CSV
CSV is a simple file format used to store tabular data, such as a spreadsheet or database.
For CSV connector, YAP ensures the following actions:
- Write files
- Read files
List of fields available for Write files action:
Field | Type |
FileName | String |
Value | String |
Content-type | String |
List of fields available for Read files action:
Field | Type |
Value | String or Array |
On the base of JSON, YAP writes CSV file – correct delimited text strings.
JSON represents an array: array of arrays (for multiple CSV) or array of objects (for one CSV).
Fields
Name | Type | Required | Description |
field | Object | Yes | Selecting field of data to back up and keep during processing. |
variable | String | Yes | Variable for a stored file. |
fileName | String | Yes | Specific system name for a file name. |
delimiter | String | No | The delimiting character.
Default parameter: semicolon (;). |
header | Boolean | No | If a boolean value is true, the first row of parsed data will be interpreted as field names. An array of field names will be returned into metadata, and each row of data will be an object of values entered by field name instead of a simple array. For example, you have two arrays: if the first-array header is true, the second array takes this header; if false, the YAP system automatically adds headers into both arrays. Default parameter: True. |
multiple | Boolean | No | If processing must generate several CSV files in the field. Default parameter: False. |
Example of data input entered in field:
Mode 1 (Array)
Mode 2 (Array of object)
Mode 2 (fields and Data)
// Two-line, comma-delimited file
const data = [
["1-1", "1-2", "1-3"],
["2-1", "2-2", "2-3"]
];
// With implicit header row
// (keys of first object populate header row)
const data = [
{
"Column 1": "foo",
"Column 2": "bar"
},
{
"Column 1": "abc",
"Column 2": "def"
}
];
// Specifying fields and data explicitly
const data = {
"fields": ["Column 1", "Column 2"],
"data": [
["foo", "bar"],
["abc", "def"]
]
};
Example of data stored in data processing pipeline:
Single csv file
Multiple csv files
// For one csv file processing
{
"#csv": {
"key": "1233774C-D28C-479D-9CE7-12E4F8A7361A-2019062708393434.csv",
"ETag": "\"c1ba1b0640a6f6489ae213a5e116\"",
"name": "Transactions-3last",
"urlTmp": "https://storage.youngapp.co/1233774C-D28C-479D-9CE7-12E4F361A-2019062708393434.csv",
"fileName": "data.csv",
"extension": "csv",
"subDirectory": "0612900020312808"
}
}
// For multiple csv file processing. the files is stored in array
{
"#csv": [{
"key": "1233774C-D28C-479D-9CE7-12E4F8A7361A-2019062708393434.csv",
"ETag": "\"c1ba1b0640a6f6489ae213a5e116\"",
"name": "Transactions-3last",
"urlTmp": "https://storage.youngapp.co/1233774C-D28C-479D-9CE7-12E4F361A-2019062708393434.csv",
"fileName": "data.csv",
"extension": "csv",
"subDirectory": "0612900020312808"
}]
}
Delimited data can be parsed from strings or files.
Data input
Name | Type | Required | Description |
field | Object | Yes | Select field to read CSV |
variable | String | Yes | Variable for stored data |
mode | Number | Yes | Type of structure data |
Data output
Mode 1 (Array)
Mode 2 (Array of object)
Mode 2 (fields and Data)
// Two-line, comma-delimited file
{
"data": [
["1-1", "1-2", "1-3"],
["2-1", "2-2", "2-3"]
]
};
// With implicit header row
// (keys of first object populate header row)
{
"data": [
{
"Column 1": "foo",
"Column 2": "bar"
},
{
"Column 1": "abc",
"Column 2": "def"
}
]
};
// Specifying fields and data explicitly
{
"data": {
"fields": ["Column 1", "Column 2"],
"data": [
["foo", "bar"],
["abc", "def"]
]
}
};
Before setup, please check that you have granted to YAP the permission to send notification to your CSV account. For this, sign in to CSV and authorize the permissions requested by YAP.
Questions?
We're always happy to help with any issues you might have!
Send us an email to [email protected] or request the demo with our sales team!
Last modified 3yr ago