⚰️ Remove unimplemented references to map and applymap (#20)

README.md

@@ -7,7 +7,7 @@
 [![downloads](https://pepy.tech/badge/mapply)](https://pypistats.org/packages/mapply)
 [![black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)
 
-[`mapply`](https://github.com/ddelange/mapply) provides sensible multi-core apply/map/applymap functions for Pandas.
+[`mapply`](https://github.com/ddelange/mapply) provides sensible multi-core apply function for Pandas.
 
 ### mapply vs. pandarallel vs. swifter
 

setup.py

@@ -12,9 +12,7 @@
 def read_requirements(path):
     try:
         with open(path, mode="rt", encoding="utf-8") as fp:
-            return list(
-                filter(None, [line.split("#")[0].strip() for line in fp])  # noqa:C407
-            )
+            return list(filter(None, (line.split("#")[0].strip() for line in fp)))
     except IndexError:
         raise RuntimeError("{} is broken".format(path))
 
@@ -26,7 +24,7 @@ def read_readme(path):
 
 setup(
     name="mapply",
-    description="Sensible multi-core apply/map/applymap functions for Pandas",
+    description="Sensible multi-core apply function for Pandas",
     long_description=read_readme(readme_path),
     long_description_content_type="text/markdown",
     setup_requires=["setuptools_scm"],
@@ -56,6 +54,6 @@ def read_readme(path):
         "Topic :: Software Development :: Libraries :: Python Modules",
         "Topic :: Utilities",
     ],
-    keywords="pandas parallel apply map applymap multicore multiprocessing",
+    keywords="pandas parallel apply multicore multiprocessing multiprocess dill",
     license="MIT",
 )

src/mapply/__init__.py

@@ -31,8 +31,6 @@ def init(
     max_chunks_per_worker: int = DEFAULT_MAX_CHUNKS_PER_WORKER,
     progressbar: bool = True,
     apply_name: str = "mapply",
-    map_name: str = "mmap",
-    applymap_name: str = "mapplymap",
 ):
     """Patch Pandas, adding multi-core methods to PandasObject.
 
@@ -48,19 +46,15 @@ def init(
             n_chunks determined by chunk_size if necessary. Set to 0 to skip this check.
         progressbar: Whether to wrap the chunks in a :meth:`tqdm.auto.tqdm`.
         apply_name: Method name for the patched apply function.
-        map_name: Method name for the patched map function.
-        applymap_name: Method name for the patched applymap function.
     """
     from pandas.core.base import PandasObject
 
-    setattr(
-        PandasObject,
-        apply_name,
-        partialmethod(
-            _mapply,
-            n_workers=n_workers,
-            chunk_size=chunk_size,
-            max_chunks_per_worker=max_chunks_per_worker,
-            progressbar=progressbar,
-        ),
+    apply = partialmethod(
+        _mapply,
+        n_workers=n_workers,
+        chunk_size=chunk_size,
+        max_chunks_per_worker=max_chunks_per_worker,
+        progressbar=progressbar,
     )
+
+    setattr(PandasObject, apply_name, apply)

src/mapply/parallel.py

@@ -20,7 +20,7 @@ def some_heavy_computation(x, power):
 """
 import logging
 from functools import partial
-from typing import Any, Callable, Iterable, Optional
+from typing import Any, Callable, Iterable, Iterator, Optional
 
 import psutil
 from pathos.multiprocessing import ProcessPool
@@ -65,7 +65,7 @@ def multiprocessing_imap(
     progressbar: bool = True,
     args=(),
     **kwargs
-) -> Iterable[Any]:
+) -> Iterator[Any]:
     """Execute func on each element in iterable on n_workers, ensuring order.
 
     Args: