%global _empty_manifest_terminate_build 0
Name:		python-bounded-pool-executor
Version:	0.0.3
Release:	1
Summary:	Bounded Process&Thread Pool Executor
License:	MIT
URL:		http://github.com/mowshon/bounded_pool_executor
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/23/f1/e34501c1228415e9fbcac8cb9c81098900e78331b30eeee1816176324bab/bounded_pool_executor-0.0.3.tar.gz
BuildArch:	noarch


%description
# Bounded Process&Thread Pool Executor
BoundedSemaphore for [ProcessPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#processpoolexecutor) & [ThreadPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor) from [concurrent.futures](https://docs.python.org/3/library/concurrent.futures.html)

## Installation
```bash
pip install bounded-pool-executor
```

# What is the main problem?
If you use the standard module "**concurrent.futures**" and want to simultaneously process several million data, then a queue of workers will take up all the free memory.

If the script is run on a weak VPS, this will lead to a **memory leak**.



## BoundedProcessPoolExecutor VS ProcessPoolExecutor

# BoundedProcessPoolExecutor
**BoundedProcessPoolExecutor** will put a new worker in queue only when another worker has finished his work.

```python
from bounded_pool_executor import BoundedProcessPoolExecutor
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 10)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with BoundedProcessPoolExecutor(max_workers=5) as worker:
    for num in range(10000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)

```
### Result:
![BoundedProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/bounded.gif)

# Classic concurrent.futures.ProcessPoolExecutor
**ProcessPoolExecutor** inserts all workers into the queue and expects tasks to be performed as the new worker is released, depending on the value of `max_workers`.

```python
import concurrent.futures
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 3)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with concurrent.futures.ProcessPoolExecutor(max_workers=5) as worker:
    for num in range(100000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)
```

### Result:
![concurrent.futures.ProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/future-ProcessPoolExecutor.gif)




%package -n python3-bounded-pool-executor
Summary:	Bounded Process&Thread Pool Executor
Provides:	python-bounded-pool-executor
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-bounded-pool-executor
# Bounded Process&Thread Pool Executor
BoundedSemaphore for [ProcessPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#processpoolexecutor) & [ThreadPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor) from [concurrent.futures](https://docs.python.org/3/library/concurrent.futures.html)

## Installation
```bash
pip install bounded-pool-executor
```

# What is the main problem?
If you use the standard module "**concurrent.futures**" and want to simultaneously process several million data, then a queue of workers will take up all the free memory.

If the script is run on a weak VPS, this will lead to a **memory leak**.



## BoundedProcessPoolExecutor VS ProcessPoolExecutor

# BoundedProcessPoolExecutor
**BoundedProcessPoolExecutor** will put a new worker in queue only when another worker has finished his work.

```python
from bounded_pool_executor import BoundedProcessPoolExecutor
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 10)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with BoundedProcessPoolExecutor(max_workers=5) as worker:
    for num in range(10000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)

```
### Result:
![BoundedProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/bounded.gif)

# Classic concurrent.futures.ProcessPoolExecutor
**ProcessPoolExecutor** inserts all workers into the queue and expects tasks to be performed as the new worker is released, depending on the value of `max_workers`.

```python
import concurrent.futures
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 3)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with concurrent.futures.ProcessPoolExecutor(max_workers=5) as worker:
    for num in range(100000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)
```

### Result:
![concurrent.futures.ProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/future-ProcessPoolExecutor.gif)




%package help
Summary:	Development documents and examples for bounded-pool-executor
Provides:	python3-bounded-pool-executor-doc
%description help
# Bounded Process&Thread Pool Executor
BoundedSemaphore for [ProcessPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#processpoolexecutor) & [ThreadPoolExecutor](https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor) from [concurrent.futures](https://docs.python.org/3/library/concurrent.futures.html)

## Installation
```bash
pip install bounded-pool-executor
```

# What is the main problem?
If you use the standard module "**concurrent.futures**" and want to simultaneously process several million data, then a queue of workers will take up all the free memory.

If the script is run on a weak VPS, this will lead to a **memory leak**.



## BoundedProcessPoolExecutor VS ProcessPoolExecutor

# BoundedProcessPoolExecutor
**BoundedProcessPoolExecutor** will put a new worker in queue only when another worker has finished his work.

```python
from bounded_pool_executor import BoundedProcessPoolExecutor
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 10)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with BoundedProcessPoolExecutor(max_workers=5) as worker:
    for num in range(10000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)

```
### Result:
![BoundedProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/bounded.gif)

# Classic concurrent.futures.ProcessPoolExecutor
**ProcessPoolExecutor** inserts all workers into the queue and expects tasks to be performed as the new worker is released, depending on the value of `max_workers`.

```python
import concurrent.futures
from time import sleep
from random import randint

def do_job(num):
    sleep_sec = randint(1, 3)
    print('value: %d, sleep: %d sec.' % (num, sleep_sec))
    sleep(sleep_sec)

with concurrent.futures.ProcessPoolExecutor(max_workers=5) as worker:
    for num in range(100000):
        print('#%d Worker initialization' % num)
        worker.submit(do_job, num)
```

### Result:
![concurrent.futures.ProcessPoolExecutor](https://python-scripts.com/wp-content/uploads/2018/12/future-ProcessPoolExecutor.gif)




%prep
%autosetup -n bounded-pool-executor-0.0.3

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-bounded-pool-executor -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.3-1
- Package Spec generated