#!/usr/bin/env python
# coding: utf-8

# ![brainome logo](./images/brainome_logo.png)
# # 303 Predictor Validation Measurements in JSON
# The predictor can output validation measurements in json rather than human-readable text.
# 
# * Validation measurements in json format.

# ## Prerequisites
# This notebook assumes brainome is installed as per notebook [brainome_101_Quick_Start](brainome_101_Quick_Start.ipynb)
# 
# The data sets are:
# * [titanic_train.csv](https://download.brainome.ai/data/public/titanic_train.csv) for training data
# * [titanic_validate.csv](https://download.brainome.ai/data/public/titanic_validate.csv) for validation
# 

# In[ ]:


get_ipython().system('python3 -m pip install brainome --quiet')
get_ipython().system('brainome --version')

import urllib.request as request
response2 = request.urlretrieve('https://download.brainome.ai/data/public/titanic_validate.csv', 'titanic_validate.csv')
get_ipython().run_line_magic('ls', '-lh titanic_validate.csv')


# ## Generate a predictor
# The predictor filename is `predictor_303.py`

# In[ ]:


get_ipython().system('brainome https://download.brainome.ai/data/public/titanic_train.csv -y -o predictor_303.py -modelonly -q')
print('\nCreated predictor_303.py')
get_ipython().system('ls -lh predictor_303.py')


# ## Validation measurements in json format.
# The same measurements as all previous exercises can be generated in JSON format for further system integration
# Use `-validate -json` to trigger the predictor to output json validation measurements.

# In[ ]:


get_ipython().system('python3 predictor_303.py -validate titanic_validate.csv -json > validation_measurements_303.json')
import json
with open('validation_measurements_303.json', 'r') as measurement_file:
    validation_measurements = json.load(measurement_file)
    print(json.dumps(validation_measurements, indent=4))


# ## Next Steps
# - Check out [300 Put your model to work](./brainome_300_Integrating_Predictors.ipynb)
# > TODO next...