p-tqdm
Parallel processing with progress bars
Decision gist · record as of 2026-08-14
Yes, if you need parallel map with a progress bar and can tolerate the high install friction (three dependencies) and dormant maintenance. The package is stable and has no known vulnerabilities, but expect no active bug fixes or new features. Best suited for one-off scripts or internal tools where the convenience of p_map outweighs the dependency cost; for production systems, consider whether direct pathos + tqdm usage or a more actively maintained alternative is preferable.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- High install friction due to three runtime dependencies (tqdm, pathos, six).
- Maintenance is dormant—last release was 2024-08-08 but no commits since then; the repository remains active with 493 stars but receives infrequent updates.
License · maintenance · safety
MIT (permissive) — MIT license is permissive and imposes no restrictions on use, modification, or distribution in proprietary or open-source projects.
last release 2024-08-08 (736 days) · last repo commit 2024-08-08 · 493 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 172,237 downloads/mo, #10,344 on PyPI
Alternatives
Verify before relying
pip install p_tqdm
from p_tqdm import p_map
def add(a, b):
return a + b
result = p_map(add, ['1', '2', '3'], ['a', 'b', 'c'])
print(result) # ['1a', '2b', '3c']- Whether pathos dependency works reliably on all platforms (Windows, macOS, Linux) where p_tqdm is deployed
- Performance overhead of the wrapper compared to direct pathos.multiprocessing calls
- Compatibility with modern async/await patterns or asyncio-based concurrency
What it is and what it does
p_tqdm is a thin wrapper combining pathos.multiprocessing and tqdm to make parallel processing more convenient. It provides functions like p_map, p_imap, p_umap, and p_uimap that apply a function across multiple iterables in parallel, while displaying a live progress bar with completion estimates. Unlike Python's built-in multiprocessing, pathos supports lambda functions, nested functions, and class methods, which p_tqdm exposes with minimal syntax overhead.
The package is designed for CPU-bound workloads where you want to parallelize a map operation without wrestling with multiprocessing pool setup. It supports controlling CPU count (as an integer or proportion), custom tqdm flavors, and both ordered and unordered result collection. Sequential variants (t_map, t_imap) are also provided for cases where you want the same interface without parallelism.
Use it for
- Batch-process large datasets with a function while monitoring progress in real time
- Apply an expensive computation across multiple inputs using all available CPU cores
- Replace a slow for-loop with parallel execution while keeping code readable and adding progress visibility
- Parallelize functions with multiple arguments or complex signatures that standard multiprocessing struggles with
- Collect results in order (p_map) or accept any order (p_umap) depending on whether result sequence matters
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need parallel map with a progress bar and can tolerate the high install friction (three dependencies) and dormant maintenance.
The package is stable and has no known vulnerabilities, but expect no active bug fixes or new features. Best suited for one-off scripts or internal tools where the convenience of p_map outweighs the dependency cost; for production systems, consider whether direct pathos + tqdm usage or a more actively maintained alternative is preferable.
Install
p-tqdm on PyPI
Before you install
High install friction due to three runtime dependencies (tqdm, pathos, six). Maintenance is dormant—last release was 2024-08-08 but no commits since then; the repository remains active with 493 stars but receives infrequent updates.
License in practice
MIT license is permissive and imposes no restrictions on use, modification, or distribution in proprietary or open-source projects.
Quickstart
pip install p_tqdm
from p_tqdm import p_map
def add(a, b):
return a + b
result = p_map(add, ['1', '2', '3'], ['a', 'b', 'c'])
print(result) # ['1a', '2b', '3c']Verify before relying
- Whether pathos dependency works reliably on all platforms (Windows, macOS, Linux) where p_tqdm is deployed
- Performance overhead of the wrapper compared to direct pathos.multiprocessing calls
- Compatibility with modern async/await patterns or asyncio-based concurrency
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | 3 packagestqdmpathossix |
| Maintenance | Dormant 736 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 172,237 / month, #10,344 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 :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: p_tqdm-1.4.2.tar.gz
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See also acvl-utils · tqdm-joblib · tqdm-multiprocess · tqdm-loggable · parallelbar · para · tqdm · tdqm · pqdm · easydev