mmar-utils
Common pure/IO utilities for multi-modal architectures team.
Installation
pip install mmar-utils
parallel_map
Mix of joblib.Parallel and tqdm.
Similar libraries
joblib.Parallel: https://joblib.readthedocs.io/en/latest/parallel.html
- doesn't support showing progress out of the box
Syntax comparison ( assuming tqdm disabled )
from math import sqrt, pow
from joblib import Parallel as P, delayed as d
from agi_med_utils import parallel_map
# ONE-ARG: THREADING
print(P(n_jobs=2)(map(d(sqrt), range(5))))
print(P(n_jobs=2)(d(sqrt)(i) for i in range(5)))
print(parallel_map(sqrt, range(5)))
# > [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
# ONE-ARG: MULTIPROCESSING
print(P(n_jobs=2, backend='multiprocessing')(d(sqrt)(i) for i in range(3)))
print(parallel_map(sqrt, range(3), process=True))
# > [0.0, 1.0, 1.4142135623730951]
# MANY-ARGS: THREADING
pow_args = [(i, j) for i in range(1, 4) for j in range(1, 3)]
print(P(n_jobs=2)(d(pow)(i, j) for i, j in pow_args))
print(parallel_map(pow, pow_args, multiple_args=True))
# > [1.0, 1.0, 2.0, 4.0, 3.0, 9.0]
# KWARGS: THREADING
def ipow_kw(*, x, y):
return 1 / pow(x, y)
ipow_kwargs = [{'x': i, 'y': j} for i, j in pow_args]
print(P(n_jobs=2)(d(ipow_kw)(**kw) for kw in ipow_kwargs))
print(parallel_map(ipow_kw, ipow_kwargs, kwargs_args=True))
# > [1.0, 1.0, 0.5, 0.25, 0.3333333333333333, 0.1111111111111111]
# KWARGS: MULTIPROCESSING
def ipow_kw_inc(*, x, y):
return 1 / pow(x, y) + 1
print(P(n_jobs=2, backend='multiprocessing')(d(ipow_kw_inc)(**kw) for kw in ipow_kwargs))
print(parallel_map(ipow_kw_inc, ipow_kwargs, kwargs_args=True, process=True))
# > [2.0, 2.0, 1.5, 1.25, 1.3333333333333333, 1.1111111111111112]
pqdm: https://pqdm.readthedocs.io/en/latest/usage.html
trace_with
Decorator for function which executes some callback on each function call.
Similar libraries
functrace: https://github.com/idanhazan/functrace
- does not remember start datetime of call, which is critical
- supports selection of parameters to remember
functrace.TraceResultobject is not serializable out of the box
Metadata
Release files for mmar-utils 1.1.20
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| mmar_utils-1.1.20.tar.gz | 13.3 kB | Without provenance | Details for mmar_utils-1.1.20.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| mmar_utils-1.1.20-py3-none-any.whl | Python 3 | none | any | Details for mmar_utils-1.1.20-py3-none-any.whl |
Total release size: 31.4 kB
Release files / mmar_utils-1.1.20.tar.gz
| Download URL | mmar_utils-1.1.20.tar.gz |
|---|---|
| Size | 13.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
affbed77ac0126079c0adaaa42732260251c9a5f30b216a57f99bfa332c679d1
|
|
BLAKE2b-256 checksum How to use checksums |
6b46dbb76a21c0c120b15a9aebb206de2c918b8818a8c05ae83a2f9bf85cc138
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.5.31
|
Release files / mmar_utils-1.1.20-py3-none-any.whl
| Download URL | mmar_utils-1.1.20-py3-none-any.whl |
|---|---|
| Size | 18.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
eec570f354426444cbb3fa6f7e6dc82311a71238bf393e4dcc911c7a2d80bbfd
|
|
BLAKE2b-256 checksum How to use checksums |
17ad2ea15881cd1f597c2f0bfee353cf6d2fad28c32b19405bce6d839f39b476
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.5.31
|
Security for mmar-utils 1.1.20
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.