#! /usr/bin/env python
#
#   gepecell.py -- Front-end script for evaluating R-based 'weight'
#   function over a large dataset.
#
#   Copyright (C) 2011, 2012  University of Zurich. All rights reserved.
#
#   This program is free software: you can redistribute it and/or
#   modify
#   it under the terms of the GNU General Public License as published by
#   the Free Software Foundation, either version 3 of the License, or
#   (at your option) any later version.
#
#   This program is distributed in the hope that it will be useful,
#   but WITHOUT ANY WARRANTY; without even the implied warranty of
#   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#   GNU General Public License for more details.
#
#   You should have received a copy of the GNU General Public License
#   along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
"""
Front-end script for submitting multiple `R` jobs.
It uses the generic `gc3libs.cmdline.SessionBasedScript` framework.

See the output of ``gepecell.py --help`` for program usage
instructions.

Input parameters consists of:
:param str edges file: Path to an .csv file containing input data in
the for of: 
    X1   X2
1  id1  id2
2  id1  id3
3  id1  id4

...

XXX: To be clarified:
. When input files should be removed ?
. What happen if an error happen at merging time ?
. Should be possible to re-run a subset of the initial chunk list
without re-creating a new session ?
e.g. adding a new argument accepting chunk ranges (-R 3000:7500)
This would trigger the re-run of the whole workflow only 
for lines between 3000 and 7500
"""

# summary of user-visible changes
__changelog__ = """
  2013-07-03:
  * Initial version
"""
__author__ = 'Sergio Maffioletti <sergio.maffioletti@gc3.uzh.ch>'
__docformat__ = 'reStructuredText'


# run script, but allow GC3Pie persistence module to access classes defined here;
# for details, see: http://code.google.com/p/gc3pie/issues/detail?id=95
if __name__ == "__main__":
    import gepecell
    gepecell.GepecellScript().run()

import os
import sys
import time
import tempfile

import tarfile
import shutil
import pandas
# import csv

from pkg_resources import Requirement, resource_filename

import gc3libs
import gc3libs.exceptions
from gc3libs import Application, Run, Task
from gc3libs.cmdline import SessionBasedScript, executable_file
import gc3libs.utils
from gc3libs.quantity import Memory, kB, MB, GB, Duration, hours, minutes, seconds
from gc3libs.workflow import RetryableTask

DEFAULT_REMOTE_OUTPUT_FOLDER = "output"
DEFAULT_EPICELL_BINARY="robustnessintime"    
## custom application class
class GepecellApplication(Application):
    """
    Custom class to wrap the execution of the R scripts passed in src_dir.
    """
    application_name = 'gepecell'
    
    def __init__(self, parameter_string, **extra_args):

        executables = []
        inputs = dict()
        outputs = dict()

        if 'binary' in extra_args:
            binary_name = os.path.basename(extra_args['binary'])
            arguments = "./%s" % binary_name
            inputs[extra_args['binary']] = binary_name
            executables.append(binary_name)
        else:
            arguments = DEFAULT_EPICELL_BINARY

        for param in parameter_string.strip().split(','):
            arguments += " %s " % param
        # Set output
        outputs[DEFAULT_REMOTE_OUTPUT_FOLDER] = os.path.basename(DEFAULT_REMOTE_OUTPUT_FOLDER)
        arguments += DEFAULT_REMOTE_OUTPUT_FOLDER

        gc3libs.log.debug("Creating application for executing: %s",
                          arguments)
        
        Application.__init__(
            self,
            arguments = arguments,
            inputs = inputs,
            outputs = gc3libs.ANY_OUTPUT,
            stdout = 'gepecell.log',
            join=True,
            executables = executables,
            **extra_args)

    def terminated(self):
        """
        Check whether output file has been properly created
        """
        pass

class GepecellScript(SessionBasedScript):
    """
    Takes 1 .csv input file containing the list of parameters to be passed
    to the `ctx-linkdyn-ordprm-sirs.p4` application.
    Each line of the input .csv file correspond to the parameter list to be
    passed to a single `ctx-linkdyn-ordprm-sirs.p4` execution. For each line
    of the input .csv file a GepecellApplication needs to be generated (depends on
    chunk value passed as part of the input options).
    Splits input .csv file into smaller chunks, each of them of size 
    'self.params.chunk_size'.
    Then submits one execution for each of the created chunked files.

