Simplify Parfun imports (finos#40)

* Simplify imports and rename @Parfun in @parallel

Signed-off-by: rafa-be <raphael@noisycamp.com>

* Refactors Parfun API so it can be imported as `import parfun as pf`.

Signed-off-by: rafa-be <raphael@noisycamp.com>

* Fixes typos and wording in documentation's front page.

Signed-off-by: rafa-be <raphael@noisycamp.com>

* Rename the `parfun.collection` module into `parfun.py_list`.

Signed-off-by: rafa-be <raphael@noisycamp.com>

---------

Signed-off-by: rafa-be <raphael@noisycamp.com>

Author: rafa-be

README.md

@@ -28,33 +28,28 @@
 Parfun is a lightweight library providing helpers to **make it easy to write and run a Python function in parallel
 and distributed systems**.
 
-The main feature of the library is its `@parfun` decorator that transparently executes standard Python functions
+The main feature of the library is its `@parallel` decorator that transparently executes standard Python functions
 following the [map-reduce](https://en.wikipedia.org/wiki/MapReduce) pattern:
 
 
 ```Python
 from typing import List
 
-from parfun import parfun
-from parfun.combine.collection import list_concat
-from parfun.partition.api import per_argument
-from parfun.partition.collection import list_by_chunk
+import parfun as pf
 
 
-@parfun(
-    split=per_argument(
-        values=list_by_chunk
+@pf.parallel(
+    split=pf.per_argument(
+        values=pf.py_list.by_chunk
     ),
-    combine_with=list_concat,
+    combine_with=pf.py_list.concat,
 )
 def list_pow(values: List[float], factor: float) -> List[float]:
     return [v**factor for v in values]
 
 
 if __name__ == "__main__":
-    from parfun.entry_point import set_parallel_backend_context
-
-    with set_parallel_backend_context("local_multiprocessing"):  # use a local pool of processes
+    with pf.set_parallel_backend_context("local_multiprocessing"):  # use a local pool of processes
         print(list_pow([1, 2, 3], 2))  # runs in parallel, prints [1, 4, 9]
 ```
 

docs/source/api.rst

@@ -0,0 +1,66 @@
+API
+===
+
+.. autofunction:: parfun.parallel
+
+
+Backend setup
+-------------
+
+.. autofunction:: parfun.set_parallel_backend
+
+.. autofunction:: parfun.set_parallel_backend_context
+
+.. autofunction:: parfun.get_parallel_backend
+
+
+Backend instances
+~~~~~~~~~~~~~~~~~
+
+.. automodule:: parfun.backend.mixins
+    :members:
+
+.. automodule:: parfun.backend.local_single_process
+    :members:
+
+.. automodule:: parfun.backend.local_multiprocessing
+    :members:
+
+.. automodule:: parfun.backend.dask
+    :members:
+
+.. automodule:: parfun.backend.scaler
+    :members:
+
+
+Partitioning
+------------
+
+.. automodule:: parfun.partition.object
+    :members:
+
+.. autofunction:: parfun.all_arguments
+
+.. autofunction:: parfun.multiple_arguments
+
+.. autofunction:: parfun.per_argument
+
+.. autofunction:: parfun.partition.utility.with_partition_size
+
+
+.. _section-lists:
+
+Python lists
+------------
+
+.. automodule:: parfun.py_list
+    :members:
+
+
+.. _section-dataframes:
+
+Pandas dataframes
+-----------------
+
+.. automodule:: parfun.dataframe
+    :members:

docs/source/api/backend.rst

@@ -57,9 +57,6 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ["_static"]
-html_css_files = ["style.css"]
-
 # html_static_path = []
 # html_css_files = []
 

docs/source/api/combine.rst

@@ -1,12 +1,15 @@
 Welcome to Parfun's documentation!
-================================================
+==================================
 
-**Parfun** is a lightweight and user-friendly Python library to assist users in running a Python function in
-parallel.
+**Parfun** is a lightweight and user-friendly Python library designed to help users run Python functions in parallel
+with ease.
 
-With limited knowledge of parallelism and distributed systems, users can significantly speedup their Python code.
+Even with minimal knowledge of parallelism or distributed systems, users can significantly speed up their Python code
+using Parfun.
 
-Parfun supports multiple execution backend, including Python's built-in multiprocessing, Dask and Scaler.
+Parfun supports multiple execution backends, including Python's built-in
+`multiprocessing <https://docs.python.org/3/library/multiprocessing.html>`_, as well as
+`Scaler <https://github.com/Citi/scaler>`_ and `Dask <https://www.dask.org/>`_.
 
 
 Content
@@ -18,7 +21,7 @@ Content
    tutorials/quickstart
    tutorials/examples
    tutorials/implementation_details
-   api/index
+   api
 
 
 Indices and tables