Every business has data in spreadsheets. Your app should speak CSV.
CSV import and export is a basic SaaS expectation. Users want to pull data out for analysis, import records from spreadsheets, and migrate data from other systems. Getting import right requires validation, error handling, and background processing for large files.
Application that doesn't support CSV import/export — users are manually copying data, or the import feature exists but fails on large files or gives unhelpful errors
CSV import is harder than export. The common failure modes:
No validation before import. The user uploads 10,000 rows; row 5,000 has a missing required field. Either the entire import fails (all 4,999 successful rows lost) or the import partially succeeds (inconsistent state). Fix: validate all rows before processing any, or process transactionally with rollback.
Unhelpful error messages. "Row 5,000 failed" without telling the user which column or why. Fix: per-row error reporting with column context.
Blocking the request. 10,000-row CSV takes 30 seconds to process. The HTTP request times out. Fix: background job processing with a progress indicator.
Column mapping assumptions. The app expects column headers to match exactly. Users import files with different headers. Fix: column mapping step that lets users match their headers to the expected fields.
No duplicate handling. Importing the same file twice creates duplicate records. Fix: upsert logic with a unique identifier field, or duplicate detection before import.
The import architecture:
- User uploads CSV file (stored in S3)
- First-pass validation: column presence, basic format checks, row count
- Display mapping UI if headers don't match expected format
- Enqueue background job for processing
- Worker processes rows in batches (not all at once — avoids memory limits)
- Progress updates via polling or WebSocket
- Completion notification with summary (rows imported, rows failed, download of failed rows)
Robust CSV import (with validation, error reporting, and background processing for large files) and export (all records or filtered results) with appropriate column mapping
Upload endpoint
with S3 storage for large files
Validation layer
with per-row error reporting
Column mapping UI
for flexible header matching
Background processing
for large imports
Import results
with downloadable error report
Export endpoint
(full dataset or filtered) as CSV download
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Robust CSV import (with validation, error reporting, and background processing for large files) and export (all records or filtered results) with appropriate column mapping
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
CSV import/export scope is defined by the data types and validation requirements. Fixed-price build.
Questions, answered.
With background processing: unlimited in principle. Practical limit depends on the row processing speed. 100,000 rows typically takes 1-5 minutes; provide a progress indicator.
Yes — xlsx libraries (SheetJS) parse Excel files and convert to the same row format. Add to the scope.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.