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

NameTypeDescription

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)

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

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

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