3 dépôts
Asynchronous iteration over spreadsheet rows to process large files without full memory loading.
Distinct from Asynchronous Stream Processors: Distinct from Asynchronous Stream Processors: specifically applied to the row-by-row traversal of spreadsheet workbooks.
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ExcelJS is a Node.js spreadsheet engine and manipulation library used for reading, writing, and modifying XLSX and CSV files. It functions as a formatting tool and asynchronous streaming parser for generating complex workbooks containing formulas, rich text, and custom styles. The library is distinguished by its ability to process large datasets using asynchronous data streaming and incremental processing, which minimizes memory usage during data extraction and file generation. Its capability surface covers comprehensive data management, including structured tables, named ranges, and cell da
Allows reading large workbooks using asynchronous iteration to process rows without loading the entire file into memory.
NPOI is a pure .NET library for reading and writing Microsoft Office files in both legacy binary (.xls) and modern OpenXML (.xlsx, .docx) formats, operating entirely without requiring Microsoft Office or COM interop. It runs on Windows and Linux under .NET Standard and .NET Framework runtimes, using only managed code to parse and generate Office documents. The library provides comprehensive spreadsheet capabilities, including creating, editing, and reading Excel workbooks in both .xls and .xlsx formats, with support for cell formatting, styles, and formulas. It includes a streaming row-by-row
Reads large .xlsx files by iterating rows from the XML sheet part without loading the entire workbook into memory.
Apache Fesod is a lightweight Java library that wraps Apache POI to provide a streaming API for reading and writing large Excel files. Its core identity is a low-memory spreadsheet processor that prevents out-of-memory errors by handling data row by row, never loading an entire document into memory at once. The library distinguishes itself through a listener-driven event model that fires row-level events to user code as each row is parsed, enabling incremental processing. It also includes an object mapping layer that maps spreadsheet rows directly to Java objects using configurable column map
Processes Excel files with millions of rows using a listener-based streaming approach for Java applications.