This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
BayesianBrandTracker
This file will become your README and also the index of your documentation.
Developer Guide
If you are new to using nbdev here are some useful pointers to get you
started.
Install BayesianBrandTracker in Development mode
# make sure BayesianBrandTracker package is installed in development mode
$ pip install -e .
# make changes under nbs/ directory
# ...
# compile to have changes apply to BayesianBrandTracker
$ nbdev_prepare
Usage
Installation
Install latest from the GitHub repository:
$ pip install git+https://github.com/redam94/BayesianBrandTracker.git
or from conda
$ conda install -c redam94 BayesianBrandTracker
or from pypi
$ pip install BayesianBrandTracker
Documentation
Documentation can be found hosted on this GitHub repository’s pages. Additionally you can find package manager specific guidelines on conda and pypi respectively.
How to use
Fill me in please! Don’t forget code examples:
1+1
2
1 maintainer
Metadata
1 maintainer
Release files for BayesianBrandTracker 0.0.1
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 |
|---|---|---|---|---|
| bayesianbrandtracker-0.0.1.tar.gz | 8.9 kB | Without provenance | Details for bayesianbrandtracker-0.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| BayesianBrandTracker-0.0.1-py3-none-any.whl | Python 3 | none | any | Details for BayesianBrandTracker-0.0.1-py3-none-any.whl |
Total release size: 17.1 kB
Release files / bayesianbrandtracker-0.0.1.tar.gz
| Download URL | bayesianbrandtracker-0.0.1.tar.gz |
|---|---|
| Size | 8.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.0
|
Release files / BayesianBrandTracker-0.0.1-py3-none-any.whl
| Download URL | BayesianBrandTracker-0.0.1-py3-none-any.whl |
|---|---|
| Size | 8.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
4d11093bb260ef0900af61f4fe00b924e21e5d34cf96f5b5b21825b367e9552e
|
|
BLAKE2b-256 checksum How to use checksums |
7f024164ebeae9f56d78ffa8d1824b3718dc96cad4d416e2b9ea874c85df8ddb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.0
|
Security for BayesianBrandTracker 0.0.1
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
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To learn more about protecting yourself from malicious actors, visit our package security documentation.
