Read CSV and send to DB
Validate rows from a CSV file and load them into a PostgreSQL database.
Reads a local cities.csv file, parses it, and loops over each row. Rows with both a City and a State value are logged and inserted into the PostgreSQL CITY table; rows missing either value are logged as warnings. After the loop, it queries the row count of the CITY table and logs the total.
- Local file reading from the ByteChef host
- CSV parsing with a header row
- Per-row validation via a condition
- PostgreSQL inserts for valid rows
- Warning logs for incomplete rows
- Post-load row-count query
- Local filesystem access to cities.csv on the ByteChef host
- A PostgreSQL connection with a CITY table (columns name, country)
Data engineers loading and validating CSV records into a relational database.
- Load the cities.csv file from the local machine.
- Parse the CSV into rows.
- Loop over each row: if both City and State are present, log and insert the row into the PostgreSQL CITY table; otherwise log a warning.
- Query the total record count of the CITY table.
- Log the total count.
MoreDocument OpsTemplates
Retrieves an offices.csv object from AWS S3, reads it into rows, and loops over each row keeping only four selected columns. The reduced rows are collected into a list, written to a new CSV file, and uploaded back to S3 as offices_reduced.csv. The workflow runs on demand.
Deletes a specific sheet from a Google Sheets spreadsheet and logs the result. A minimal, on-demand example workflow.
Lists all sheets in a Google Sheets spreadsheet and logs them. A minimal, on-demand example workflow.
On the first day of every month at 09:00, computes the previous month, creates a new Google Sheet tab for it, and fetches the tracked-time report from Nifty. It loops over each tracked task to retrieve details and compute its duration in hours, writes a row per task, adds a total-hours row, and emails a notification with a link to the spreadsheet.