old_contents: """ LOG_LEVEL: level of logging to be used for this job """
  LOG_LEVEL = "info"
  """
  LOG_FORMAT:
    format of log messages
    available format params are:
      - message: actual log message
      - levelname: message log level
  """
  LOG_FORMAT = "%(levelname)s:%(message)s"
  
  """ NUM_WORKERS: number of worker processes to use """
  NUM_WORKERS = 4
  """ DOWNLOAD_RETRIES: number of retries when downloading from S3 """
  DOWNLOAD_RETRIES = 3
  """
  OUTPUT_FILENAME:
    filename where results for this job will be stored.
    results will be output to STDOUT if set to None
    available format params are:
      - config_name: basename of config file that's passed to smr
      - time: current date and time
  """
  OUTPUT_FILENAME = "results/%(config_name)s.%(time)s.out"
  
  """ AWS_ACCESS_KEY: AWS access key used for S3 access """
  AWS_ACCESS_KEY = None
  """ AWS_SECRET_KEY: AWS secret key used for S3 access """
  AWS_SECRET_KEY = None
  """ S3_BUCKET_NAME: S3 bucket name that contains files that we want to process """
  S3_BUCKET_NAME = None
  """ S3_FILE_PREFIXES: list of S3 file prefixes that we're interested in for this job """
  S3_FILE_PREFIXES = [""]
  
  """ AWS_EC2_REGION: region to use when running ec2 workers """
  AWS_EC2_REGION = "us-east-1"
  """ AWS_EC2_AMI: ami to use when running ec2 workers """
  AWS_EC2_AMI = "ami-8f311fe6"
  """ AWS_EC2_INSTANCE_TYPE: instance type to use for EC2 instances """
  AWS_EC2_INSTANCE_TYPE = "m1.large"
  """ AWS_EC2_KEYNAME: keyname to use for starting EC2 instances """
  AWS_EC2_KEYNAME = None
  """ AWS_EC2_LOCAL_KEYFILE: local private key file used for ssh access to EC2 instances"""
  AWS_EC2_LOCAL_KEYFILE = "~/.ssh/id_rsa"
  """ AWS_EC2_SECURITY_GROUPS: security groups to use for accessing EC2 workers (needs port 22 open) """
  AWS_EC2_SECURITY_GROUPS = ["default"]
  """ AWS_EC2_SSH_USERNAME: username to use when logging into workers over SSH """
  AWS_EC2_SSH_USERNAME = "ubuntu"
  """ AWS_EC2_WORKERS: number of EC2 instances to use for this job """
  AWS_EC2_WORKERS = 1
  
  from . import __version__
  """ AWS_EC2_INITIALIZE_SMR_COMMANDS: commands to run for each EC2 instance to initialize smr """
  AWS_EC2_INITIALIZE_SMR_COMMANDS = ["sudo apt-get -y install python-pip", "sudo pip install smr==%s" % __version__]
  
  """
  MAP_FUNC:
    map function that will process s3 data
    takes a single argument of local filename to be processed
  """
  MAP_FUNC = None
  """
  REDUCE_FUNC:
    reduce function that takes input from map function's STDOUT
    takes a single string argument of a map function output
  """
  REDUCE_FUNC = None
  
  def OUTPUT_RESULTS_FUNC():
      """ OUTPUT_RESULTS_FUNC: called upon job completion. takes no arguments """
      print "done."
  
new_contents: """ LOG_LEVEL: level of logging to be used for this job """
  LOG_LEVEL = "info"
  """
  LOG_FORMAT:
    format of log messages
    available format params are:
      - message: actual log message
      - levelname: message log level
  """
  LOG_FORMAT = "%(levelname)s:%(message)s"
  
  """ NUM_WORKERS: number of worker processes to use """
  NUM_WORKERS = 4
  """ DOWNLOAD_RETRIES: number of retries when downloading from S3 """
  DOWNLOAD_RETRIES = 3
  """
  OUTPUT_FILENAME:
    filename where results for this job will be stored.
    results will be output to STDOUT if set to None
    available format params are:
      - config_name: basename of config file that's passed to smr
      - time: current date and time
  """
  OUTPUT_FILENAME = "results/%(config_name)s.%(time)s.out"
  
  """ AWS_ACCESS_KEY: AWS access key used for S3 access """
  AWS_ACCESS_KEY = None
  """ AWS_SECRET_KEY: AWS secret key used for S3 access """
  AWS_SECRET_KEY = None
  """ S3_BUCKET_NAME: S3 bucket name that contains files that we want to process """
  S3_BUCKET_NAME = None
  """ S3_FILE_PREFIXES: list of S3 file prefixes that we're interested in for this job """
  S3_FILE_PREFIXES = [""]
  
  """ AWS_EC2_REGION: region to use when running ec2 workers """
  AWS_EC2_REGION = "us-east-1"
  """ AWS_EC2_AMI: ami to use when running ec2 workers """
  AWS_EC2_AMI = "ami-8f311fe6"
  """ AWS_EC2_INSTANCE_TYPE: instance type to use for EC2 instances """
  AWS_EC2_INSTANCE_TYPE = "m1.large"
  """ AWS_EC2_KEYNAME: keyname to use for starting EC2 instances """
  AWS_EC2_KEYNAME = None
  """ AWS_EC2_LOCAL_KEYFILE: local private key file used for ssh access to EC2 instances"""
  AWS_EC2_LOCAL_KEYFILE = "~/.ssh/id_rsa"
  """ AWS_EC2_SECURITY_GROUPS: security groups to use for accessing EC2 workers (needs port 22 open) """
  AWS_EC2_SECURITY_GROUPS = ["default"]
  """ AWS_EC2_SSH_USERNAME: username to use when logging into workers over SSH """
  AWS_EC2_SSH_USERNAME = "ubuntu"
  """ AWS_EC2_WORKERS: number of EC2 instances to use for this job """
  AWS_EC2_WORKERS = 1
  
  #from . import __version__
  """ AWS_EC2_INITIALIZE_SMR_COMMANDS: commands to run for each EC2 instance to initialize smr """
  #AWS_EC2_INITIALIZE_SMR_COMMANDS = ["sudo apt-get -y install python-pip", "sudo pip install smr==%s" % __version__]
  AWS_EC2_INITIALIZE_SMR_COMMANDS = ["sudo apt-get -y install python-pip git", "sudo pip install git+git://github.com/idyedov/smr.git"]
  
  """
  MAP_FUNC:
    map function that will process s3 data
    takes a single argument of local filename to be processed
  """
  MAP_FUNC = None
  """
  REDUCE_FUNC:
    reduce function that takes input from map function's STDOUT
    takes a single string argument of a map function output
  """
  REDUCE_FUNC = None
  
  def OUTPUT_RESULTS_FUNC():
      """ OUTPUT_RESULTS_FUNC: called upon job completion. takes no arguments """
      print "done."
  
subject: install smr from github for now