Metadata-Version: 2.1
Name: apptuit
Version: 0.2.3
Summary: Apptuit Python Client
Home-page: https://github.com/ApptuitAI/apptuit-py
Author: Abhinav Upadhyay
Author-email: abhinav.updadhyay@agiltix.ai
License: UNKNOWN
Description: # Python client for Apptuit.AI
        
        [![Build Status](https://www.travis-ci.org/ApptuitAI/apptuit-py.svg?branch=master)](https://www.travis-ci.org/ApptuitAI/apptuit-py)
        
        ### Installation
        
        ```
        pip install apptuit
        ```
        
        ### Dependencies
        
        Supported Python versions: 2.7.x, 3.4, 3.5, 3.6, 3.7
        
        Requirements:
        - pandas
        - numpy
        - requests
        
        ### Usage
        
        #### Querying for data
        
        ```python
        
        from apptuit import Apptuit
        import time
        token = 'my_token' # replace with your Apptuit token
        apptuit = Apptuit(token=token) 
        start_time = int(time.time()) - 3600 # let's query for data going back 1 hour from now
        query_res = apptuit.query("fetch('proc.cpu.percent').downsample('1m', 'avg')", start=start_time)
        # we can create a Pandas dataframe from the result object by calling to_df()
        df = query_res[0].to_df()
        # Another way of creating the DF is accessing by the metric name in the query
        another_df = query_res['proc.cpu.percent'].to_df()
        
        ```
        
        #### Sending data
        
        ```python
        from apptuit import Apptuit, DataPoint
        import time
        import random
        token = "mytoken"
        client = Apptuit(token=token)
        metrics = ["proc.cpu.percent", "node.memory.bytes", "network.send.bytes", "network.receive.bytes", "node.load.avg"]
        tags = {"host": "localhost", "ip": "127.0.0.1"}
        curtime = int(time.time())
        dps = []
        while True:
            curtime = int(time.time())
            for metric in metrics:
                dps.append(DataPoint(metric, tags, curtime, random.random()))
            if len(dps) == 100:
                client.send(dps)
                dps = []
            time.sleep(60)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
