LazyBox
A user friendly API to jump-start your Deep Learning project based on Fastai.
The library is still in early development, but a lot of new features will be added in future
[ ] Support for non-image Datasets
[ ] Import NN architecture from the timm library
[ ] Make it better
Install
pip install lazybox
How to use
Let's go through a typical workflow for a DeepLearning task. Let's download this Dataset on Kaggle: https://www.kaggle.com/tongpython/cat-and-dog which are images of cat and dogs.
# we lazy folks only use wild imports
from lazybox.all import *
path = Path('test_dataset')
path.find('archive')
'test_dataset/archive.zip'
Let's decompress this archive
1 maintainer
Metadata
1 maintainer
Release files for lazybox 0.0.2.5
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 |
|---|---|---|---|---|
| lazybox-0.0.2.5.tar.gz | 11.0 kB | Without provenance | Details for lazybox-0.0.2.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| lazybox-0.0.2.5-py3-none-any.whl | Python 3 | none | any | Details for lazybox-0.0.2.5-py3-none-any.whl |
Total release size: 24.0 kB
Release files / lazybox-0.0.2.5.tar.gz
| Download URL | lazybox-0.0.2.5.tar.gz |
|---|---|
| Size | 11.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8a49803055f827823db2b2f6a0c009f5a7d615878051fcaecb93d21242c011db
|
|
BLAKE2b-256 checksum How to use checksums |
6d9c05b589abb45da148071dcbe8f6cbf72c914923cc3d0d8af7ad8810a28ecc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.7
|
Release files / lazybox-0.0.2.5-py3-none-any.whl
| Download URL | lazybox-0.0.2.5-py3-none-any.whl |
|---|---|
| Size | 13.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
49d4e03f8a72892cb2206ab5299b42d7af2506496723de439d5be2aae4cefa49
|
|
BLAKE2b-256 checksum How to use checksums |
8aaafd68f1ef98cecc37301d2428f69e66ff609a0d130214c5da6710057be9f3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.7
|
Security for lazybox 0.0.2.5
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.
