opsforgeio/cabot

from django.conf import settings
import requests
import logging
import time

graphite_api = settings.GRAPHITE_API
user = settings.GRAPHITE_USER
password = settings.GRAPHITE_PASS
graphite_from = settings.GRAPHITE_FROM
auth = (user, password)


def get_data(target_pattern, mins_to_check=None):

    if mins_to_check:
        _from = '-%dminute' % mins_to_check
    else:
        _from = graphite_from

    resp = requests.get(
        graphite_api + 'render', auth=auth,
        params={
            'target': target_pattern,
            'format': 'json',
            'from': _from,
        }
    )
    resp.raise_for_status()
    return resp.json()


def get_matching_metrics(pattern):
    print 'Getting metrics matching %s' % pattern
    resp = requests.get(
        graphite_api + 'metrics/find/', auth=auth,
        params={
            'query': pattern,
            'format': 'completer'
        },
        headers={
            'accept': 'application/json'
        }
    )
    resp.raise_for_status()
    return resp.json()


def get_all_metrics(limit=None):
    """Grabs all metrics by navigating find API recursively"""
    metrics = []

    def get_leafs_of_node(nodepath):
        for obj in get_matching_metrics(nodepath)['metrics']:
            if int(obj['is_leaf']) == 1:
                metrics.append(obj['path'])
            else:
                get_leafs_of_node(obj['path'])
    get_leafs_of_node('')
    return metrics


def parse_metric(metric, mins_to_check=5, utcnow=None):
    if utcnow is None:
        utcnow = time.time()
    ret = {
        'num_series_with_data': 0,
        'num_series_no_data': 0,
        'error': None,
        'raw': '',
        'series': [],
    }
    try:
        data = get_data(metric, mins_to_check)
    except requests.exceptions.RequestException, e:
        ret['error'] = 'Error getting data from Graphite: %s' % e
        ret['raw'] = ret['error']
        logging.error('Error getting data from Graphite: %s' % e)
        return ret
    all_values = []
    for target in data:
        series = {'values': [
            float(t[0]) for t in target['datapoints'] if validate_datapoint(t, mins_to_check, utcnow)]}
        series["target"] = target["target"]
        all_values.extend(series['values'])
        if series['values']:
            ret['num_series_with_data'] += 1
            series['max'] = max(series['values'])
            series['min'] = min(series['values'])
            series['average_value'] = sum(series['values']) / len(series['values'])
            ret['series'].append(series)
        else:
            ret['num_series_no_data'] += 1
    if all_values:
        ret['average_value'] = sum(all_values) / len(all_values)
    ret['all_values'] = all_values
    ret['raw'] = data
    return ret

def validate_datapoint(datapoint, mins_to_check, utcnow):
    val, timestamp = datapoint
    secs_to_check = 60 * mins_to_check
    if val is None:
        return False
    if timestamp > (utcnow - secs_to_check):
        return True
    else:
        return False