How to read a CSV file with a custom separator like semicolon in rapidcsv?

Use SeparatorParams with the desired character when constructing the Document, as demonstrated in the custom separator example with ';' for semi-colon files.

Rapidcsv vs fast-cpp-csv-parser which is better for performance?

Fast-cpp-csv-parser is optimized for speed and memory efficiency, while rapidcsv focuses on simplicity and flexibility. Choose based on whether you prioritize ease-of-use or raw performance.

How to handle empty cells or invalid numbers in rapidcsv without exceptions?

Configure ConverterParams to enable default values, setting it to true to use NaN for floats or zero for integers instead of throwing errors, as described in the section on reading files with invalid numbers.

Can rapidcsv parse CSV data directly from a string without a file?

Yes, it supports input from streams or strings via std::stringstream, allowing in-memory parsing as shown in the example reading CSV from a const std::string.

How to convert CSV rows to custom C++ structs using rapidcsv?

Implement custom conversion functions for your struct type, either globally or per call, as illustrated in the example with MyStruct and ConvMyStruct.

Does rapidcsv support UTF-16 encoded CSV files?

Yes, but only if HAS_CODECVT is defined and the system supports it; otherwise, UTF-8 is the default, with automatic detection for UTF-16 LE/BE when enabled.

Open-Awesome

rapidcsv

BSD-3-ClauseC++v8.92

A header-only C++11 CSV parser library with easy-to-use API for reading and writing CSV files.

GitHub

1.1k stars196 forks0 contributors

What is rapidcsv?

Rapidcsv is a C++ library for parsing and manipulating CSV (Comma-Separated Values) files. It provides an easy-to-use API for reading and writing CSV data, supporting various data types, custom separators, and flexible header configurations. The library solves the problem of handling CSV files in C++ projects with minimal dependencies and a straightforward interface.

Target Audience

C++ developers who need to read or write CSV files in their applications, particularly those working with data processing, analytics, or file I/O tasks.

Value Proposition

Developers choose Rapidcsv for its simplicity, header-only design, and ease of integration. It offers a clean API without the complexity of larger parsing libraries, making it ideal for projects that require lightweight CSV handling with support for modern C++ standards.

Overview

C++ CSV parser library

Use Cases

Best For

Parsing financial or scientific data stored in CSV format
Reading configuration or data files in C++ applications
Converting CSV data to C++ vectors or custom data structures
Handling CSV files with custom separators (e.g., semicolons)
Processing CSV data from streams or strings in memory
Quick prototyping of CSV-based data processing tools

Not Ideal For

High-performance applications parsing multi-gigabyte CSV files with strict memory constraints
Projects requiring real-time streaming or incremental parsing without loading entire files into memory
Systems needing built-in CSV schema validation, data transformation, or complex relational operations

Pros & Cons

Pros

Header-Only Simplicity

Single-file inclusion eliminates separate compilation, making integration trivial—just copy rapidcsv.h to your project as per the installation guide.

Flexible Header Handling

Supports column headers, row headers, both, or none via LabelParams, enabling versatile data access patterns as shown in the multiple examples.

Custom Type Conversion

Allows global or per-call overrides for any data type, with examples for custom structs and fixed-point numbers, enhancing integration flexibility.

Locale-Independent Parsing

Optional locale-independent numeric parsing via ConverterParams ensures consistent float handling across systems, avoiding regional formatting issues.

Cons

In-Memory Parsing Limitation

Loads entire CSV into memory, lacking true streaming support for large files, which can be inefficient for datasets exceeding available RAM.

Basic Error Handling Defaults

Throws exceptions on invalid numeric data by default, requiring explicit ConverterParams configuration for graceful fallbacks, which adds complexity.

Limited Advanced CSV Features

Missing support for multi-line quoted cells or complex escaping rules beyond basic auto-quote removal, as noted in the handling of quoted cells section.

Frequently Asked Questions

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