parallel in win notebook

fastcore/_nbdev.py

@@ -182,10 +182,11 @@
          "threaded": "03a_parallel.ipynb",
          "startthread": "03a_parallel.ipynb",
          "set_num_threads": "03a_parallel.ipynb",
-         "check_parallel_num": "03a_parallel.ipynb",
+         "parallelable": "03a_parallel.ipynb",
          "ThreadPoolExecutor": "03a_parallel.ipynb",
          "ProcessPoolExecutor": "03a_parallel.ipynb",
          "parallel": "03a_parallel.ipynb",
+         "add_one": "03a_parallel.ipynb",
          "run_procs": "03a_parallel.ipynb",
          "parallel_gen": "03a_parallel.ipynb",
          "url_default_headers": "03b_net.ipynb",

fastcore/parallel.py

@@ -1,7 +1,7 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/03a_parallel.ipynb (unless otherwise specified).
 
-__all__ = ['threaded', 'startthread', 'set_num_threads', 'check_parallel_num', 'ThreadPoolExecutor',
-           'ProcessPoolExecutor', 'parallel', 'run_procs', 'parallel_gen']
+__all__ = ['threaded', 'startthread', 'set_num_threads', 'parallelable', 'ThreadPoolExecutor', 'ProcessPoolExecutor',
+           'parallel', 'add_one', 'run_procs', 'parallel_gen']
 
 # Cell
 from .imports import *
@@ -58,12 +58,13 @@ def _call(lock, pause, n, g, item):
     return g(item)
 
 # Cell
-def check_parallel_num(param_name, num_workers):
-    if sys.platform == "win32" and IN_NOTEBOOK and num_workers > 0:
+def parallelable(param_name, num_workers, f=None):
+    f_in_main = f == None or sys.modules[f.__module__].__name__ == "__main__"
+    if sys.platform == "win32" and IN_NOTEBOOK and num_workers > 0 and f_in_main:
         print("Due to IPython and Windows limitation, python multiprocessing isn't available now.")
-        print(f"So `{param_name}` is changed to 0 to avoid getting stuck")
-        num_workers = 0
-    return num_workers
+        print(f"So `{param_name}` has to be changed to 0 to avoid getting stuck")
+        return False
+    return True
 
 # Cell
 class ThreadPoolExecutor(concurrent.futures.ThreadPoolExecutor):
@@ -88,13 +89,16 @@ class ProcessPoolExecutor(concurrent.futures.ProcessPoolExecutor):
     "Same as Python's ProcessPoolExecutor, except can pass `max_workers==0` for serial execution"
     def __init__(self, max_workers=defaults.cpus, on_exc=print, pause=0, **kwargs):
         if max_workers is None: max_workers=defaults.cpus
-        max_workers = check_parallel_num('max_workers', max_workers)
         store_attr()
         self.not_parallel = max_workers==0
         if self.not_parallel: max_workers=1
         super().__init__(max_workers, **kwargs)
 
     def map(self, f, items, *args, timeout=None, chunksize=1, **kwargs):
+        if not parallelable('max_workers', self.max_workers, f): self.max_workers = 0
+        self.not_parallel = self.max_workers==0
+        if self.not_parallel: self.max_workers=1
+
         if self.not_parallel == False: self.lock = Manager().Lock()
         g = partial(f, *args, **kwargs)
         if self.not_parallel: return map(g, items)
@@ -118,6 +122,13 @@ def parallel(f, items, *args, n_workers=defaults.cpus, total=None, progress=None
             r = progress_bar(r, total=total, leave=False)
         return L(r)
 
+# Cell
+def add_one(x, a=1):
+    # this import is necessary for multiprocessing in notebook on windows
+    import random
+    time.sleep(random.random()/80)
+    return x+a
+
 # Cell
 def run_procs(f, f_done, args):
     "Call `f` for each item in `args` in parallel, yielding `f_done`"
@@ -135,7 +146,7 @@ def _done_pg(queue, items): return (queue.get() for _ in items)
 # Cell
 def parallel_gen(cls, items, n_workers=defaults.cpus, **kwargs):
     "Instantiate `cls` in `n_workers` procs & call each on a subset of `items` in parallel."
-    n_workers = check_parallel_num('n_workers', n_workers)
+    if not parallelable('n_workers', n_workers): n_workers = 0
     if n_workers==0:
         yield from enumerate(list(cls(**kwargs)(items)))
         return

