Updating the code to adapt to changes in backend

HISTORY.rst

@@ -2,6 +2,7 @@
 
 History
 -------
+
 4.6.0 (2016-04-10)
 ~~~~~~~~~~~~~~~~~~
 

bigml/__init__.py

@@ -1 +1 @@
-__version__ = '4.5.4'
+__version__ = '4.6.0'

bigml/api.py

@@ -86,7 +86,7 @@
     SAMPLE_PATH, SAMPLE_RE, CORRELATION_PATH, CORRELATION_RE,
     STATISTICAL_TEST_PATH, STATISTICAL_TEST_RE,
     LOGISTIC_REGRESSION_PATH, LOGISTIC_REGRESSION_RE, ASSOCIATION_PATH,
-    ASSOCIATION_RE, ASSOCIATION_SET_PATH, ASSOCIATION_SET_RE
+    ASSOCIATION_RE, ASSOCIATION_SET_PATH, ASSOCIATION_SET_RE,
     SCRIPT_PATH, SCRIPT_RE,
     EXECUTION_PATH, EXECUTION_RE, LIBRARY_PATH, LIBRARY_RE)
 
@@ -99,7 +99,7 @@
     get_status, check_resource, http_ok, get_project_id, get_sample_id,
     get_correlation_id, get_statistical_test_id, get_logistic_regression_id,
     get_association_id, get_association_set_id, get_script_id,
-    get_execution_id, get_library_id))
+    get_execution_id, get_library_id)
 
 
 # Map status codes to labels

bigml/constants.py

@@ -42,6 +42,9 @@
 LOGISTIC_REGRESSION_PATH = 'logisticregression'
 ASSOCIATION_PATH = 'association'
 ASSOCIATION_SET_PATH = 'associationset'
+SCRIPT_PATH = 'script'
+EXECUTION_PATH = 'execution'
+LIBRARY_PATH = 'library'
 
 
 # Resource Ids patterns
@@ -81,6 +84,12 @@
     (ASSOCIATION_PATH, ID_PATTERN, ASSOCIATION_PATH, SHARED_PATTERN))
 ASSOCIATION_SET_RE = re.compile(r'^%s/%s$' % \
     (ASSOCIATION_SET_PATH, ID_PATTERN))
+SCRIPT_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
+    (SCRIPT_PATH, ID_PATTERN, SCRIPT_PATH, SHARED_PATTERN))
+EXECUTION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
+    (EXECUTION_PATH, ID_PATTERN, EXECUTION_PATH, SHARED_PATTERN))
+LIBRARY_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
+    (LIBRARY_PATH, ID_PATTERN, LIBRARY_PATH, SHARED_PATTERN))
 
 RESOURCE_RE = {
     SOURCE_PATH: SOURCE_RE,
@@ -102,7 +111,10 @@
     STATISTICAL_TEST_PATH: STATISTICAL_TEST_RE,
     LOGISTIC_REGRESSION_PATH: LOGISTIC_REGRESSION_RE,
     ASSOCIATION_PATH: ASSOCIATION_RE,
-    ASSOCIATION_SET_PATH: ASSOCIATION_SET_RE}
+    ASSOCIATION_SET_PATH: ASSOCIATION_SET_RE,
+    SCRIPT_PATH: SCRIPT_RE,
+    EXECUTION_PATH: EXECUTION_RE,
+    LIBRARY_PATH: LIBRARY_RE}
 
 
 RENAMED_RESOURCES = {

bigml/executionhandler.py

@@ -31,8 +31,8 @@
 from bigml.resourcehandler import (check_resource_type,
                                    get_execution_id, get_resource_type,
                                    get_script_id, check_resource)
-from bigml.resourcehandler import (EXECUTION_PATH, SCRIPT_PATH,
-                                   TINY_RESOURCE)
+from bigml.constants import (EXECUTION_PATH, SCRIPT_PATH,
+                             TINY_RESOURCE)
 
 
 class ExecutionHandler(ResourceHandler):

bigml/fields.py

@@ -44,6 +44,7 @@
 import sys
 import json
 
+
 from bigml.util import invert_dictionary, python_map_type, find_locale
 from bigml.util import DEFAULT_LOCALE
 from bigml.api import get_resource_type
@@ -70,8 +71,12 @@
 UPDATABLE_HEADERS = {"field name": "name",
                      "field label": "label",
                      "field description": "description",
+<<<<<<< HEAD
                      "field type": "optype",
                      "preferred": "preferred"}
+=======
+                     "field type": "optype"}
+>>>>>>> Updating the code to adapt to changes in backend
 
 ITEM_SINGULAR = {u"categories": u"category"}
 
@@ -131,16 +136,34 @@ def get_fields_structure(resource, errors=False):
             result = result + (field_errors,)
         return result
     else:
+<<<<<<< HEAD
         return (None, None, None, None, None) if errors else \
             (None, None, None, None)
+=======
+
+        return None, None, None, None, None if errors else \
+            None, None, None, None
+
+
+def text_encode(text):
+    """Encoding text to be written in a utf-8 file
+
+    """
+    if isinstance(text, basestring):
+        return text.encode("utf-8")
+    return text
+>>>>>>> Updating the code to adapt to changes in backend
 
 
 def attribute_summary(attribute_value, item_type, limit=None):
     """Summarizes the information in fields attributes where content is
        written as an array of arrays like tag_cloud, items, etc.