    The ``gepecell`` command keeps a record of jobs (submitted, executed
    and pending) in a session file (set name with the ``-s`` option); at
    each invocation of the command, the status of all recorded jobs is
    updated, output from finished jobs is collected, and a summary table
    of all known jobs is printed.
    
    Options can specify a maximum number of jobs that should be in
    'SUBMITTED' or 'RUNNING' state; ``gepecell`` will delay submission of
    newly-created jobs so that this limit is never exceeded.

    Once the processing of all chunked files has been completed, ``gepecell``
    aggregates them into a single larger output file located in 
    'self.params.output'.
    """

    def __init__(self):
        SessionBasedScript.__init__(
            self,
            version = __version__, # module version == script version
            application = GepecellApplication, 
            # only display stats for the top-level policy objects
            # (which correspond to the processed files) omit counting
            # actual applications because their number varies over
            # time as checkpointing and re-submission takes place.
            stats_only_for = GepecellApplication,
            )

    def setup_args(self):
        
        self.add_param('csv_input_file', type=str,
                       help="Input .csv file")

        self.add_param("-k", "--chunk", metavar="INT", type=int,
                       dest="chunk_size", default=1000,
                       help="How to split the edges input data set.")

        self.add_param("-B", "--binary",
                       dest="binary", default=None,
                       help="Path to alternative 'Robustnessintime' binary file." \
                       " Note: binary fily MUST be statically linked.")

        
    def parse_args(self):
        """
        Check presence of input folder (should contains R scripts).
        path to command_file should also be valid.
        """
        try:
            assert os.path.isfile(os.path.abspath(self.params.csv_input_file)),  \
                "Input CSV not found: %s " \
                % os.path.abspath(self.params.csv_input_file)

            # Verify that 'self.params.chunk_size' is int
            assert isinstance(self.params.chunk_size,int), \
                "Chunk value must be an interger."
            self.params.chunk_size = int(self.params.chunk_size)

            if self.params.binary:
                assert os.path.isfile(self.params.binary), \
                    "'Robustnessintime' binary file '%s' not found" % self.params.binary
            
        except AssertionError as ex:
            raise ValueError(ex.message)            

    def new_tasks(self, extra):
        """
        Read content of 'command_file'
        For each command line, generate a new GcgpsTask
        """
        tasks = []

        with open(self.params.csv_input_file) as fd:
            for line in fd:
                jobname = "gepecell-%s" % (line.strip().replace(",","_"))

                extra_args = extra.copy()
                extra_args['jobname'] = jobname
            
                extra_args['output_dir'] = self.params.output
                extra_args['output_dir'] = extra_args['output_dir'].replace('NAME', jobname)
                extra_args['output_dir'] = extra_args['output_dir'].replace('SESSION', jobname)
                extra_args['output_dir'] = extra_args['output_dir'].replace('DATE', jobname)
                extra_args['output_dir'] = extra_args['output_dir'].replace('TIME', jobname)

                if self.params.binary:
                    extra_args['binary'] = self.params.binary
                
                tasks.append(GepecellApplication(
                    line,
                    **extra_args))

        return tasks

    def _getchunk(self, file_to_chunk, chunk_size=2):
        """
        Takes a file_name as input and a defined chunk size
        ( uses 1000 as default )
        returns a list of filenames 1 for each chunk created and a corresponding
        index reference
        e.g. ('/tmp/chunk2800.csv,2800) for the chunk segment that goes
        from 2800 to (2800 + chunk_size)
        """
        
        chunks = []
        chunk_files_dir = os.path.join(self.session.path,"tmp")

        # creating 'chunk_files_dir'
        if not(os.path.isdir(chunk_files_dir)):
            try:
                os.mkdir(chunk_files_dir)
            except OSError, osx:
                gc3libs.log.error("Failed while creating tmp folder %s. " % chunk_files_dir +
                                  "Error %s." % str(osx) +
                                  "Using default '/tmp'")
                chunk_files_dir = "/tmp"

        # XXX: by convenction, 1st row contains headers
        reader = pandas.read_csv(file_to_chunk, header=0, chunksize=chunk_size)

        index = 0
        for chunk in reader:
            index += 1     
            filename = "%s/chunk_%s.csv" % (chunk_files_dir,index)
            chunk.to_csv(filename, header=True, index=False)
            chunks.append((filename,index))
            
        return chunks
