Hb Bank Statement Machine Learning Module
This module add a machine learning on the account.bank.statement to predict the party and the account to use for a new line.
Install
Dependencies for ArchLinux
sudo pacman -S cairo pkgconf gobject-introspection
Dependencies for debian
sudo apt-get install libcairo2-dev libgirepository1.0-dev
Install the package
# installs python deps
pip install hb_bank_statement_machine_learning
# install the module
trytond-admin -u hb_bank_statement_machine_learning --activate-dependencies
Install the db by hb-tryton-devtools
pip install git+https://gitlab.com/hashbangfr/tryton-modules/hb_tryton_devtools.git#egg=hb_tryton_devtools
export TRYTON_DATABASE_URI=postgresql:///
export TRYTON_DATABASE_NAME=test
hb-tryton-admin create-db --modules hb_bank_statement_machine_learning
Test package
The package need pytest and hb-tryton-devtools
pip install pytest pytest-cov
pip install git+ssh://git@gitlab.com/hashbangfr/tryton-modules/hb_tryton_devtools.git#egg=hb_tryton_devtools
Run the test with pytest with environ variable
export TRYTON_DATABASE_URI=postgresql:///
export TRYTON_DATABASE_NAME=test
pytest hb_bank_statement_machine_learning/tests
Low level
The machine learning is added on the acount.statement.line, the machine learning is based on the field number on the line, this field must be filled
pool = Pool()
Line = pool.get('account.statement.line')
line = Line()
line.number = 'My number'
line.set_account_and_party_from_ml()
assert line.party
assert line.account
Usage
An on_change method on the field number exist to predict the fields party and account from the interface
CHANGELOG
1.0.0 (2022-05-18)
Used cache from trytond
0.1.0 (2021-09-28)
Implemented the machine learning
Implemented the on change method on the fields number
Metadata
Release files for hb-bank-statement-machine-learning 1.0.0
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 |
|---|---|---|---|---|
| hb_bank_statement_machine_learning-1.0.0.tar.gz | 19.1 kB | Without provenance | Details for hb_bank_statement_machine_learning-1.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| hb_bank_statement_machine_learning-1.0.0-py3-none-any.whl | Python 3 | none | any | Details for hb_bank_statement_machine_learning-1.0.0-py3-none-any.whl |
Total release size: 38.6 kB
Release files / hb_bank_statement_machine_learning-1.0.0.tar.gz
| Download URL | hb_bank_statement_machine_learning-1.0.0.tar.gz |
|---|---|
| Size | 19.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b99208bb13ecab8af9cc20bf31a50481b1a538f46a2568aae583b63e1c6a551a
|
|
BLAKE2b-256 checksum How to use checksums |
f8eb382c365768635402f09aef66774560ac707fa8a7ff9c506651759649327b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.9.2
|
Release files / hb_bank_statement_machine_learning-1.0.0-py3-none-any.whl
| Download URL | hb_bank_statement_machine_learning-1.0.0-py3-none-any.whl |
|---|---|
| Size | 19.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9864d4d6f57f4e89fd987b7198ad5abb35cb255229c9dd524cf382591d3cd8c1
|
|
BLAKE2b-256 checksum How to use checksums |
07f42bd89b5de6a66863ef3e130e742d7aeca6aa2b30861d0f1cde1f876aeeb3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.9.2
|
Security for hb-bank-statement-machine-learning 1.0.0
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.