     """
+<<<<<<< HEAD
     if attribute_value is None:
         return None
+=======
+>>>>>>> Updating the code to adapt to changes in backend
     items = [u"%s (%s)" % (item, instances) for
              item, instances in attribute_value]
     items_length = len(items)
@@ -588,7 +611,6 @@ def new_fields_structure(self, csv_attributes_file=None,
                         self.field_id(int(field_attributes[0]))
                     new_fields_structure[field_id] = \
                         dict(zip(headers, field_attributes[1: 6]))
-
             except ValueError:
                 raise ValueError("The first column should contain either the"
                                  " column or ID of the fields. Failed to find"

bigml/libraryhandler.py

@@ -31,7 +31,7 @@
 from bigml.resourcehandler import (check_resource_type,
                                    get_library_id, get_resource_type,
                                    check_resource)
-from bigml.resourcehandler import (LIBRARY_PATH, TINY_RESOURCE)
+from bigml.constants import LIBRARY_PATH, TINY_RESOURCE
 
 
 class LibraryHandler(ResourceHandler):

bigml/logistic.py

@@ -137,7 +137,9 @@ def __init__(self, logistic_regression, api=None):
             self.input_fields = logistic_regression.get("input_fields", [])
             self.dataset_field_types = logistic_regression.get(
                 "dataset_field_types", {})
-            objective_field = logistic_regression['objective_fields']
+            objective_field = logistic_regression['objective_fields'] if \
+                logistic_regression['objective_fields'] else \
+                logistic_regression['objective_field']
         except KeyError:
             raise ValueError("Failed to find the logistic regression expected "
                              "JSON structure. Check your arguments.")

bigml/resourcehandler.py

@@ -28,104 +28,6 @@
 from bigml.bigmlconnection import BigMLConnection
 
 
-# Basic resources
-SOURCE_PATH = 'source'
-DATASET_PATH = 'dataset'
-MODEL_PATH = 'model'
-PREDICTION_PATH = 'prediction'
-EVALUATION_PATH = 'evaluation'
-ENSEMBLE_PATH = 'ensemble'
-BATCH_PREDICTION_PATH = 'batchprediction'
-CLUSTER_PATH = 'cluster'
-CENTROID_PATH = 'centroid'
-BATCH_CENTROID_PATH = 'batchcentroid'
-ANOMALY_PATH = 'anomaly'
-ANOMALY_SCORE_PATH = 'anomalyscore'
-BATCH_ANOMALY_SCORE_PATH = 'batchanomalyscore'
-PROJECT_PATH = 'project'
-SAMPLE_PATH = 'sample'
-CORRELATION_PATH = 'correlation'
-STATISTICAL_TEST_PATH = 'statisticaltest'
-SCRIPT_PATH = 'script'
-EXECUTION_PATH = 'execution'
-LIBRARY_PATH = 'library'
-
-# Resource Ids patterns
-ID_PATTERN = '[a-f0-9]{24}'
-SHARED_PATTERN = '[a-zA-Z0-9]{24,30}'
-SOURCE_RE = re.compile(r'^%s/%s$' % (SOURCE_PATH, ID_PATTERN))
-# public resources: model and dataset
-# shared resources: all except sources
-DATASET_RE = re.compile(r'^(public/)?%s/%s$|^shared/%s/%s$' % (
-    DATASET_PATH, ID_PATTERN, DATASET_PATH, SHARED_PATTERN))
-MODEL_RE = re.compile(r'^(public/)?%s/%s$|^shared/%s/%s$' % (
-    MODEL_PATH, ID_PATTERN, MODEL_PATH, SHARED_PATTERN))
-#
-PREDICTION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    PREDICTION_PATH, ID_PATTERN, PREDICTION_PATH, SHARED_PATTERN))
