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Update setup instructions and documentation
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Procfile
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web: sh setup.sh && streamlit run app.py
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web: sh setup.sh && streamlit run src/app.py
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README.md
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#### Complete graphviz installation
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https://graphviz.org/download/
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### Run the streamlit app (app.py) by running the following in terminal:
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streamlit run app.py
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>* Clear and adequate information to the user;
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>* Appropriate human oversight measures to minimise risk;
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>* High level of robustness, security and accuracy."
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#### Complete graphviz installation
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https://graphviz.org/download/
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## Build and install local package
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```shell
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python setup.py build
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```
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```shell
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python setup.py install
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```
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### Run the streamlit app (app.py) by running the following in terminal:
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streamlit run app.py
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>* Clear and adequate information to the user;
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>* Appropriate human oversight measures to minimise risk;
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>* High level of robustness, security and accuracy."
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# Docs creation
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## [pydeps](https://github.com/thebjorn/pydeps) Python module depenency visualization
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```shell
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pydeps src --max-bacon=3 --cluster --max-cluster-size=3 --rankdir BT -o docs/module-dependency-graph/src.svg
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```
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```shell
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pydeps src/app.py --max-bacon=3 --cluster --max-cluster-size=3 --rankdir BT -o docs/module-dependency-graph/app.svg
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```
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## [code2flow](https://github.com/scottrogowski/code2flow) Call graphs for a pretty good estimate of project structure
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### Logistic
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```shell
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code2flow src/models/logistic_train_model.py -o docs/call-graph/logistic_train_model.svg
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```
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```shell
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code2flow src/models/logistic_model.py -o docs/call-graph/logistic_model.svg
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```
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### Xgboost
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```shell
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code2flow src/models/xgboost_train_model.py -o docs/call-graph/xgboost_train_model.svg
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```
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```shell
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code2flow src/models/xgboost_model.py -o docs/call-graph/xgboost_model.svg
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```
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### utils
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```shell
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code2flow src/models/util_test.py -o docs/call-graph/util_test.svg
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```
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```shell
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code2flow src/models/util_predict_model_threshold.py -o docs/call-graph/util_predict_model_threshold.svg
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```
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```shell
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code2flow src/models/util_predict_model.py -o docs/call-graph/util_predict_model.svg
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```
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```shell
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code2flow src/models/util_model_comparison.py -o docs/call-graph/util_model_comparison.svg
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```
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setup.py
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from setuptools import find_packages, setup
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setup(
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name='src',
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packages=find_packages(),
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version='0.1.0',
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description='Tool for credit risk modelling',
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author='Author',
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license='MIT',
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)
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