{"id":1068,"date":"2026-07-29T09:00:00","date_gmt":"2026-07-29T00:00:00","guid":{"rendered":"https:\/\/blog.hancom.com\/python-hwp-hwpx-text-extraction-pyhwp-guide\/"},"modified":"2026-07-31T11:13:20","modified_gmt":"2026-07-31T02:13:20","slug":"python-hwp-hwpx-text-extraction-pyhwp-guide","status":"publish","type":"post","link":"https:\/\/blog.hancom.com\/en\/python-hwp-hwpx-text-extraction-pyhwp-guide\/","title":{"rendered":"How to Extract HWP Text with Python: From pyhwp Installation and Usage to Limitations and Alternatives"},"content":{"rendered":"\n

It is more common than you might think to experience frustration while attempting to extract HWP\/HWPX text using Python. You might install pyhwp only to encounter errors in a Linux environment, find that table data is not extracted correctly, or see code that worked fine on a local PC freeze the moment it is uploaded to a server. We will take a step-by-step look at the definition, installation, and usage of pyhwp, identify where its limitations lie, and explore realistic alternatives for professional use. <\/p>\n\n

What is pyhwp? Basic Concepts and Installation <\/strong><\/h2>\n\n

pyhwp is an open-source Python library that extracts text by interpreting the binary structure of HWP files. Since it is a pre-release based on Python 2.7, additional configuration is required for Python 3 environments. <\/p>\n\n

Definition and Core Features of pyhwp<\/strong><\/h3>\n\n

According to AWS<\/a>, Python is a widely used language for web development, data science, and machine learning, with over 137,000 libraries available for various applications.<\/p>\n\n

pyhwp is the library responsible for HWP file processing within this ecosystem, supporting HWP version 5.0 and above, and is distributed via PyPI. Internally, it works by opening streams with olefile, decompressing them with zlib, and then reading the text. Because it parses the file directly, it functions without the need to install the Hancom Office (Hangul) program. However, as it is specialized for text extraction, it does not support cell structures within tables, images, or paragraph hierarchies. <\/p>\n\n

pyhwp Installation and Documentation Usage<\/strong><\/h3>\n\n

To install pyhwp, use the command: pip install –user –pre pyhwp.<\/p>\n\n

The –pre flag is required instead of a standard pip install pyhwp because pyhwp is distributed as a pre-release beta without an official release. The –user flag is used to install the package in the user’s home directory without administrator privileges. Since there have been no official updates for a long time, compatibility issues may arise in modern Python environments. <\/p>\n\n

pip install –user –pre pyhwp # pyhwp<\/td><\/tr><\/tbody><\/table><\/figure>\n\n

\ud83d\udca1 If you are running within a virtual environment (virtualenv), omit the –user option and install using pip install –pre pyhwp. Since virtual environments already install packages in an isolated space, the –user option may cause a conflict and result in a “Can not perform a ‘–user’ install” error. <\/p>\n\n

Windows requires setuptools and Lxml separately, while Linux requires a setuptools-based build environment and optionally pycrypto. Since Python 2.7 reached its official end-of-life on January 1, 2020, according to PEP 373, compatibility issues may occur in Python 3 environments. <\/p>\n\n

After installation, you can check the support range and basic usage in the official documentation (pythonhosted.org\/pyhwp).<\/p>\n\n

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How to Extract HWP\/HWPX Text with Python<\/strong><\/h2>\n\n

When extracting HWP text with Python, you can use the hwp5txt command-line tool from pyhwp. However, the situation is different for HWPX. There are no lightweight open-source tools comparable to pyhwp that directly parse HWPX files, and pyhwpx, often mentioned as an alternative, is not a direct file parser but operates in an entirely different way. <\/p>\n\n

Basic pyhwp Usage: Reading HWP Files and Extracting Text <\/strong><\/h3>\n\n

The simplest way to extract text with pyhwp is by using the hwp5txt command-line tool.<\/p>\n\n

hwp5txt sample.hwp > sample.txt<\/td><\/tr><\/tbody><\/table><\/figure>\n\n

Specifying the file path will convert and output the text. You can also call this via subprocess within a Python script to connect it to an automated pipeline. While plain text is extracted well, text within tables is output as flat text without cell structures. This limitation becomes particularly evident in documents with many tables, such as official government documents. <\/p>\n\n