-EVALUATION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    EVALUATION_PATH, ID_PATTERN, EVALUATION_PATH, SHARED_PATTERN))
-ENSEMBLE_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    ENSEMBLE_PATH, ID_PATTERN, ENSEMBLE_PATH, SHARED_PATTERN))
-BATCH_PREDICTION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    BATCH_PREDICTION_PATH, ID_PATTERN, BATCH_PREDICTION_PATH, SHARED_PATTERN))
-CLUSTER_RE = re.compile(r'^%s/%s$|^shared/%s/%s$' % (
-    CLUSTER_PATH, ID_PATTERN, CLUSTER_PATH, SHARED_PATTERN))
-CENTROID_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    CENTROID_PATH, ID_PATTERN, CENTROID_PATH, SHARED_PATTERN))
-BATCH_CENTROID_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    BATCH_CENTROID_PATH, ID_PATTERN, BATCH_CENTROID_PATH, SHARED_PATTERN))
-ANOMALY_RE = re.compile(r'^(public/)?%s/%s$|^shared/%s/%s$' % (
-    ANOMALY_PATH, ID_PATTERN, ANOMALY_PATH, SHARED_PATTERN))
-ANOMALY_SCORE_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    ANOMALY_SCORE_PATH, ID_PATTERN, ANOMALY_SCORE_PATH, SHARED_PATTERN))
-BATCH_ANOMALY_SCORE_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    BATCH_ANOMALY_SCORE_PATH, ID_PATTERN,
-    BATCH_ANOMALY_SCORE_PATH, SHARED_PATTERN))
-PROJECT_RE = re.compile(r'^%s/%s$' % (PROJECT_PATH, ID_PATTERN))
-SAMPLE_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    SAMPLE_PATH, ID_PATTERN, SAMPLE_PATH, SHARED_PATTERN))
-CORRELATION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % (
-    CORRELATION_PATH, ID_PATTERN, CORRELATION_PATH, SHARED_PATTERN))
-STATISTICAL_TEST_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
-    (STATISTICAL_TEST_PATH, ID_PATTERN, STATISTICAL_TEST_PATH, SHARED_PATTERN))
-SCRIPT_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
-    (SCRIPT_PATH, ID_PATTERN, SCRIPT_PATH, SHARED_PATTERN))
-EXECUTION_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
-    (EXECUTION_PATH, ID_PATTERN, EXECUTION_PATH, SHARED_PATTERN))
-LIBRARY_RE = re.compile(r'^%s/%s|^shared/%s/%s$' % \
-    (LIBRARY_PATH, ID_PATTERN, LIBRARY_PATH, SHARED_PATTERN))
-
-RESOURCE_RE = {
-    'source': SOURCE_RE,
-    'dataset': DATASET_RE,
-    'model': MODEL_RE,
-    'prediction': PREDICTION_RE,
-    'evaluation': EVALUATION_RE,
-    'ensemble': ENSEMBLE_RE,
-    'batchprediction': BATCH_PREDICTION_RE,
-    'cluster': CLUSTER_RE,
-    'centroid': CENTROID_RE,
-    'batchcentroid': BATCH_CENTROID_RE,
-    'anomaly': ANOMALY_RE,
-    'anomalyscore': ANOMALY_SCORE_RE,
-    'batchanomalyscore': BATCH_ANOMALY_SCORE_RE,
-    'project': PROJECT_RE,
-    'sample': SAMPLE_RE,
-    'correlation': CORRELATION_RE,
-    'statisticaltest': STATISTICAL_TEST_RE,
-    'script': SCRIPT_RE,
-    'execution': EXECUTION_RE,
-    'library': LIBRARY_RE}
-
-
-RENAMED_RESOURCES = {
-    'batchprediction': 'batch_prediction',
-    'batchcentroid': 'batch_centroid',
-    'anomalyscore': 'anomaly_score',
-    'batchanomalyscore': 'batch_anomaly_score',
-    'statisticaltest': 'statistical_test'
-}
 
 NO_QS = [c.EVALUATION_RE, c.PREDICTION_RE, c.BATCH_PREDICTION_RE,
          c.CENTROID_RE, c.BATCH_CENTROID_RE, c.ANOMALY_SCORE_RE,
@@ -364,21 +266,21 @@ def get_script_id(script):
     """Returns a script/id.
