para
a set utilities that ake advantage of python's 'multiprocessing' module to distribute CPU-intensive tasks
Decision gist · record as of 2026-08-14
Yes, but with strong conditions. Para is worth installing only if you are maintaining existing code that already depends on it, or if you need a minimal, zero-dependency parallel-map utility and can accept that the package is unmaintained. For new projects, evaluate modern alternatives that receive active maintenance and may offer better compatibility with current Python versions. The permissive MIT license and low install friction are advantages, but abandonment is a significant drawback.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3; no explicit minimum version specified in package metadata.
- Installation is frictionless with no runtime dependencies.
- However, the package is abandoned—last release was 2020-01-17, so expect no maintenance, bug fixes, or compatibility 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 2020-01-17 (2401 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 247,051 downloads/mo, #8,701 on PyPI
Alternatives
Verify before relying
pip install para
import para
import gzip
items = ["file1.gz", "file2.gz"]
def process(path):
with gzip.open(path, 'rt') as f:
for line in f:
yield line
for result in para.map(process, items):
print(result)- Compatibility with Python versions released after 2020-01-17, given the package's abandonment.
- Performance characteristics and scalability limits compared to modern alternatives.
- Whether the map() function handles generator functions and exception propagation as expected in current Python releases.
What it is and what it does
Para is a lightweight wrapper around Python's multiprocessing module that simplifies distributing CPU-bound work across multiple processor cores on a single machine. It centers on a map() function that applies a function to each item in a collection, executing the work in parallel across available cores rather than sequentially. The library is designed for straightforward parallel processing tasks without the complexity of lower-level multiprocessing APIs.
The package has no external runtime dependencies and installs with minimal friction. However, it has been abandoned since 2020-01-17 and receives no maintenance. For projects already using it or for simple parallel-map use cases where the API fits, it remains functional; for new projects, you should evaluate whether modern alternatives better suit your Python version and concurrency needs.
Use it for
- Process multiple large gzip-compressed files in parallel, extracting and filtering lines across CPU cores.
- Distribute CPU-intensive computations over a collection of data items without writing explicit multiprocessing boilerplate.
- Parallelize operations like reading or transforming files when the work can be divided into independent tasks.
- Leverage multiple cores for batch processing tasks in legacy codebases already using para.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, but with strong conditions.
Para is worth installing only if you are maintaining existing code that already depends on it, or if you need a minimal, zero-dependency parallel-map utility and can accept that the package is unmaintained. For new projects, evaluate modern alternatives that receive active maintenance and may offer better compatibility with current Python versions. The permissive MIT license and low install friction are advantages, but abandonment is a significant drawback.
Install
para on PyPI
Before you install
Installation is frictionless with no runtime dependencies. However, the package is abandoned—last release was 2020-01-17, so expect no maintenance, bug fixes, or compatibility updates.
Requires Python 3; no explicit minimum version specified in package metadata.
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 para
import para
import gzip
items = ["file1.gz", "file2.gz"]
def process(path):
with gzip.open(path, 'rt') as f:
for line in f:
yield line
for result in para.map(process, items):
print(result)Verify before relying
- Compatibility with Python versions released after 2020-01-17, given the package's abandonment.
- Performance characteristics and scalability limits compared to modern alternatives.
- Whether the map() function handles generator functions and exception propagation as expected in current Python releases.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 2,401 days since the last release |
| First released | |
| Downloads | 247,051 / month, #8,701 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Environment :: Other EnvironmentIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyTopic :: Scientific/EngineeringTopic :: Software Development :: Libraries :: Python ModulesTopic :: Utilities |
Evidence: para-0.0.8-py3-none-any.whl
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See also mapply · pandarallel · p-tqdm · parallelbar · mpire · pytest-xdist · mkl · multitasking · mkl-include · mkl-static