Skip to main content

Data Hooks

Data Hooks allow you to validate user uploads during the interactive import process, so that your users can address any invalid data before it's imported into your app. When configuring your importer in the UseCSV admin, you can choose which columns to enable Data Hooks for.

To use Data Hooks you'll need to implement two callbacks: onRecordsInitial and onRecordEdit. They will pass you the uploaded data (for the columns Data Hooks is enabled for) and allow you to return errors to the user.

onRecordsInitial: Function

onRecordsInitial callback function is triggered after the user uploads a file and once the column matching is completed. Data from the columns with Data Hook enabled will be sent to your frontend, so you can run your own validation and return rows with errors if any and custom error messages to be shown to the user. Data will be sent in batches of 1000 rows.

onRecordsInitial callback function parameters

type ParamsType = {
uploadId: string;
fileName: string;
importerId: string;
batch: {
index: number;
count: number;
totalRows: number;
};
user?: Record<string, string | number> | null;
metadata?: Record<string, string | number> | null;
rows: Array<{
row: number;
data: {
[columnName: string]: {
value: string | number;
isValid: boolean;
};
};
}>;
};
// onRecordsInitial parameters example
{
uploadId: 334,
fileName: "data.csv",
importerId: "123-456-789"
batch: {
index: 1;
count: 1;
totalRows: 3;
},
user: {
userId: "12345",
},
metadata: {
anotherId: "1",
},
rows: [{
row: 1,
data: {
email: {
value: "Mari@gmail.com",
isValid: true
}
age: {
value: 5,
isValid: true
}
}
},
{
row: 2,
data: {
email: {
value: "John@gmail.com",
isValid: true
},
age: {
value: "not a number",
isValid: false
}
}
} {
row: 3,
data: {
email: {
value: "invalid@email@.com",
isValid: false
},
age: {
value: 35,
isValid: true
}
}
}
]
}
  • uploadId: upload ID.
  • fileName: uploaded file name.
  • importerId: importer key that can be found in the admin panel.
  • batch: json object of batch details, with keys of:
    • index: number of batch starting from 1.
    • count: number of total batches expected to be received.
    • totalRows: number of total rows per file.
  • user json object of user object if provided.
  • metadatajson object of metadata object if provided.
  • rows: array of json objects of rows, with keys of:
    • row: number of row in the uploaded file starting from 1.
    • data: json object of columns:
      • columnName: array of json objects of the configured columns, with keys of:
        • value: value of cell.
        • isValid: boolean validation result according to the validation format configured for each column in admin panel when the column was created.

Return errors

type ResponseType = Array<{
row: number;
data: {
[columnName: string]: Array<{
message: string;
level: "error";
}>;
};
}>;
// Example of returned errors
return Promise.resolve([
{
row: 1,
data: {
email: [
{
message: "Email already exists", // first error message
level: "error",
},
{
message: "Invalid email", // second error message (optional)
level: "error",
},
],
age: [
{
message: "Age must be 18 or above",
level: "error",
},
],
},
},
{
row: 2,
data: {
age: {
message: "Age must be a number",
level: "error",
},
},
},
{
row: 3,
data: {
email: [
{
message: "Invalid email",
level: "error",
},
],
},
},
]);
  • row: required row number already included in the recieved data.
  • data: json object of columns:
    • columnName: array of json objects with keys of: message and level. At lease one column should be included in the response.
      • message: custom error message shown to user.
      • level: currently the only implemented level is error but more will be added soon.

onRecordEdit: Function

onRecordEdit callback function is triggered after any of the cells is edited in the Match Columns step. The edited row will be sent to your frontend, so you can run your own validation and return errors if any and custom error messages to be shown to the user.

onRecordEdit callback function parameters

type ParamsType = {
uploadId: string;
fileName: string;
importerId: string;
user?: Record<string, string | number> | null;
metadata?: Record<string, string | number> | null;
row: {
row: number;
data: {
[columnName: string]: {
value: string | number;
isValid: boolean;
};
};
};
};
// onRecordEdit parameters example
{
uploadId: 334,
fileName: "data.csv",
importerId: "123-456-789"
user: {
userId: "12345",
},
metadata: {
anotherId: "1",
},
row: {
row: 2,
data: {
email: {
value: "invalid@email@.com",
isValid: false
},
age: {
value: 35,
isValid: true
}
}
}
}
  • uploadId: upload ID.
  • fileName: uploaded file name.
  • importerId: importer key that can be found in the admin panel.
  • user json object of user object if provided.
  • metadatajson object of metadata object if provided.
  • row: json object of edited row, with keys of:
    • row: number of row in the uploaded file.
    • data: json object of columns:
      • columnName: array of json objects of the configured columns, with keys of:
        • value: value of cell.
        • isValid: boolean validation result according to the validation format configured for each column in admin panel when the column was created.

Return errors

type ResponseType = {
row: number;
data: {
[columnName: string]: Array<{
message: string;
level: "error";
}>;
};
};
//  Example of returned errors
return Promise.resolve({
row: 2,
data: {
email: [
{
message: "Invalid email", // first error message
level: "error",
},
{
message: "Email does not exist", // second error message (optional)
level: "error",
},
],
},
});
  • row: required row number already included in the recieved data.
  • data: json object of columns:
    • columnName: json object with keys of: message and level. At lease one column should be included in the response.
      • message: custom error message shown to user.
      • level: currently the only implemented level is error but more will be added soon.