nbs/03a_parallel.ipynb

@@ -193,12 +193,13 @@
    "outputs": [],
    "source": [
     "#export\n",
-    "def check_parallel_num(param_name, num_workers):\n",
-    "    if sys.platform == \"win32\" and IN_NOTEBOOK and num_workers > 0:\n",
+    "def parallelable(param_name, num_workers, f=None):\n",
+    "    f_in_main = f == None or sys.modules[f.__module__].__name__ == \"__main__\" \n",
+    "    if sys.platform == \"win32\" and IN_NOTEBOOK and num_workers > 0 and f_in_main:\n",
     "        print(\"Due to IPython and Windows limitation, python multiprocessing isn't available now.\")\n",
-    "        print(f\"So `{param_name}` is changed to 0 to avoid getting stuck\")\n",
-    "        num_workers = 0\n",
-    "    return num_workers"
+    "        print(f\"So `{param_name}` has to be changed to 0 to avoid getting stuck\")\n",
+    "        return False\n",
+    "    return True"
    ]
   },
   {
@@ -263,13 +264,16 @@
     "    \"Same as Python's ProcessPoolExecutor, except can pass `max_workers==0` for serial execution\"\n",
     "    def __init__(self, max_workers=defaults.cpus, on_exc=print, pause=0, **kwargs):\n",
     "        if max_workers is None: max_workers=defaults.cpus\n",
-    "        max_workers = check_parallel_num('max_workers', max_workers)\n",
     "        store_attr()\n",
     "        self.not_parallel = max_workers==0\n",
     "        if self.not_parallel: max_workers=1\n",
     "        super().__init__(max_workers, **kwargs)\n",
     "\n",
     "    def map(self, f, items, *args, timeout=None, chunksize=1, **kwargs):\n",
+    "        if not parallelable('max_workers', self.max_workers, f): self.max_workers = 0\n",
+    "        self.not_parallel = self.max_workers==0\n",
+    "        if self.not_parallel: self.max_workers=1\n",
+    "            \n",
     "        if self.not_parallel == False: self.lock = Manager().Lock()\n",
     "        g = partial(f, *args, **kwargs)\n",
     "        if self.not_parallel: return map(g, items)\n",
@@ -340,10 +344,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def add_one(x, a=1): \n",
+    "#export\n",
+    "def add_one(x, a=1):\n",
+    "    # this import is necessary for multiprocessing in notebook on windows\n",
+    "    import random\n",
     "    time.sleep(random.random()/80)\n",
-    "    return x+a\n",
-    "\n",
+    "    return x+a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "inp,exp = range(50),range(1,51)\n",
     "\n",
     "test_eq(parallel(add_one, inp, n_workers=2, progress=False), exp)\n",
@@ -378,11 +392,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 2021-02-03 09:51:30.561681\n",
-      "1 2021-02-03 09:51:30.812066\n",
-      "2 2021-02-03 09:51:31.063662\n",
-      "3 2021-02-03 09:51:31.313478\n",
-      "4 2021-02-03 09:51:31.564776\n"
+      "0 2021-02-23 06:38:58.778425\n",
+      "1 2021-02-23 06:38:59.028804\n",
+      "2 2021-02-23 06:38:59.280227\n",
+      "3 2021-02-23 06:38:59.530889\n",
+      "4 2021-02-23 06:38:59.781011\n"
      ]
     }
    ],
@@ -438,15 +452,15 @@
     "#export \n",
     "def parallel_gen(cls, items, n_workers=defaults.cpus, **kwargs):\n",
     "    \"Instantiate `cls` in `n_workers` procs & call each on a subset of `items` in parallel.\"\n",
-    "    n_workers = check_parallel_num('n_workers', n_workers)\n",
+    "    if not parallelable('n_workers', n_workers): n_workers = 0\n",
     "    if n_workers==0:\n",
     "        yield from enumerate(list(cls(**kwargs)(items)))\n",
     "        return\n",
     "    batches = L(chunked(items, n_chunks=n_workers))\n",
     "    idx = L(itertools.accumulate(0 + batches.map(len)))\n",
     "    queue = Queue()\n",
     "    if progress_bar: items = progress_bar(items, leave=False)\n",
-    "    f=partial(_f_pg, cls(**kwargs), queue)\n",
+    "    f=partial(_f_pg, cls(**kwargs), queue)        \n",
     "    done=partial(_done_pg, queue, items)\n",
     "    yield from run_procs(f, done, L(batches,idx).zip())"
    ]
@@ -546,7 +560,8 @@
       "Converted 05_transform.ipynb.\n",
       "Converted 07_meta.ipynb.\n",
       "Converted 08_script.ipynb.\n",
-      "Converted index.ipynb.\n"
+      "Converted index.ipynb.\n",
+      "Converted parallel_win.ipynb.\n"
      ]
     }
    ],
@@ -569,6 +584,13 @@
     "exit_code = process.wait()\n",
     "test_eq(exit_code, 0)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

nbs/parallel_win.ipynb

@@ -0,0 +1,38 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "informational-central",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fastcore.test import *\n",
+    "from fastcore.parallel import *\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    inp,exp = range(50),range(1,51)\n",
+    "\n",
+    "    test_eq(parallel(add_one, inp, n_workers=2, progress=False), exp)\n",
+    "    test_eq(parallel(add_one, inp, n_workers=1, a=2), range(2,52))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "developing-darwin",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}