File & Data Online Tools

Free online file and data converters: CSV to JSON, JSON to CSV, JSON to TypeScript interfaces, XML to JSON, CSV column extractor, CSV cleaner, JSON diff checker, and data storage converter.

Available Tools in File & Data (11)

  • JSON to TypeScript Interface Generator

    Convert raw JSON payloads or API responses into clean, strictly-typed TypeScript interfaces, nested object types, and optional array item definitions.

  • CSV Column Extractor & Filter

    Extract, filter, or reorder specific columns from CSV datasets by header name or 1-based column index with full RFC 4180 quoted field support.

  • XML to JSON Data Converter

    Convert XML documents, RSS feeds, and SOAP payloads into formatted JSON objects while preserving XML attributes (@attributes) and text nodes (#text).

  • File Size & Data Rate Converter

    Convert between decimal SI (KB, MB, GB, TB) and binary IEC (KiB, MiB, GiB, TiB) storage units and estimate download transfer times across network speeds.

  • CSV & Text List Deduplicator

    Remove duplicate rows or items from CSV datasets, email lists, and text files with A-Z, Z-A, or original order preservation and case-sensitivity controls.

  • JSON Object Diff & Comparison

    Compare two JSON objects side-by-side with recursive deep key inspection to highlight added, modified, and deleted properties.

  • CSV ↔ JSON Data Converter

    Bidirectionally convert CSV tables into JSON arrays or transform JSON objects back to CSV with custom comma, semicolon, or tab delimiters.

  • CSV Data Cleaner & Sanitizer

    Sanitize CSV datasets by removing duplicate rows, trimming cell whitespace, stripping blank lines, and normalizing RFC 4180 quotes.

  • Universal Data Formatter & Beautifier

    Beautify, format, validate, or minify JSON payloads, SQL queries, XML documents, and YAML configurations in one unified tool.

  • CSV to JSON Converter

    Convert tabular CSV spreadsheets with header rows into structured, pretty-printed JSON object arrays with full RFC 4180 quoted field support.

  • JSON to CSV Converter

    Flatten JSON arrays and nested objects into RFC 4180 compliant CSV spreadsheet rows using dot-notation column headers.

Frequently Asked Questions About File & Data Formats

What is the IETF RFC 4180 standard for CSV files and why do simple comma splits fail?

RFC 4180 defines the formal specification for Comma-Separated Values (CSV) files. A naive string `.split(',')` corrupts data whenever a text field legitimately contains a comma (such as an address '"100 Main St, Suite 4B"' or a formatted currency '"$1,250.00"'). Under RFC 4180, fields containing delimiters, line breaks (CRLF), or double quotes must be enclosed in double quotes ('"..."'), and literal double quotes inside a quoted field must be escaped by doubling them ('""'). EverySolve's CSV engines implement a state-machine tokenizer that respects RFC 4180 quoting rules.

What is the difference between Decimal SI (KB, MB, GB, TB) and Binary IEC (KiB, MiB, GiB, TiB) data units?

The International System of Units (SI) defines decimal prefixes using base-10 powers of 1,000: 1 KB = 1,000 bytes, 1 MB = 10^6 bytes, 1 GB = 10^9 bytes, and 1 TB = 10^12 bytes. By contrast, the International Electrotechnical Commission (IEC 80000-13) defines binary prefixes using base-2 powers of 1,024 (2^10): 1 KiB = 1,024 bytes, 1 MiB = 1,048,576 bytes, 1 GiB = 1,073,741,824 bytes, and 1 TiB = 1,099,511,627,776 bytes. Storage manufacturers label SSDs and hard drives in decimal SI units, whereas operating systems like Windows often display binary GiB sizes labeled as 'GB', causing a 1 TB drive to appear as 931.32 GB.

How are nested JSON objects flattened into tabular CSV columns without losing data?

Relational spreadsheets (CSV, Excel, SQL tables) are two-dimensional grids of rows and columns, whereas JSON is a hierarchical tree structure. To convert nested JSON objects into CSV without outputting unreadable '[object Object]' cells, EverySolve recursively traverses nested object keys and joins their path segments using dot notation (for example, flattening `{"user": {"address": {"city": "Mumbai"}}}` into the column header `user.address.city`) while scanning the entire array to capture the union of all keys across rows.

How does XML to JSON conversion handle XML attributes alongside text content?

Unlike JSON, XML elements can simultaneously hold key-value attributes on the opening tag and inner text or child elements (e.g., `<item sku="A100">Keyboard</item>`). To achieve lossless conversion, EverySolve maps XML attributes into a dedicated `@attributes` dictionary (`{"@attributes": {"sku": "A100"}}`) and preserves leaf text nodes alongside attributes under the `#text` property (`"#text": "Keyboard"`), while automatically grouping repeated sibling tags into JSON arrays.

What is CSV Formula Injection (Spreadsheet DDE Injection) and how do you prevent it?

CSV Injection occurs when untrusted user input exported into a CSV file begins with spreadsheet formula trigger characters: equals (`=`), plus (`+`), minus (`-`), or at (`@`). When opened in Microsoft Excel, LibreOffice Calc, or Google Sheets, cells starting with these symbols may be executed as active formulas or Dynamic Data Exchange (DDE) commands. Prefixing non-numeric formula-triggering strings with a single quote (`'`) forces spreadsheet software to treat the cell strictly as literal text.

When should I use JSON vs CSV vs XML vs YAML in modern data pipelines?

Use CSV for flat, high-volume tabular datasets, financial ledger exports, and bulk database `COPY` loads where minimal syntax overhead is critical. Use JSON for REST/GraphQL API payloads, NoSQL document stores, and web application state where native JavaScript parsing and nested arrays/objects are required. Use XML for enterprise SOAP services, RSS/Atom feeds, Sitemaps, and document schemas requiring strict XSD validation and namespaces. Use YAML for human-edited DevOps configurations (Docker Compose, Kubernetes manifests, GitHub Actions).

How does structural JSON diffing differ from standard line-by-line text comparison?

A standard line-based text diff compares raw lines of characters, meaning changes in indentation, whitespace, or the order of keys inside a JSON object produce noisy false-positive diffs. Structural JSON diffing parses both inputs into memory, normalizes key ordering at every depth, and compares actual key-value semantics along dot-notation paths (`config.db.host`), isolating true Added, Deleted, and Modified properties.

Are my CSV spreadsheets, JSON payloads, or XML files uploaded to EverySolve servers?

No. All 11 File & Data utilities on EverySolve execute 100% client-side inside your web browser's JavaScript runtime. Your CSV customer lists, proprietary JSON API responses, and XML feeds remain in local volatile RAM and are never transmitted to backend servers, databases, or third-party analytics services.

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