 
     """
-    return get_resource(SCRIPT_RE, script)
+    return get_resource(c.SCRIPT_PATH, script)
 
 
 def get_execution_id(execution):
     """Returns a execution/id.
 
     """
-    return get_resource(EXECUTION_RE, execution)
+    return get_resource(c.EXECUTION_PATH, execution)
 
 
 def get_library_id(library):
     """Returns a library/id.
 
     """
-    return get_resource(LIBRARY_RE, library)
+    return get_resource(c.LIBRARY_PATH, library)
 
 
 def get_resource_id(resource):

bigml/scripthandler.py

@@ -31,8 +31,8 @@
 from bigml.resourcehandler import (check_resource_type,
                                    get_script_id, get_resource_type,
                                    get_dataset_id, check_resource)
-from bigml.resourcehandler import (SCRIPT_PATH, DATASET_PATH,
-                                   TINY_RESOURCE)
+from bigml.constants import (SCRIPT_PATH, DATASET_PATH,
+                             TINY_RESOURCE)
 
 
 class ScriptHandler(ResourceHandler):

bigml/tests/inspect_model_steps.py

@@ -65,6 +65,12 @@ def i_check_the_model_summary_with(step, file):
     output = io.BytesIO()
     world.local_model.summarize(out=output)
     world.output = output.getvalue()
+    if not os.path.exists('./tmp'):
+        os.mkdir('./tmp')
+    with open('./tmp/summary.txt', "w") as rules_file:
+        rules_file.write(world.output)
+
+
     i_check_if_the_output_is_like_expected_file(step, file)
 
 

bigml/tests/test_28_execution.py → bigml/tests/test_30_execution.py

@@ -50,11 +50,11 @@ def test_scenario1(self):
 
                 Examples:
                 | source_code      | time_1  | time_2  | time_3  | param | param_value
-                | (+ 1 1)          | 10      | 10      | 10      | name  | my execution
+                | (+ 1 1)          | 10      | 10      | 50      | name  | my execution
         """
         print self.test_scenario1.__doc__
         examples = [
-            ['(+ 1 1)', '10', '10', '10', 'name', 'my execution']]
+            ['(+ 1 1)', '10', '10', '50', 'name', 'my execution']]
         for example in examples:
             print "\nTesting with:\n", example
             script_create.i_create_a_script(self, example[0])
@@ -80,11 +80,11 @@ def test_scenario2(self):
 
                 Examples:
                 | source_code      | time_1  | time_2  | time_3  | param | param_value
-                | (+ 1 1)          | 10      | 10      | 10      | name  | my execution
+                | (+ 1 1)          | 10      | 10      | 50      | name  | my execution
         """
         print self.test_scenario2.__doc__
         examples = [
-            ['(+ 1 1)', '10', '10', '10', 'name', 'my execution']]
+            ['(+ 1 1)', '10', '10', '50', 'name', 'my execution']]
         for example in examples:
             print "\nTesting with:\n", example
             script_create.i_create_a_script(self, example[0])

bigml/tests/world.py

@@ -48,7 +48,7 @@
     'correlation',
     'statisticaltest',
     'logisticregression',
-    'association'
+    'association',
     'script',
     'execution',
     'library'
@@ -60,9 +60,10 @@
     'anomalyscore': 'anomaly_scores',
     'batchanomalyscore': 'batch_anomaly_scores',
     'statisticaltest': 'statistical_tests',
-    'logisticregression': 'logistic_regressions'
+    'logisticregression': 'logistic_regressions',
     'library': 'libraries'
 }
+
 TRANSLATED_RESOURCES = {
     'batchprediction': 'batch_prediction',
     'batchcentroid': 'batch_centroid',