From 971848f38b417e6cb71fea59d49bf9bd03477f06 Mon Sep 17 00:00:00 2001
From: llllllllll <joe@quantopian.com>
Date: Tue, 13 Oct 2015 11:22:48 -0400
Subject: [PATCH] MAINT: reshuffle logic in from_blaze to make the control flow
 easier

---
 zipline/pipeline/loaders/blaze.py | 59 +++++++++++++++++++++++--------
 1 file changed, 44 insertions(+), 15 deletions(-)

diff --git a/zipline/pipeline/loaders/blaze.py b/zipline/pipeline/loaders/blaze.py
index 57e0ad90..eec03fea 100644
--- a/zipline/pipeline/loaders/blaze.py
+++ b/zipline/pipeline/loaders/blaze.py
@@ -428,6 +428,42 @@ def _get_deltas(expr, deltas, no_deltas_rule):
     return None
 
 
+def _ensure_timestamp_field(dataset_expr, deltas):
+    """Verify that the baseline and deltas expressions have a timestamp field.
+
+    If there is not a ``TS_FIELD_NAME`` on either of the expressions, it will
+    be copied from the ``AD_FIELD_NAME``. If one is provided, then we will
+    verify that it is the correct dshape.
+
+    Parameters
+    ----------
+    dataset_expr : Expr
+        The baseline expression.
+    deltas : Expr or None
+        The deltas expression if any was provided.
+
+    Returns
+    -------
+    dataset_expr, deltas : Expr
+        The new baseline and deltas expressions to use.
+    """
+    measure = dataset_expr.dshape.measure
+    if TS_FIELD_NAME not in measure.names:
+        dataset_expr = bz.transform(
+            dataset_expr,
+            **{TS_FIELD_NAME: dataset_expr[AD_FIELD_NAME]}
+        )
+        if deltas is not None:
+            deltas = bz.transform(
+                deltas,
+                **{TS_FIELD_NAME: deltas[AD_FIELD_NAME]}
+            )
+    else:
+        _check_datetime_field(TS_FIELD_NAME, measure)
+
+    return dataset_expr, deltas
+
+
 @expect_element(no_deltas_rule=_valid_no_deltas_rules)
 def from_blaze(expr,
                deltas='auto',
@@ -508,9 +544,11 @@ def from_blaze(expr,
                     break
             rename = expr._name
             expr = expr._child
-        expr = expr.relabel({rename: single_column})
+        dataset_expr = expr.relabel({rename: single_column})
+    else:
+        dataset_expr = expr
 
-    measure = expr.dshape.measure
+    measure = dataset_expr.dshape.measure
     if not isrecord(measure) or AD_FIELD_NAME not in measure.names:
         raise TypeError(
             "The dataset must be a collection of records with at least an"
@@ -521,16 +559,7 @@ def from_blaze(expr,
             ),
         )
     _check_datetime_field(AD_FIELD_NAME, measure)
-
-    if TS_FIELD_NAME not in measure.names:
-        expr = bz.transform(expr, **{TS_FIELD_NAME: expr[AD_FIELD_NAME]})
-        if deltas is not None:
-            deltas = bz.transform(
-                deltas,
-                **{TS_FIELD_NAME: deltas[AD_FIELD_NAME]}
-            )
-    else:
-        _check_datetime_field(TS_FIELD_NAME, measure)
+    dataset_expr, deltas = _ensure_timestamp_field(dataset_expr, deltas)
 
     if deltas is not None and (sorted(deltas.dshape.measure.fields) !=
                                sorted(measure.fields)):
@@ -542,14 +571,14 @@ def from_blaze(expr,
         )
 
     # Ensure that we have a data resource to execute the query against.
-    _check_resources('expr', expr, resources)
+    _check_resources('dataset_expr', dataset_expr, resources)
     _check_resources('deltas', deltas, resources)
 
     # Create or retrieve the Pipeline API dataset.
-    ds = new_dataset(expr, deltas)
+    ds = new_dataset(dataset_expr, deltas)
     # Register our new dataset with the loader.
     (loader if loader is not None else global_loader)[ds] = ExprData(
-        expr,
+        dataset_expr,
         deltas,
         resources,
     )