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357 lines
12 KiB
Python
357 lines
12 KiB
Python
from pydruid.utils.filters import Dimension, Filter
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from datetime import datetime
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from flask import render_template, flash, request
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import pandas as pd
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from pandas_highcharts.core import serialize
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from pydruid.utils import aggregators as agg
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from collections import OrderedDict
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from app import utils
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from wtforms import Form, SelectMultipleField, SelectField, TextField
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import config
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CHART_ARGS = {
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'figsize': (None, 700),
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'title': None,
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'render_to': 'chart',
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}
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class OmgWtForm(Form):
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field_order = (
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'viz_type', 'granularity', 'since', 'group_by', 'limit')
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def fields(self):
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fields = []
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for field in self.field_order:
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if hasattr(self, field):
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obj = getattr(self, field)
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if isinstance(obj, Field):
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fields.append(getattr(self, field))
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return fields
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def form_factory(datasource, form_args=None, extra_fields_dict=None):
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extra_fields_dict = extra_fields_dict or {}
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limits = [0, 5, 10, 25, 50, 100, 500]
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if form_args:
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limit = form_args.get("limit")
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try:
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limit = int(limit)
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if limit not in limits:
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limits.append(limit)
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limits = sorted(limits)
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except:
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pass
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class QueryForm(OmgWtForm):
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viz_type = SelectField(
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'Viz',
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choices=[(k, v.verbose_name) for k, v in viz_types.items()])
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metrics = SelectMultipleField('Metrics', choices=datasource.metrics_combo)
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groupby = SelectMultipleField(
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'Group by', choices=[
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(s, s) for s in datasource.groupby_column_names])
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granularity = TextField('Time Granularity', default="one day")
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since = TextField('Since', default="one day ago")
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until = TextField('Until', default="now")
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limit = SelectField(
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'Limit', choices=[(s, s) for s in limits])
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for i in range(10):
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setattr(QueryForm, 'flt_col_' + str(i), SelectField(
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'Filter 1', choices=[(s, s) for s in datasource.filterable_column_names]))
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setattr(QueryForm, 'flt_op_' + str(i), SelectField(
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'Filter 1', choices=[(m, m) for m in ['in', 'not in']]))
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setattr(QueryForm, 'flt_eq_' + str(i), TextField("Super"))
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for k, v in extra_fields_dict.items():
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setattr(QueryForm, k, v)
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return QueryForm
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class BaseViz(object):
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verbose_name = "Base Viz"
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template = "panoramix/datasource.html"
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def __init__(self, datasource, form_data, view):
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self.datasource = datasource
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self.form_class = self.form_class()
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self.form_data = form_data
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self.metrics = form_data.getlist('metrics') or ['count']
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self.groupby = form_data.getlist('groupby') or []
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self.df = self.bake_query()
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self.view = view
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if self.df is not None:
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self.df.timestamp = pd.to_datetime(self.df.timestamp)
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self.df_prep()
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self.form_prep()
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def form_class(self):
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return form_factory(self.datasource, request.args)
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def query_filters(self):
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args = self.form_data
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# Building filters
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filters = None
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for i in range(1, 10):
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col = args.get("flt_col_" + str(i))
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op = args.get("flt_op_" + str(i))
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eq = args.get("flt_eq_" + str(i))
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if col and op and eq:
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cond = None
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if op == '==':
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cond = Dimension(col)==eq
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elif op == '!=':
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cond = ~(Dimension(col)==eq)
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elif op in ('in', 'not in'):
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fields = []
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splitted = eq.split(',')
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if len(splitted) > 1:
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for s in eq.split(','):
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s = s.strip()
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fields.append(Filter.build_filter(Dimension(col)==s))
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cond = Filter(type="or", fields=fields)
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else:
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cond = Dimension(col)==eq
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if op == 'not in':
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cond = ~cond
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if filters:
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filters = Filter(type="and", fields=[
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Filter.build_filter(cond),
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Filter.build_filter(filters)
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])
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else:
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filters = cond
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return filters
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def query_obj(self):
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ds = self.datasource
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args = self.form_data
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groupby = args.getlist("groupby") or []
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granularity = args.get("granularity", "1 day")
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granularity = utils.parse_human_timedelta(granularity).total_seconds() * 1000
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aggregations = {
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m.metric_name: m.json_obj
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for m in ds.metrics if m.metric_name in self.metrics
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}
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limit = int(
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args.get("limit", config.ROW_LIMIT)) or config.ROW_LIMIT
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since = args.get("since", "1 year ago")
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from_dttm = utils.parse_human_datetime(since)
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if from_dttm > datetime.now():
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from_dttm = datetime.now() - (from_dttm-datetime.now())
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from_dttm = from_dttm.isoformat()
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until = args.get("until", "now")
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to_dttm = utils.parse_human_datetime(until).isoformat()
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if from_dttm >= to_dttm:
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flash("The date range doesn't seem right.", "danger")
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from_dttm = to_dttm # Making them identicial to not raise
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d = {
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'datasource': ds.datasource_name,
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'granularity': {"type": "duration", "duration": granularity},
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'intervals': from_dttm + '/' + to_dttm,
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'dimensions': groupby,
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'aggregations': aggregations,
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'limit_spec': {
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"type": "default",
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"limit": limit,
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"columns": [{
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"dimension": self.metrics[0],
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"direction": "descending",
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}],
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},
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}
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filters = self.query_filters()
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if filters:
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d['filter'] = filters
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return d
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def bake_query(self):
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client = utils.get_pydruid_client()