\ud83d\udca1 To gain a deeper understanding of the internal structure of HWP\/HWPX files, please refer to the technical blog prepared by the Hancom development team.<\/p>\n\n

\ud83d\udcc3 Hancom Tech, Hangul Document File Format: Parsing HWP Format via Python (1)<\/a><\/p>\n\n

Python HWPX Text Extraction: Why is pyhwpx Not a Parser? <\/strong><\/h3>\n\n

HWP is binary-based, while HWPX is XML-based, which theoretically makes it easier to create a parser that reads the structure directly. However, pyhwpx, which is often mistaken for a dedicated HWPX parser due to its name, is not actually that kind of library. <\/p>\n\n

pyhwpx does not open and interpret files directly; instead, it is an automation library that runs the Hancom Office program installed on a PC via pywin32 (COM) to control the program to open documents and export text\/table data. Therefore, a Windows environment with Hancom Office installed is mandatory, making its operating principle fundamentally different from pyhwp, which works with just the file. Due to this approach, both libraries have clear limitations for tasks like RAG that require unattended processing of large volumes of documents on a server. <\/p>\n\n

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What Causes Failures in HWP\/HWPX Text Extraction with Python?<\/strong><\/h2>\n\n

Most issues stem from pyhwp’s Python version and Linux build compatibility, or the fact that pyhwpx is an automation tool that remotely controls Hancom Office rather than being a parser, necessitating Windows and a Hancom Office installation. These issues are often compounded by a lack of support for structuring tables and images. <\/p>\n\n

Reasons Why pyhwp Fails in Python Versions and Linux Environments<\/strong><\/h3>\n\n

pyhwp officially supports Python 2.7 and 3.5\u20133.8. However, since the last release was in 2020 (0.1b15), environments using Python 3.9 or higher are outside the official support range, which may lead to compatibility issues. <\/p>\n\n

Linux servers require a setuptools-based build environment, and errors frequently occur when running on modern Python versions (3.9+). Rather than trying to solve each error individually, it may be more efficient to reconsider the choice of tool. pyhwp is an open-source project, not based on an official SDK, which can lead to limitations in supporting the latest formats and processing structural information. <\/p>\n\n

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Why Table and Image Data Cannot Be Extracted with pyhwp<\/strong><\/h3>\n\n

Because pyhwp parses based on text records, it cannot extract cell structures within tables or contextual information from images.<\/p>\n\n

In the HWP format, table data is stored in an extended control record structure separate from the text. pyhwp does not have the logic to process these records separately, so it cannot extract structures at the cell level. This structure can be confirmed in the HWP format analysis provided by the Hancom development team. <\/p>\n\n

According to the PubTables-1M study<\/a>, accurate extraction of tables is difficult without TSR (Table Structure Recognition) technology due to complexities such as merged cells and multi-column headers. Ultimately, a tool equipped with TSR functionality is required. <\/p>\n\n

You can find more details in the technical blog along with the code.<\/p>\n\n

\ud83d\udcc3 Hancom Tech, Hangul Document File Format: Parsing HWP Format via Python (2)<\/a><\/p>\n\n

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Types of Python HWP\/HWPX Libraries and Selection Criteria<\/strong><\/h2>\n\n

Python HWP\/HWPX libraries are divided into local automation methods (pyhwp, pyhwpx), direct implementation methods (olefile), cloud API methods, and on-premise solutions. The appropriate tool depends on the purpose and environment.<\/p>\n\n

Comparison of Python HWP\/HWPX Libraries at a Glance<\/strong><\/h3>\n\n

There are four main ways to process HWP\/HWPX with Python. While pyhwp parses files directly, pyhwpx is an automation tool for Hancom Office, meaning their prerequisites are entirely different. If you require table structuring, server deployment, or air-gapped environment support, the options change completely. <\/p>\n\n

