Estimator
A Python script for automatically estimating work hours in Jira using supervised learning.
Installation
Install the Python 3 package:
pip install estimator
Usage
Fill out the login credentials in your config.yaml. A sample file to pull data from Jira would look like:
source: jira
server: https://myname.atlassian.net
username: myusername
password: mypassword
projects: MYPROJECTKEY
regressor:
cls: KernelRidge
stop_words: ''
ngram_range: [1, 6]
analyzer: char
min_df: 0.0
minimum_estimate_minutes: 15
hour_update_fields:
- Story Points
Retrieve training data:
estimator config.yaml retrieve
Generate all possible algorithm and setting combinations:
estimator config.yaml generation-combinations
Test all combinations to find which algorithm works best:
estimator config.yaml test-combinations
Fill in the regressor settings in your config.yaml, then train your final regressor:
estimator config.yaml train
Find the algorithm's accuracy:
estimator config.yaml test
Dryrun the application of the regressor to unestimated tickets:
estimator config.yaml apply
Save these estimates with:
estimator config.yaml apply --save
To combine the above retrieve, train and apply steps into a single command, just add --retrain to the apply command:
estimator config.yaml apply --save --retrain
Development
Run tests locally with:
tox
To run tests for a specific environment (e.g. Python 3.7):
tox -e py37
To run a specific test:
export TESTNAME=.test_learning; tox -e py37
Metadata
Release files for task-estimator 0.9.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| task-estimator-0.9.2.tar.gz | 12.3 kB | Details |
Release files / task-estimator-0.9.2.tar.gz
| Download URL | task-estimator-0.9.2.tar.gz |
|---|---|
| Size | 12.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.32.2 CPython/3.5.2
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