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client.groupby(**self.query_obj())
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return client.export_pandas()
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def get_query(self):
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client = utils.get_pydruid_client()
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client.groupby(**self.query_obj())
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return client.query_dict
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def df_prep(self, ):
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pass
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def form_prep(self):
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pass
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def render_no_data(self):
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self.template = "panoramix/no_data.html"
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return BaseViz.render(self)
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def render(self, *args, **kwargs):
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form = self.form_class(self.form_data)
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return self.view.render_template(
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self.template, form=form, viz=self, datasource=self.datasource,
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*args, **kwargs)
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class TableViz(BaseViz):
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verbose_name = "Table View"
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template = 'panoramix/viz_table.html'
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def render(self):
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if self.df is None or self.df.empty:
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flash("No data.", "error")
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table = None
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else:
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if self.form_data.get("granularity") == "all":
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del self.df['timestamp']
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table = self.df.to_html(
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classes=[
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'table', 'table-striped', 'table-bordered',
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'table-condensed'],
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index=False)
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return super(TableViz, self).render(table=table)
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class HighchartsViz(BaseViz):
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verbose_name = "Base Highcharts Viz"
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template = 'panoramix/viz_highcharts.html'
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chart_kind = 'line'
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stacked = False
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chart_type = 'not_stock'
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compare = False
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class TimeSeriesViz(HighchartsViz):
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verbose_name = "Time Series - Line Chart"
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chart_kind = "spline"
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chart_type = 'stock'
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def render(self):
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metrics = self.metrics
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df = self.df
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df = df.pivot_table(
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index="timestamp",
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columns=self.groupby,
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values=metrics)
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rolling_periods = request.args.get("rolling_periods")
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rolling_type = request.args.get("rolling_type")
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if rolling_periods and rolling_type:
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if rolling_type == 'mean':
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df = pd.rolling_mean(df, int(rolling_periods))
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chart_js = serialize(
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df, kind=self.chart_kind,
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viz=self,
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compare=self.compare,
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chart_type=self.chart_type, stacked=self.stacked, **CHART_ARGS)
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return super(TimeSeriesViz, self).render(chart_js=chart_js)
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def form_class(self):
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return form_factory(self.datasource, request.args,
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extra_fields_dict={
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'compare': TextField('Period Compare',),
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'rolling_type': SelectField(
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'Rolling',
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choices=[(s, s) for s in ['mean', 'sum', 'std']]),
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'rolling_periods': TextField('Periods',),
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})
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def bake_query(self):
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"""
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Doing a 2 phase query where we limit the number of series.
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"""
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client = utils.get_pydruid_client()
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qry = self.query_obj()
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qry['granularity'] = "all"
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client.groupby(**qry)
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df = client.export_pandas()
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if not df is None:
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dims = qry['dimensions']
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filters = []
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for index, row in df.iterrows():
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fields = []
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for dim in dims:
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f = Filter.build_filter(Dimension(dim) == row[dim])
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fields.append(f)
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if len(fields) > 1:
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filters.append(Filter.build_filter(Filter(type="and", fields=fields)))
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elif fields:
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filters.append(fields[0])
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qry = self.query_obj()
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if filters:
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ff = Filter(type="or", fields=filters)
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qry['filter'] = ff
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del qry['limit_spec']
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client.groupby(**qry)
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return client.export_pandas()
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class TimeSeriesCompareViz(TimeSeriesViz):
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verbose_name = "Time Series - Percent Change"
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compare = 'percent'
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class TimeSeriesAreaViz(TimeSeriesViz):
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verbose_name = "Time Series - Stacked Area Chart"
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stacked=True
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chart_kind = "area"
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class TimeSeriesBarViz(TimeSeriesViz):
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verbose_name = "Time Series - Bar Chart"
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chart_kind = "bar"
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class TimeSeriesStackedBarViz(TimeSeriesViz):
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verbose_name = "Time Series - Stacked Bar Chart"
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chart_kind = "bar"
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stacked = True
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class DistributionBarViz(HighchartsViz):
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verbose_name = "Distribution - Bar Chart"
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chart_kind = "bar"
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def query_obj(self):
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d = super(DistributionBarViz, self).query_obj()
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d['granularity'] = "all"
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return d
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def render(self):
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df = self.df
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df = df.pivot_table(
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index=self.groupby,
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values=self.metrics)
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df = df.sort(self.metrics[0], ascending=False)
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chart_js = serialize(
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df, kind=self.chart_kind, **CHART_ARGS)
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return super(DistributionBarViz, self).render(chart_js=chart_js)
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class DistributionPieViz(HighchartsViz):
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verbose_name = "Distribution - Pie Chart"
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chart_kind = "pie"
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def query_obj(self):
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d = super(DistributionPieViz, self).query_obj()
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d['granularity'] = "all"
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return d
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def render(self):
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df = self.df
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df = df.pivot_table(
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index=self.groupby,
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values=[self.metrics[0]])
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df = df.sort(self.metrics[0], ascending=False)
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chart_js = serialize(
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df, kind=self.chart_kind, **CHART_ARGS)
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return super(DistributionPieViz, self).render(chart_js=chart_js)
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viz_types = OrderedDict([
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['table', TableViz],
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['line', TimeSeriesViz],
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['compare', TimeSeriesCompareViz],
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['area', TimeSeriesAreaViz],
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['bar', TimeSeriesBarViz],
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['stacked_ts_bar', TimeSeriesStackedBarViz],
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['dist_bar', DistributionBarViz],
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['pie', DistributionPieViz],
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])
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