Data Input (DP_1)

Specify the data sources, this functionality can take database connection, CSV, JSON or ZIP files

NOTE: If you're using a database connection, create a separate user with appropriate permissions, before uploading data from a database.

Sample Request

{
    "project_id": 1,
    "parent_id": 0,
    "block_id": 1,
    "function_code": "DP_1",
    "args": {
        "dburl": "https://raw.githubusercontent.com/autogonai/autogon-public-datasets/main/mobile_price_prediction.csv",
        "dbservertype": "",
        "file_type": "csv",
        "database_name": "",
        "dbuser": "",
        "dbpassword": "",
        "query": "",
    }
}

Data input

POST https://api.autogon.ai/api/v1/engine/start

Loads data into a project.

Request Body

Name	Type	Description
dburl*	String	database host or Data Source URL
file_type*	String	File type for data input (db for database, csv for CSV, json for JSON for source files.
dbservertype	String	database server type (required with file_type: db)
database_name	String	Name of the database (required with file_type: db)
dbuser	String	Username for connecting with database (required with file_type: db)
dbpassword	String	Password for connecting with the database (required with file_type: db)
query	String	query to fetch data from the database (required with file_type: db)
project_id*	int	current project ID
block_id*	int	current block ID
function_code*	String	block's function code
args*	object	block arguments
parent_id	int	previous block ID
method*	String	Method of importation. Options: 'img_class_folder': import as an image classification problem with folder names as image class labels 'img_csv': import as an image regression or classification problem with image paths listed in a colmn of a csv and target variables on other column(s) (required with file_type : zip)
images_path	String	Path to images from zip file's root (required with file_type: zip)
class_mode	String	Method of importing target labels or variables Options: 'binary': The inputter will return binary labels indicating the class membership of each sample 'categorical': The inputter will return one-hot encoded labels, where each class is represented by a binary vector with a single 1 and 0s elsewhere 'sparse': Instead of one-hot encoded labels for a multi-classifcation problem, the inputter will return integer labels for each class 'input': The inputter will return the input images as both the input and output. 'raw': The inputter will return the raw data gotten for the y_column
target_size*	array	Image size in pixels (Length, Width) (required with file_type: zip)
csv_path*	String	Path to CSV from zip file's root (required with file_type: zip and method: img_csv)
image_files_column*	String	Column name of column containing the list of image file names (images within folders aren't allowed) (required with file_type: zip and method: img_csv)
y_columns	array	Column names of columns containing target variable(s). Leave empty to include all other columns (required with file_type: zip and method: img_csv)

200: OK Data Input Successful

{
    "status": "true",
    "message": {
        "id": 1,
        "project": 2,
        "block_id": 1,
        "parent_id": 0,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": ""
    }
}

Python

// Some code

Node

Good to know: Unlike other block requests, the Data Input block isn't permitted to have parent blocks, hence its null value.