PROGRESS'
#     NETWORK_DONE = 'NETWORK_DONE'
#     NETWORK_ERROR = 'NETWORK_ERROR'
#     NETWORK_PROGRESS = 'NETWORK_PROGRESS'
#     WRITER_DONE = 'WRITER_DONE'
#     WRITER_ERROR = 'WRITER_ERROR'
#     WRITER_PROGRESS = 'WRITER_PROGRESS'
#     REGRESSION = 'Regression'
#     BINARY = 'Binary'
# class WriterQueueMsg(object):
# class ProgressQueueMsg(object):
# class TargetType(object):
# 
# Path: datarobot_batch_scoring/reader.py
# def fast_to_csv_chunk(data, header):
#     """Fast routine to format data for prediction api.
# 
#     Returns data in unicode.
#     """
#     header = ','.join(header)
#     chunk = ''.join(chain((header, os.linesep), data))
#     if six.PY3:
#         return chunk.encode('utf-8')
#     else:
#         return chunk
# 
# def slow_to_csv_chunk(data, header):
#     """Slow routine to format data for prediction api.
#     Returns data in unicode.
#     """
#     if six.PY3:
#         buf = io.StringIO()
#     else:
#         buf = io.BytesIO()
# 
#     writer = csv.writer(buf)
#     writer.writerow(header)
#     writer.writerows(data)
#     if six.PY3:
#         return buf.getvalue().encode('utf-8')
#     else:
#         return buf.getvalue()
# 
# Path: datarobot_batch_scoring/utils.py
# def compress(data):
#     buf = io.BytesIO()
#     with GzipFile(fileobj=buf, mode='wb', compresslevel=2) as f:
#         f.write(data)
#     return buf.getvalue()
# 
# def get_rusage():
#     usage = resource.getrusage(resource.RUSAGE_SELF)
#     return {
#         "utime": usage.ru_utime,
#         "stime": usage.ru_stime,
#         "rss": usage.ru_maxrss,
#     }
# 
# class Worker(object):
#     state_names = {}
# 
#     def __init__(self, status_value):
#         self.status_value = status_value
# 
#     @property
#     def state(self):
#         return self.status_value.value
# 
#     @state.setter
#     def state(self, status):
#         self.ui.debug('state: {} -> {}'
#                       ''.format(self.state_name(), self.state_name(status)))
#         self.status_value.value = status
# 
#     def state_name(self, s=None):
#         return self.state_names[s or self.state]


# Path: datarobot_batch_scoring/network/base_network_worker.py
import collections
import logging
import os
import sys
from datarobot_batch_scoring.consts import (WriterQueueMsg, Batch,
                                            ProgressQueueMsg)
from datarobot_batch_scoring.reader import (fast_to_csv_chunk,
                                            slow_to_csv_chunk)
from datarobot_batch_scoring.utils import compress, get_rusage, Worker

                        'batch {}-{} transmitting {} byte - space savings '
                        '{}%'.format(batch.id, batch.rows,
                                     sys.getsizeof(data),
                                     '%.2f' % float(1 -
                                                    (sys.getsizeof(data) /
                                                     starting_size))))
                else:
                    self.ui.debug('batch {}-{} transmitting {} bytes'
                                  ''.format(batch.id, batch.rows,
                                            starting_size))

                yield (batch, data)
            else:
                if batch.rows < 2:
                    msg = ('batch {} is single row but bigger '
                           'than limit, skipping. We lost {} '
                           'records'.format(batch.id,
                                            len(batch.data)))
                    self.ui.error(msg)
                    self.send_error_to_ctx(batch, msg)
                    continue

                msg = ('batch {}-{} is too long: {} bytes,'
                       ' splitting'.format(batch.id, batch.rows,
                                           len(data)))
                self.ui.debug(msg)
                self.send_warning_to_ctx(batch, msg)
                split_point = int(batch.rows/2)

                data1 = batch.data[:split_point]

                batch1 = Batch(batch.id, split_point, batch.fieldnames,