yhat / bandit Goto Github PK

#!/usr/bin/env python
# -*- coding: utf-8 -*- 
"""new_bandit_instance.py
"""
from bandit import Bandit

BANDIT_API_KEY = os.environ['BANDIT_API_KEY']
BANDIT_URL = 'http://00.000.000.000/'

bandit = Bandit("austin", BANDIT_API_KEY, BANDIT_URL)


# newly created bandit instance should have more logical starting values
# Useful example to go by would be pandas
# import json; import pandas as pd; print json.dumps(vars(pd.options), indent=2)

# FOR EXAMPLE...
bandit.job    # should return None
bandit.email  # should return None

# bandit has several `set_{{value}}()` type methods
# therefore it must also have an equal number of `get_{{value}}()` properties
bandit.job.get_status()    # should throw error
bandit.job.get_name()      # should return None
bandit.job.properties      # should return {"id": {{random_id_hash}}}

#!/usr/bin/env python
# -*- coding: utf-8 -*- 
"""classification_algorithm_evaluation_metrics.py
    * Classification Accuracy
    * Logarithmic Loss
    * Area Under ROC Curve
    * Confusion Matrix
    * Classification Report
"""
# Cross Validation Classification Accuracy
import sys
import os
from pandas import read_csv
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_score
from sklearn.linear_model import LogisticRegression
from bandit import Bandit

BANDIT_API_KEY = os.environ['BANDIT_API_KEY']
BANDIT_URL = 'http://00.000.000.000/'

bandit = Bandit("austin", BANDIT_API_KEY, BANDIT_URL)

colnames = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class'] 
df = read_csv('pima-indians-diabetes.data.csv', names=colnames)

feature_names = df.columns[df.columns!='class'].tolist()
target_name = 'class'

bandit.metadata.description = """For classification metrics, the Pima Indians onset of diabetes dataset is used as demon- stration. 
This is a binary classification problem where all of the input variables are numeric.
"""

bandit.metadata.feature_names = feature_names
bandit.metadata.target_name = target_name


X = df.ix[:, feature_names]
y = df[target_name]

# use kfold
kfold = KFold(n_splits=10, random_state=7)

# tell bandit about your cross val method
bandit.metadata.cross_val.method = "kfold"
bandit.metadata.cross_val.n_splits = 10
bandit.metadata.cross_val.random_state = 7

# use logistic regression
model = LogisticRegression()

# tell bandit about your model
bandit.metadata.model_name = "glm-pima-indians-diabetes"

# compute arbitrary statistics about your model performance
results = cross_val_score(model, X, y, cv=kfold, scoring='accuracy') 

# tell bandit about your metrics
# NOTE before i run the next line, metadata.metrics should return None
# print json.dumps(dict(bandit.metadata), indent=2)
# {}
bandit.metadata.metrics.accuracy.mean = results.mean()
bandit.metadata.metrics.accuracy.std = results.std()

# after i tell bandit that i want a substructure called metadata.metrics, this is what it should look like
# print json.dumps(dict(bandit.metadata), indent=2)
# {
#   "metrics": {
#     "std": 0.048410519245671947,
#     "accuracy": {
#       "mean": 0.76951469583048526
#     }
#   }
# }


# bandit should complain if you try to put anything that's NOT json serializable into bandit.metadata

��Requirement already satisfied: pandas==0.19.1 in /root/anaconda/lib/python2.7/site-packages (from -r requirements.txt (line 2))
�=Collecting tweepy==3.2.0 (from -r requirements.txt (line 3))
�0  Downloading tweepy-3.2.0-py2.py3-none-any.whl
��Requirement already satisfied: psycopg2==2.6.2 in /root/anaconda/lib/python2.7/site-packages (from -r requirements.txt (line 4))
��Requirement already satisfied: python-dateutil in /root/anaconda/lib/python2.7/site-packages (from pandas==0.19.1->-r requirements.txt (line 2))
��Requirement already satisfied: pytz>=2011k in /root/anaconda/lib/python2.7/site-packages (from pandas==0.19.1->-r requirements.txt (line 2))
�ICollecting six==1.7.3 (from tweepy==3.2.0->-r requirements.txt (line 3))
�-  Downloading six-1.7.3-py2.py3-none-any.whl
�NCollecting requests==2.4.3 (from tweepy==3.2.0->-r requirements.txt (line 3))
�:  Downloading requests-2.4.3-py2.py3-none-any.whl (459kB)
�WCollecting requests-oauthlib==0.4.1 (from tweepy==3.2.0->-r requirements.txt (line 3))
�;  Downloading requests_oauthlib-0.4.1-py2.py3-none-any.whl
�hCollecting oauthlib>=0.6.2 (from requests-oauthlib==0.4.1->tweepy==3.2.0->-r requirements.txt (line 3))
�,  Downloading oauthlib-2.0.1.tar.gz (122kB)
�1Building wheels for collected packages: oauthlib
�5  Running setup.py bdist_wheel for oauthlib: started
�I  Running setup.py bdist_wheel for oauthlib: finished with status 'done'
�k  Stored in directory: /root/.cache/pip/wheels/e7/4e/b5/c36a97caf4408037eb35aeb1e0a80d95ea0c521a562c3488a3
�nSuccessfully built oauthlib
Installing collected packages: six, requests, oauthlib, requests-oauthlib, tweepy
�*  Found existing installation: six 1.10.0
��    DEPRECATION: Uninstalling a distutils installed project (six) has been deprecated and will be removed in a future version. This is due to the fact that uninstalling a distutils project will only partially uninstall the project.
��    Uninstalling six-1.10.0:
�*      Successfully uninstalled six-1.10.0
�/  Found existing installation: requests 2.11.1
�"    Uninstalling requests-2.11.1:
�/      Successfully uninstalled requests-2.11.1
�dSuccessfully installed oauthlib-2.0.1 requests-2.4.3 requests-oauthlib-0.4.1 six-1.7.3 tweepy-3.2.0
�L[Errno 2] No such file or directory: '/jobs/output-files/tweets-to-load.csv'```

