- Use a singleton pool to prevent lengthy restarts of the pool, this also means that arguments for pool size have gone.

- Removed qbar and TqdmMeter.
- Wrap chunked function for better error messages.

README.md

@@ -1,10 +1,12 @@
+[![pytest](https://github.com/wimpomp/parfor/actions/workflows/pytest.yml/badge.svg)](https://github.com/wimpomp/parfor/actions/workflows/pytest.yml)
+
 # Parfor
 Used to parallelize for-loops using parfor in Matlab? This package allows you to do the same in python.
 Take any normal serial but parallelizable for-loop and execute it in parallel using easy syntax.
 Don't worry about the technical details of using the multiprocessing module, race conditions, queues,
 parfor handles all that. 
 
-Tested on linux on python 3.8 and 3.10 and on Windows and OSX on python 3.8.
+Tested on linux, Windows and OSX with python 3.10.
 
 ## Why is parfor better than just using multiprocessing?
 - Easy to use
@@ -27,8 +29,6 @@ of objects that cannot be used. They can be used however, for the iterator argum
 iterations need to be dillable. You might be able to make objects dillable anyhow using `dill.register` or with
 `__reduce__`, `__getstate__`, etc.
 
-On OSX the buffer bar does not work due to limitations of the OS.
-
 ## Arguments
 ### Required:
     fun:      function taking arguments: iteration from  iterable, other arguments defined in args & kwargs
@@ -154,10 +154,7 @@ The function parfor decorates, use it like `map`.
 ## `Chunks`
 Split a long iterator in bite-sized chunks to parallelize
 
-## `Parpool`
+## `ParPool`
 More low-level accessibility to parallel execution. Submit tasks and request the result at any time,
 (although necessarily submit first, then request a specific task), use different functions and function
 arguments for different tasks.
-
-## `TqdmMeter`
-Meter bar, inherited from tqdm, used for displaying buffers.