Skip to content

PERF: Cythonize from_nested_dict #33485

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 15 commits into from
Closed

PERF: Cythonize from_nested_dict #33485

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
15 commits
Select commit Hold shift + click to select a range
6d44e55
PERF: Cythonize `from_nested_dict`
Apr 11, 2020
78ae5ab
Merge remote-tracking branch 'upstream/master' into TODO-cythonize
Apr 11, 2020
61c841d
List issues
Apr 11, 2020
1c7ffbb
Added wrappers
Apr 11, 2020
94977b2
Converting the object dict inside the function
Apr 11, 2020
bcb25b9
Avoiding expensive call
Apr 11, 2020
b3ebae6
Merge remote-tracking branch 'upstream/master' into TODO-cythonize
Apr 13, 2020
7dfbca8
Converting the data to builtin dict, in the python space
Apr 13, 2020
c8e515f
Going less offen to the python space
Apr 13, 2020
4829f78
Got rid of unneeded vars
Apr 13, 2020
5faa02b
Better perf if we have nested series
Apr 13, 2020
d349b4f
Assigning the new value into a variable
Apr 13, 2020
4f8afed
Remove the `if` statement
Apr 13, 2020
babaf64
Merge remote-tracking branch 'upstream/master' into TODO-cythonize
Apr 13, 2020
e22fbda
Suggestion by @topper-123
Apr 13, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 17 additions & 0 deletions pandas/_libs/lib.pyx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2526,3 +2526,20 @@ def fast_multiget(dict mapping, ndarray keys, default=np.nan):
output[i] = default

return maybe_convert_objects(output)


@cython.wraparound(False)
@cython.boundscheck(False)
def from_nested_dict(dict data) -> dict:
cdef:
object index, column, value, dict_or_series
dict new_data = {}

for index, dict_or_series in data.items():
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can you keep with using the defaultdict? Should be more performant as it is implemented already in C

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Sure, one thing I do have a concern and it's the return type, if it's a defaultdict, the return type must be an object, unless we return it as a dict, e.g

return dict(new_data)

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Does it make a difference whether typed as object or dict? I think both are just mapped to PyObject anyway so maybe doesn’t matter?

for column, value in dict_or_series.items():
if column in new_data:
new_data[column][index] = value
else:
new_data[column] = {index: value}

return new_data
18 changes: 7 additions & 11 deletions pandas/core/frame.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1265,8 +1265,13 @@ def from_dict(cls, data, orient="columns", dtype=None, columns=None) -> "DataFra
if orient == "index":
if len(data) > 0:
# TODO speed up Series case
if isinstance(list(data.values())[0], (Series, dict)):
data = _from_nested_dict(data)
first_val = next(iter((data.values())), None)
if isinstance(first_val, (Series, dict)):
# If we are dealing with not a builtin dict,
# `collections.defaultdict` for example, we need to convert it
# to a regular dict so Cython will not raise.
data = dict(data) if not type(data) is dict else data
data = lib.from_nested_dict(data)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

If you change the above to

data = dict(data) if not type(data) is dict else data  # convert OrderedDict
data = lib.from_nested_dict(data)

you can change the function interface in lib to def from_nested_dict(dict data) -> dict:, which will simplify things and make it faster too.

else:
data, index = list(data.values()), list(data.keys())
elif orient == "columns":
Expand Down Expand Up @@ -8817,12 +8822,3 @@ def isin(self, values) -> "DataFrame":

ops.add_flex_arithmetic_methods(DataFrame)
ops.add_special_arithmetic_methods(DataFrame)


def _from_nested_dict(data):
# TODO: this should be seriously cythonized
new_data = collections.defaultdict(dict)
for index, s in data.items():
for col, v in s.items():
new_data[col][index] = v
return new_data