#!/usr/bin/env python
# -*- coding: utf-8 -*- 
"""run_existing_job.py
"""
import sys
import os

from bandit import Bandit

BANDIT_API_KEY = os.environ['BANDIT_API_KEY']
BANDIT_URL = 'http://54.201.192.120/'

bandit = Bandit("austin", BANDIT_API_KEY, BANDIT_URL)
print bandit.run(" hello")    # job which previously completed successfully in the UI

$  python run_existing_job.py
<html>
  <head>
    <title>Bandit</title>
    <link href="/css/bulma.css" rel="stylesheet" />
    <link href="/css/font-awesome.css" rel="stylesheet" />
  </head>
  <body>
    <section class="hero is-bold is-dark is-fullheight">
      <div class="hero-body">
        <div class="container has-text-centered">
          <div class="columns is-vcentered">
            <div class="column is-5">
              <figure class="image is-4by3">
                <img src="http://placehold.it/800x600" alt="Description">
              </figure>
            </div>
            <div class="column is-6 is-offset-1">
              <h1 class="title is-2">
                Whoops!
              </h1>
              <h2 class="subtitle is-4">
                The page you're looking for doesn't exist!
              </h2>
              <br>
              <p class="has-text-centered">
                <a href="/" class="button is-dark is-inverted is-large">
                  <span class="icon">
                    <i class="fa fa-home"></i>
                  </span>
                  <span>Take Me Home</span>
                </a>
              </p>
            </div>
          </div>
        </div>
      </div>

      <!-- Hero footer: will stick at the bottom -->
      <!-- <div class="hero-foot">
        <nav class="tabs is-boxed is-fullwidth">
          <div class="container">
            <ul>
              <li class="is-active"><a>Overview</a></li>
              <li><a>Modifiers</a></li>
              <li><a>Grid</a></li>
              <li><a>Elements</a></li>
              <li><a>Components</a></li>
              <li><a>Layout</a></li>
            </ul>
          </div>
        </nav>
      </div> -->
    </section>
  </body>
</html>

In [40]: bandit.get_jobs()
---------------------------------------------------------------------------
JSONDecodeError                           Traceback (most recent call last)
<ipython-input-40-270c11c54d58> in <module>()
----> 1 bandit.get_jobs()

/usr/local/lib/python2.7/site-packages/bandit/bandit.pyc in get_jobs(self)
     73         """
     74         r = requests.get(self.url + "/jobs", auth=(self.username, self.apikey))
---> 75         jobs = r.json()['jobs']
     76         return [Job(**j) for j in jobs]
     77

/usr/local/lib/python2.7/site-packages/requests/models.pyc in json(self, **kwargs)
    824                     # used.
    825                     pass
--> 826         return complexjson.loads(self.text, **kwargs)
    827
    828     @property

/usr/local/lib/python2.7/site-packages/simplejson/__init__.pyc in loads(s, encoding, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, use_decimal, **kw)
    514             parse_constant is None and object_pairs_hook is None
    515             and not use_decimal and not kw):
--> 516         return _default_decoder.decode(s)
    517     if cls is None:
    518         cls = JSONDecoder

/usr/local/lib/python2.7/site-packages/simplejson/decoder.pyc in decode(self, s, _w, _PY3)
    372         if _PY3 and isinstance(s, binary_type):
    373             s = s.decode(self.encoding)
--> 374         obj, end = self.raw_decode(s)
    375         end = _w(s, end).end()
    376         if end != len(s):

/usr/local/lib/python2.7/site-packages/simplejson/decoder.pyc in raw_decode(self, s, idx, _w, _PY3)
    402             elif ord0 == 0xef and s[idx:idx + 3] == '\xef\xbb\xbf':
    403                 idx += 3
--> 404         return self.scan_once(s, idx=_w(s, idx).end())

JSONDecodeError: Expecting value: line 1 column 1 (char 0)