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Metadata-Version: 1.0
Name: Dataset-Maker
Version: 0.0.1
Summary: Python package for creating a dataset using InfluxDB data points
Home-page: http://git.dac.ds.unipi.gr/morphemic/datasetmaker
Author: Jean-Didier Totow
Author-email: totow@unipi.gr
License: LICENSE.txt
Description: 1. Generality
        
        Dataset maker is morphemic python library for 
        building dataset from data points registered into InfluxDB.
        Dataset maker receives the name of an application, the start time 
        and the tolerance interval. More details are provided below.
        
        2. InfluxDB format 
        
        Data points in InfluxDB should have the following format for being used
        correctly by the dataset maker:
        
        measurement : "application_name" #mandatory 
        timestamp : timestamp #optional
        fields : dictionnary containing metric exposed by the given application 
                 cpu_usage, memory_consumption, response_time, http_latency
        tags : dictionnary of metrics related information
        
        The JSON describing the above information is the following:
        
        Ex.: 
            {"measurement": "application_name", 
              "timestamp": 155655476.453, 
              "fields": {
                  "cpu_usage": 40,
                  "memory_consumption": 67.9,
                  "response_time": 28,
                  "http_latency": 12
              },
              "tags": {
                  "core": 2 #cpu_usage of 40% is the usage of the cpu core number 2
              }
            }
         
        If data points are presented as the above format, the dataset maker will output 
        a csv (application_name.csv) file with the following schema:
        time, cpu_usage, memory_consumption, response_time, http_latency, core
        
        3. Usage 
        
        
        Warming : make sure the above variables exist before importing dataset make library
        
        from morphemic.dataset import DatasetMaker 
        
        data_maker = DatasetMaker(application, start, configs)
        response  = data_maker.make()
        
        application, string containing the application name 
        start, when to start building the dataset 
        Ex.: '10m' , build dataset containg data point stored the 10 last minute
        Ex.: '3h', three hours 
        Ex.: '4d', four days 
        leave empty or set to None if you wish all data points stored in your InfluxDB
        configs is dictionnary containg parameters
        
        {
            "hostname": hostname or IP of InfluxDB
            "port": port of InfluxDB
            "username": InfluxDB username 
            "password": password of the above user 
            "dbname": database name 
            "path_dataset": path where the dataset will be saved
        }
        
        the response contains 
        {'status': True,'url': url, 'application': application_name, 'features': features}
        
        or if an error occured
        {'status': False,'message': "reason of the error"}
Platform: UNKNOWN