I'm building ImportCSV, a self-hosted CSV importer that makes CSV onboarding easier for SaaS apps. Here is a quick demo: https://screen.studio/share/8STvmqkq
CSVs are like the cockroach of data transfer—they're everywhere and refuse to go away. At my last startup, we realized spreadsheets and Excel files were deeply embedded across our users' workflows, acting like glue between different systems, even as APIs became more common.
But handling CSV imports turned out to be surprisingly painful. We faced weird issues like strange encodings, unexpected delimiters, and huge files that crashed our system. Each failed CSV import frustrated both us and our users.
Existing tools weren't much help—they were either overly complex, too expensive, or difficult to integrate. Eventually, we built our own tool internally to handle these challenges.
We've cleaned it up and open-sourced it as ImportCSV to hopefully save others from similar headaches. It’s:
- Easy to deploy (`docker compose up`)
- Simple to use (fix errors on the spot)
- Smart (auto-matching columns like "DoJ" → `date_of_joining`)
aray07•9mo ago
I'm building ImportCSV, a self-hosted CSV importer that makes CSV onboarding easier for SaaS apps. Here is a quick demo: https://screen.studio/share/8STvmqkq
CSVs are like the cockroach of data transfer—they're everywhere and refuse to go away. At my last startup, we realized spreadsheets and Excel files were deeply embedded across our users' workflows, acting like glue between different systems, even as APIs became more common.
But handling CSV imports turned out to be surprisingly painful. We faced weird issues like strange encodings, unexpected delimiters, and huge files that crashed our system. Each failed CSV import frustrated both us and our users.
Existing tools weren't much help—they were either overly complex, too expensive, or difficult to integrate. Eventually, we built our own tool internally to handle these challenges.
We've cleaned it up and open-sourced it as ImportCSV to hopefully save others from similar headaches. It’s:
- Easy to deploy (`docker compose up`)
- Simple to use (fix errors on the spot)
- Smart (auto-matching columns like "DoJ" → `date_of_joining`)
- Flexible with different column schemas
What it can do today:
- Handles multiple file types (CSV, XLS, XLSX, TSV)
- Spreadsheet-style user interface
- Sends validated data directly to your API
Next up:
- Better handling of large files with streaming
- AI-powered data cleaning and validation
- More integration options (databases, webhooks)
I'd love your feedback or any challenging CSV stories you've faced!