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mapply

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library0.2.0pypypi✓ verified 85d ago

Sensible multi-core apply function for Pandas. Currently version 0.2.0, supporting Pandas v3 (last version supporting Pandas v2 is 0.1.31). Active development with frequent releases.

pip install mapply
INSTALL
IMPORT
SIG · MAPPLY
M
mapply
datapythonv0.2.0
Install
8.3s avg
Import
1369ms
Disk
169MB
Pass rate
10/ 10
Env Coverage10 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v0.1.31 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
py 3.103.95 runs
installs and imports cleanly · install 0.0s · import 1.398s · 169.2MB
glibc
py 3.103.95 runs
installs and imports cleanly · install 8.3s · import 1.340s · 162MB
169MB installed
● package 169MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

mapply
import mapply
from mapply import mapply
mapply is a top-level module that monkey-patches pandas; you import it, not a specific class.

Initialize mapply with all CPUs, then use .mapply() like .apply() but parallel.

import pandas as pd import mapply mapply.init(n_workers=-1) # use all CPUs df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]}) result = df.mapply(lambda row: row['a'] + row['b'], axis=1) print(result)
Debug
Known issues
breakingmapply 0.2.0 drops support for Pandas v2. Pandas v3+ is required. Last compatible version is 0.1.31.
fix
Pin mapply<0.2.0 if using Pandas v2, or upgrade to Pandas v3.
affects: >=0.2.0
deprecatedmapply 0.1.24+ declares pandas as a dependency. Older versions lack this, causing resolvers to pair with incompatible pandas versions.
fix
Always pin mapply>=0.1.24.
affects: <0.1.24
gotchamapply must be imported before any pandas operations. Importing after creating DataFrames will not apply the monkey-patch.
fix
Always import mapply at the top of your script, before any pandas calls.
affects: all
gotchaBy default mapply uses multiprocessing (Pool). For multithreading, set POOL_CLASS to ThreadPool via mapply.init(pool_class='ThreadPool').
fix
Call mapply.init(n_workers=..., pool_class='ThreadPool') for I/O-bound tasks.
affects: >=0.1.29
Errors
Common errors & fixes
AttributeError: 'DataFrame' object has no attribute 'mapply'
mapply not imported or imported after DataFrame already created.
fix
Add 'import mapply' at the top of your script, before any pandas DataFrame creation.
ModuleNotFoundError: No module named 'mapply'
mapply is not installed.
fix
Run: pip install mapply
ValueError: n_workers must be >= 1 or -1 for all CPUs
Passing invalid value to mapply.init(n_workers=...).
fix
Use n_workers=-1 for all CPUs, or an integer >= 1.
Upgrade
Version history
0.2.0latest on PyPI · released Feb 23, 2026
Audit
Dependencies

No dependency data recorded yet.

Agent activity
2 hits · last 30 days
node
2
Resources
mapply — pip install mapply · libregistry