Fix chrisdev#63 and add compress argument to read_frame

django_pandas/io.py

@@ -1,6 +1,11 @@
+from collections.abc import Mapping
+
 import pandas as pd
+from pandas.core.index import _ensure_index
+from pandas.core.frame import _to_arrays, _arrays_to_mgr
 from .utils import update_with_verbose, get_related_model
 import django
+import numpy as np
 
 
 def to_fields(qs, fieldnames):
@@ -32,14 +37,82 @@ def is_values_queryset(qs):
         return qs._iterable_class == django.db.models.query.ValuesIterable
 
 
+_FIELDS_TO_DTYPES = {
+    django.db.models.fields.AutoField:                  np.int32,
+    django.db.models.fields.BigAutoField:               np.int64,
+    django.db.models.fields.BigIntegerField:            np.int64,
+    django.db.models.fields.BinaryField:                np.bytes_,
+    django.db.models.fields.BooleanField:               np.bool_,
+    django.db.models.fields.CharField:                  np.unicode_,
+    django.db.models.fields.DateField:                  np.datetime64,
+    django.db.models.fields.DateTimeField:              np.datetime64,
+    django.db.models.fields.DecimalField:               object,
+    django.db.models.fields.DurationField:              np.timedelta64,
+    django.db.models.fields.EmailField:                 np.unicode_,
+    django.db.models.fields.FilePathField:              np.unicode_,
+    django.db.models.fields.FloatField:                 np.float64,
+    django.db.models.fields.GenericIPAddressField:      np.unicode_,
+    django.db.models.fields.IntegerField:               np.int32,
+    django.db.models.fields.NullBooleanField:           object, # bool(None) is False
+    django.db.models.fields.PositiveIntegerField:       np.uint32,
+    django.db.models.fields.PositiveSmallIntegerField:  np.uint16,
+    django.db.models.fields.SlugField:                  np.unicode_,
+    django.db.models.fields.TextField:                  np.unicode_,
+    django.db.models.fields.TimeField:                  np.datetime64,
+    django.db.models.fields.URLField:                   np.unicode_,
+    django.db.models.fields.UUIDField:                  object,
+    django.db.models.fields.SmallIntegerField:          np.int16,
+}
+
+
+def _get_dtypes(fields_to_dtypes, fields):
+    """Infer NumPy dtypes from field types among those named in fieldnames.
+
+    Returns a list of (fieldname, NumPy dtype) pairs. Read about NumPy dtypes
+    here [#]_ and here [#]_. The returned list can be passed to ``numpy.array``
+    in ``read_frame``.
+
+    Parameters
+    ----------
+
+    field_to_dtypes : mapping
+        A (potentially empty) mapping of Django field classes to NumPy dtypes.
+        This mapping overrides the defualts from ``_FIELDS_TO_DTYPES``. The
+        back-up default dtype is ``object`` for unfamiliar field classes.
+
+    fields : list of Django field class instances
+        They must correspond in order to the columns of the dataframe that
+        ``read_frame`` is building.
+
+    .. [#] https://docs.scipy.org/doc/numpy/user/basics.types.html
+    .. [#] https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
+    """
+    dtypes = []
+    f2d = _FIELDS_TO_DTYPES.copy()
+    f2d.update(fields_to_dtypes)
+    for field in fields:
+        # Find the lowest subclass mong the keys of f2d
+        t, dtype = object, object
+        for k, v in f2d.items():
+            if isinstance(field, k) and issubclass(k, t):
+                t = k
+                dtype = v
+        dtypes.append((field.name, dtype))
+    return dtypes
+
+
 def read_frame(qs, fieldnames=(), index_col=None, coerce_float=False,
-               verbose=True):
+               verbose=True, compress=False):
     """
     Returns a dataframe from a QuerySet
 
     Optionally specify the field names/columns to utilize and
     a field as the index
 
+    This function uses the QuerySet's ``iterator`` method, so it does not
+    populate the QuerySet's cache. This is more memory efficient in the typical
+    case where you do not use the QuerySet after ``read_frame``.
+
     Parameters
     ----------
 