<\/div>\n\n
Category<\/td>Operational Method<\/td>Hancom Office Installation<\/td>Text Extraction<\/td>Table Structuring<\/td>Hierarchical Structure<\/td>Air-gapped Network<\/td>Mass Batch Processing<\/td>Cost<\/td><\/tr>
pyhwp<\/td>Direct File Parsing <\/td>Not Required<\/td>Possible<\/td>Not Supported<\/td>Not Supported<\/td>Possible<\/td>Difficult<\/td>Free<\/td><\/tr>
pyhwpx<\/td>Hancom Office Automation (COM) <\/td>Required<\/td>Possible<\/td>Limited (GUI Dependent) <\/td>Not Supported<\/td>Possible<\/td>Difficult<\/td>Free<\/td><\/tr>
olefile Direct Parsing<\/td>Direct Parsing (Implementation Required) <\/td>Not Required<\/td>Manual Implementation<\/td>Manual Implementation<\/td>Manual Implementation<\/td>Possible<\/td>Manual Design<\/td>Free<\/td><\/tr>
Cloud API<\/td>External Server Processing <\/td>N\/A<\/td>Possible<\/td>Possible<\/td>Partial<\/td>Impossible<\/td>Possible<\/td>Paid<\/td><\/tr>
Hancom Data Loader<\/td>Direct Original Parsing <\/td>N\/A<\/td>Possible<\/td>Possible<\/td>Possible<\/td>Possible<\/td>Possible<\/td>Inquire Separately<\/td><\/tr><\/tbody><\/table><\/figure>\n\n
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Criteria for Selecting HWP\/HWPX Libraries Based on Purpose and Environment<\/strong><\/h3>\n\n

If the goal is simple text extraction or document editing, pyhwp or pyhwpx is sufficient. However, if you need table structuring, Linux server deployment, mass processing, or an air-gapped environment, you should consider a parsing solution. <\/p>\n\n

<\/p>\n\n

\u2705 Small-scale processing\/simple text extraction in a Windows environment \u2192 pyhwp \/ pyhwpx<\/p>\n\n

\u2705 Linux server deployment required \u2192 Consider on-premise solutions or cloud APIs<\/p>\n\n

\u2705 Table\/image structuring required \u2192 TSR-supported solution required<\/p>\n\n

\u2705 Air-gapped\/Public\/Financial environments \u2192 On-premise is mandatory<\/p>\n\n

If two or more of the above apply \u2192 We recommend considering a parsing solution<\/a>.<\/strong><\/p>\n\n

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\ud83d\udca1 If you need to extract tables and hierarchical structures during the document pre-processing stage of a RAG pipeline, please check the actual implementation first with the Hancom Data Loader demo.<\/p>\n\n

\ud83d\udc49 Go to Hancom Data Loader Demo<\/a><\/strong><\/p>\n\n

Python HWP\/HWPX Automation: Limitations of Library Methods and Realistic Alternatives<\/strong><\/p>\n\n

While library methods are sufficient at the single-file level, their practical limitations become apparent when server deployment, mass processing, and air-gapped operations are required.<\/p>\n\n

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Limitations of Library Methods in Large-scale and Batch Processing<\/strong><\/h3>\n\n

It is common for pyhwp code that worked well on a personal PC to fail on a server due to differences in the execution environment, or for performance to slow down and errors to become frequent when the number of files to process increases to hundreds.<\/p>\n\n

Since pyhwp is not actively maintained, it is difficult to respond to HWP\/HWPX format version updates, and operational features such as parallelization and queue management for mass batch processing must be implemented manually. <\/p>\n\n

Similarly, pyhwpx is structurally unsuitable for processing large volumes of files in parallel because it controls Hancom Office programs one by one. Hancom Data Loader is a tool that has already internalized and solved these operational burdens.<\/p>\n\n

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What Are the Realistic HWP\/HWPX Parsing Alternatives for Server and Air-gapped Environments?<\/strong><\/h3>\n\n

Cloud API methods cannot be used in public, financial, or legal air-gapped environments because documents must be transmitted to an external server. In these cases, a Docker REST API-based on-premise parsing solution is a realistic alternative. <\/p>\n\n

By calling the API with Python’s requests library, it can be seamlessly integrated into existing Python pipelines. It operates entirely within an internal network without an external connection and can run using only CPU resources.<\/p>\n\n

