bounded-pool-executor
Bounded Process&Thread Pool Executor
Decision gist · record as of 2026-08-14
Yes, if you are processing large task volumes on memory-limited systems and can tolerate dormant maintenance. The package solves a real problem (memory exhaustion with standard executors) and has no dependencies, making it low-risk to add. However, verify compatibility with your Python version first, as the latest release was 2019-06-04 and no updates are planned.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- No external dependencies, but verify Python version compatibility given latest release was 2019-06-04.
- Low install friction with no runtime dependencies.
- Maintenance is dormant—last release was 2019-06-04 and last commit 2024-03-08—so expect no active support or updates, though the repository remains active.
License · maintenance · safety
MIT (permissive) — MIT license is permissive, allowing commercial and private use with minimal restrictions; attribution required but no copyleft obligations.
last release 2019-06-04 (2628 days) · last repo commit 2024-03-08 · 63 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 417,754 downloads/mo, #6,810 on PyPI
Alternatives
Verify before relying
from bounded_pool_executor import BoundedProcessPoolExecutor
def task(item):
return item
with BoundedProcessPoolExecutor(max_workers=5) as executor:
for i in range(10000):
executor.submit(task, i)- Whether the package works with current Python versions given dormant maintenance status since latest release.
- Whether BoundedThreadPoolExecutor is also provided or only BoundedProcessPoolExecutor.
- Performance characteristics and overhead of the bounded semaphore approach vs. standard executors.
What it is and what it does
bounded-pool-executor provides drop-in replacements for concurrent.futures.ProcessPoolExecutor and ThreadPoolExecutor that apply backpressure to task submission. Instead of accepting all submitted tasks into an unbounded queue, it uses a BoundedSemaphore to block submit() calls until a worker finishes, ensuring the queue never grows beyond the number of active workers. This prevents the memory exhaustion that occurs when processing millions of items with standard executors on memory-constrained systems.
The package is a thin wrapper around the standard library's executor classes, requiring no external dependencies. It is designed as a direct replacement: you import BoundedProcessPoolExecutor or BoundedThreadPoolExecutor and use them identically to their standard counterparts, but with the guarantee that memory usage stays bounded by the number of workers rather than the number of submitted tasks.
Use it for
- Processing millions of items on a memory-constrained system without exhausting available RAM.
- Batch processing large datasets where task submission rate far exceeds worker completion rate.
- Long-running services that accept unbounded work queues and need to apply backpressure to prevent memory issues.
- Distributed crawling or scraping tasks where the task generator runs faster than workers can consume.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are processing large task volumes on memory-limited systems and can tolerate dormant maintenance.
The package solves a real problem (memory exhaustion with standard executors) and has no dependencies, making it low-risk to add. However, verify compatibility with your Python version first, as the latest release was 2019-06-04 and no updates are planned.
Install
bounded-pool-executor on PyPI
Before you install
Low install friction with no runtime dependencies. Maintenance is dormant—last release was 2019-06-04 and last commit 2024-03-08—so expect no active support or updates, though the repository remains active.
No external dependencies, but verify Python version compatibility given latest release was 2019-06-04.
License in practice
MIT license is permissive, allowing commercial and private use with minimal restrictions; attribution required but no copyleft obligations.
Quickstart
from bounded_pool_executor import BoundedProcessPoolExecutor
def task(item):
return item
with BoundedProcessPoolExecutor(max_workers=5) as executor:
for i in range(10000):
executor.submit(task, i)Verify before relying
- Whether the package works with current Python versions given dormant maintenance status since latest release.
- Whether BoundedThreadPoolExecutor is also provided or only BoundedProcessPoolExecutor.
- Performance characteristics and overhead of the bounded semaphore approach vs. standard executors.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 2,628 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 417,754 / month, #6,810 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: bounded_pool_executor-0.0.3-py3-none-any.whl
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