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https://github.com/recruit-tech/drctrl

Automatically configuration tool for DataRobot.
https://github.com/recruit-tech/drctrl

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Automatically configuration tool for DataRobot.

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README 

        
# drctrl



drctrl is a tool for automatically configuration for DataRobot. drctrl can manage features provided datarobot like building project, training, freezing, prediction.



python support:	3.6.x and greater



## 1. Installation



```bash

$ pip install drctrl

```



## 2. Get started



Setting up credential



```bash

$ cat << _EOF_ > ~/.config/datarobot/drconfig.yaml

token: 

endpoint: 

_EOF_



# get all projects

$ drctrl get_projects



# get project detail

$ drctrl get_project 



# you can get the exist project configuration for drctrl with

$ drctrl get_project_setting 

```



### Build a new project



Download Boston Housing dataset in UCI [url](https://archive.ics.uci.edu/ml/machine-learning-databases/housing/Index).



```bash

# downloading dataset into `./data/raw/`

$ drctrl create_dataset

```



Setting up configure.yml



```yaml

environment:

   project_id: # if null, build a new project

   project_name: 'sample_project'

   target_feature: target

   metric: 'RMSE' 

   cv_method: 'random'

   validation_type: 'CV' 

   validation_params:

      holdout_pct: 20

      #validation_pct: 10

      reps: 3    # number of cross validation folds to use

      seed: 2017 # a seed to use for randomization

   dataset:

       type: file

       path: './data/raw'

       filename: 'boston.csv'

   autopilot: 'manual' # fullauto, quick, manual

   convert_features:

      - {name: RAD, rename_to: RAD_categoricalInt, variable_type: categoricalInt}



fit:

   model_id:  # if None, run autopilot

   autopilot: 'fullauto'

   featurelist_name: 'without_feature'  # if already exist, current time string will be used

   source_featurelist: 'Raw Features'

   except_features:

      - 'NOX'

      

predict:

   model_id:  # if None, a model will be automatically selected 

   input:     # prediction target dataset

       type: 'file'

       path: './data/raw/'

       filename: 'boston.csv'

   reasoncode: True

   merge_origin: True 

   feature_impact: True

   output:   # output format

       type: 'file'

       path: './'

       filename: 'prediction.csv'

```



Run drctrl with configuration



```bash

$ drctrl apply configure.yml

```



Details of commands and options is [here](docs/options.md)



## 3. Commands



```bash

Usage: drctrl [OPTIONS] COMMAND [ARGS]...



Options:

  --credential PATH

  --help             Show this message and exit.



Commands:

  apply                  Apply all commands in configuration file

  build                  building project on the basis of a configuration file

  create_dataset         download and install boston housing and iris dataset

  fit                    training model on the basis of a configuration file

  frozen                 freezing model on the basis of configuration file

  get_project            fetch the project detail

  get_project_setting    dump the project parameter as yaml file

  get_projects           fetch project details

  predict                predicting on the basis of a configuration file

  validate               validate configuration file

```



## 4. I/O format



There are several options for I/O format. redshift, file, url format can be specified as `dataset` param in `environment`, `input` / `output` param in `predict` for now.



Details are [here](docs/iotype.md)



### file format



```yaml

environment:

   dataset:

      type: file

      path: /path/to/dataset

      filename: dataset.csv

```



or 



```yaml

predict:

   input:

      type: redshift

      aws_key_id: 

      aws_secret_key: 

      bucket: 

      key_path: 

      dbname: 

      host: 

      port: 

      user: 

      password: 

      schema: 

      table:  

   output:

      type: redshift

      aws_key_id: 

      aws_secret_key: 

      bucket: 

      key_path: 

      dbname: 

      host: 

      port: 

      user: 

      password: 

      schema: 

      table:  

```



and so on.



## 5. template



drctrl support [Jinja2](https://github.com/pallets/jinja/tree/master/jinja2) template format. Configuration file have to satisfy file extention format `.yml.tmple` .



In tmpl file, `env['FILE_PATH']` variable is replaced by environment variable `FILE_PATH`.

The following is an example.



```yaml

environment:

    project_id: {{ env.PROJECT_ID }}



predict:

    model_id: {{ env.MODEL_ID }}

    dataset:

      type: file

      path: {{ env['DATASET_PATH'] }}

      filename: {{ env['DATASET_FILE'] }}

    feature_impact: false

    reasoncode: false

    merge_origin: true

```