@@ -58,13 +131,31 @@ def read_frame(qs, fieldnames=(), index_col=None, coerce_float=False,
     coerce_float : boolean, default False
         Attempt to convert values to non-string, non-numeric data (like
         decimal.Decimal) to floating point, useful for SQL result sets
+        Does not work with ``compress``.
 
     verbose:  boolean If  this is ``True`` then populate the DataFrame with the
                 human readable versions of any foreign key fields else use
                 the primary keys values.
                 The human readable version of the foreign key field is
                 defined in the ``__unicode__`` or ``__str__``
                 methods of the related class definition
+
+    compress: boolean or a mapping, default False
+        If a true value, infer NumPy data types [#]_ for Pandas dataframe
+        columns from the corresponding Django field types. For example, Django's
+        built in ``SmallIntgerField`` is cast to NumPy's ``int16``. If
+        ``compress`` is a mapping (e.g., a ``dict``), it should be a mapping
+        with Django field subclasses as keys and  NumPy dtypes [#]_ as values.
+        This mapping overrides the defualts for the field classes appearing in
+        the mapping. However, the inference is based on the field subclass
+        lowest on a chain of subclasses, that is, in order of inheritence.
+        To override ``SmallIntegerField`` it is therefore not sufficient to
+        override ``IntegerField``. Careful of setting ``compress={}`` because
+        ``{}`` is a false value in Python, which would cause ``read_frame``
+        not to compress columns.
+
+    .. [#] https://docs.scipy.org/doc/numpy/user/basics.types.html
+    .. [#] https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
    """
 
     if fieldnames:
@@ -108,13 +199,23 @@ def read_frame(qs, fieldnames=(), index_col=None, coerce_float=False,
         fields = qs.model._meta.fields
         fieldnames = [f.name for f in fields]
 
-    if is_values_queryset(qs):
-        recs = list(qs)
-    else:
-        recs = list(qs.values_list(*fieldnames))
-
-    df = pd.DataFrame.from_records(recs, columns=fieldnames,
-                                   coerce_float=coerce_float)
+    if not is_values_queryset(qs):
+        qs = qs.values_list(*fieldnames)
+
+    # Goal is to avoid instantiating the NumPy columns with wider dtypes than
+    # compress needs. If pandas.DataFrame.from_records accepted a dtype
+    # argument, we would just call that constructor. The following several lines
+    # do the same thing.
+    columns = _ensure_index(fieldnames)
+    values = list(qs.iterator()) # Potentially the hardest step
+    if compress:
+        if not isinstance(compress, Mapping):
+            compress = {}
+        values = np.array(values, dtype=_get_dtypes(compress, fields))
+    df = pd.DataFrame(_arrays_to_mgr(
+        arrays=_to_arrays(
+            data=values, columns=columns, coerce_float=coerce_float)[0],
+        arr_names=columns, index=None, columns=columns))
 
     if verbose:
         update_with_verbose(df, fieldnames, fields)

django_pandas/tests/models.py

@@ -9,7 +9,7 @@ class MyModel(models.Model):
     col1 = models.IntegerField()
     col2 = models.FloatField(null=True)
     col3 = models.FloatField(null=True)
-    col4 = models.IntegerField()
+    col4 = models.SmallIntegerField()
 
     def __str__(self):
         return "{} {} {} {}".format(

django_pandas/tests/test_io.py

@@ -46,6 +46,16 @@ def test_basic(self):
         df1 = read_frame(qs, ['col1', 'col2'])
         self.assertEqual(df1.shape, (qs.count(), 2))
 
+    def test_compress(self):
+        qs = MyModel.objects.all()
+        df = read_frame(qs, compress=True)
+
+        # Test automatic inference of dtypes
+        self.assertIs(df.col1.dtype, np.dtype('int32'))
+        self.assertIs(df.col2.dtype, np.dtype('float_'))
+        self.assertIs(df.col3.dtype, np.dtype('float_'))
+        self.assertIs(df.col4.dtype, np.dtype('int16'))
+
     def test_values(self):
         qs = MyModel.objects.all()
         qs = qs.extra(select={"ecol1": "col1+1"})