/
evaluationhandler.py
110 lines (88 loc) · 3.81 KB
/
evaluationhandler.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
# -*- coding: utf-8 -*-
#!/usr/bin/env python
#
# Copyright 2014-2016 BigML
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""Base class for evaluations' REST calls
https://bigml.com/developers/evaluations
"""
try:
import simplejson as json
except ImportError:
import json
from bigml.resourcehandler import ResourceHandler
from bigml.resourcehandler import (check_resource_type,
get_evaluation_id)
from bigml.constants import EVALUATION_PATH, MODEL_PATH, ENSEMBLE_PATH
class EvaluationHandler(ResourceHandler):
"""This class is used by the BigML class as
a mixin that provides the REST calls models. It should not
be instantiated independently.
"""
def __init__(self):
"""Initializes the EvaluationHandler. This class is intended to be
used as a mixin on ResourceHandler, that inherits its
attributes and basic method from BigMLConnection, and must not be
instantiated independently.
"""
self.evaluation_url = self.url + EVALUATION_PATH
def create_evaluation(self, model, dataset,
args=None, wait_time=3, retries=10):
"""Creates a new evaluation.
"""
create_args = {}
if args is not None:
create_args.update(args)
model_types = [ENSEMBLE_PATH, MODEL_PATH]
origin_resources_checked = self.check_origins(
dataset, model, create_args, model_types=model_types,
wait_time=wait_time, retries=retries)
if origin_resources_checked:
body = json.dumps(create_args)
return self._create(self.evaluation_url, body)
def get_evaluation(self, evaluation):
"""Retrieves an evaluation.
The evaluation parameter should be a string containing the
evaluation id or the dict returned by create_evaluation.
As evaluation is an evolving object that is processed
until it reaches the FINISHED or FAULTY state, the function will
return a dict that encloses the evaluation values and state info
available at the time it is called.
"""
check_resource_type(evaluation, EVALUATION_PATH,
message="An evaluation id is needed.")
evaluation_id = get_evaluation_id(evaluation)
if evaluation_id:
return self._get("%s%s" % (self.url, evaluation_id))
def list_evaluations(self, query_string=''):
"""Lists all your evaluations.
"""
return self._list(self.evaluation_url, query_string)
def update_evaluation(self, evaluation, changes):
"""Updates an evaluation.
"""
check_resource_type(evaluation, EVALUATION_PATH,
message="An evaluation id is needed.")
evaluation_id = get_evaluation_id(evaluation)
if evaluation_id:
body = json.dumps(changes)
return self._update("%s%s" % (self.url, evaluation_id), body)
def delete_evaluation(self, evaluation):
"""Deletes an evaluation.
"""
check_resource_type(evaluation, EVALUATION_PATH,
message="An evaluation id is needed.")
evaluation_id = get_evaluation_id(evaluation)
if evaluation_id:
return self._delete("%s%s" % (self.url, evaluation_id))