Hancom Data Loader is a document parsing solution that converts HWP, HWPX, PDF, and OOXML into structured data. By internalizing DLA (Document Layout Analysis), OCR (Optical Character Recognition), and TSR into an integrated pipeline, it reduces the burden of the document pre-processing stage when building RAG pipelines. <\/p>\n\n

* The Image Captioning feature is currently in the PoC stage, and the commercial release schedule will be announced later.<\/p>\n\n

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Frequently Asked Questions about HWP\/HWPX Text Extraction with Python<\/strong><\/h2>\n
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Q1. What is the difference between pyhwp and pyhwpx?<\/strong><\/h3>\n
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pyhwp is a parser that directly interprets the binary structure of HWP files, so it works without the Hancom Office program. In contrast, pyhwpx is not a parser but an automation tool that remotely controls an actual installed Hancom Office program via Python to open documents and retrieve text. Therefore, a Windows environment with Hancom Office installed is required to use pyhwpx. <\/p>\n\n<\/div>\n<\/div>\n

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Q2. Is there a way to parse HWP\/HWPX files on a Linux server?<\/strong><\/h3>\n
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Since pyhwp is based on Python 2.7, version and build compatibility issues often occur in Linux environments. pyhwpx cannot be run on Linux servers because it remotely controls Hancom Office installed on Windows. For stable parsing on a Linux server, an on-premise method that completes processing within the server without external transmission is a realistic alternative, and Hancom Data Loader is suitable for such environments. <\/p>\n\n<\/div>\n<\/div>\n

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Q3. Can HWP\/HWPX text extracted with Python be used directly in a RAG pipeline?<\/strong><\/h3>\n
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Text extracted with pyhwp is provided as flat text with document structure information removed, which limits its direct use in RAG pipelines. RAG requires the hierarchical structure and context of a document to be maintained for accurate chunking into semantic units. If structural information is lost, different content may be grouped into a single chunk, or related information may be separated, reducing search accuracy. Therefore, preserving paragraph hierarchies is as important as text extraction for improving chunking quality. Hancom Data Loader, equipped with a Level Inference Engine, automatically tags paragraph hierarchies to support semantic-based chunking. <\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Have You Considered the Next Steps for Python HWP\/HWPX Text Extraction?<\/strong><\/h2>\n\n

As we have seen, pyhwp and pyhwpx are sufficient for extracting text from single files. However, limitations emerge when requirements include preserving table or paragraph hierarchies, Linux server deployment, mass processing, or air-gapped environments. Feeding flat text directly into a RAG pipeline makes it difficult to improve search accuracy. <\/p>\n\n

The problem is that although HWP\/HWPX are the standards for Korean public, financial, and legal documents, the lack of tools to parse original files directly often leads to bypass processing by converting them to PDF, which results in the loss of table structures and document hierarchy information. Cloud APIs are not an option for air-gapped networks due to external transmission. The Korean document environment requires a solution designed from the ground up with these conditions in mind. <\/p>\n\n

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\ud83d\udda5\ufe0f<\/strong>Hancom Data Loader<\/strong><\/a><\/strong><\/h3>\n\n

Hancom Data Loader<\/a> is a document parsing solution that converts HWP, HWPX, PDF, and OOXML into structured data. it can reduce information loss issues that occur during the document pre-processing stage of RAG pipeline construction. <\/p>\n\n

\u2705 Minimizes PDF conversion loss by directly parsing original HWP\/HWPX based on HWP SDK core technology <\/p>\n\n

\u2705 Processes DLA, TSR, and OCR in a single pipeline without external dependencies<\/p>\n\n

\u2705 Ensures chunking quality by automatically tagging the hierarchical structure of Korean official documents and laws using a Level Inference Engine<\/p>\n\n

\u2705 Operates without external transmission even in air-gapped environments through complete on-premise internalization via Docker REST API<\/p>\n\n

\u2705 Secured supply references for public, financial, and legal institutions with GS certification<\/p>\n\n

If you have been stuck with pyhwp, we recommend checking your environment for the ability to extract tables and hierarchies along with text.<\/p>\n\n

\ud83d\udc49 <\/a>Explore Hancom Data Loader<\/a><\/p>\n\n

\ud83d\udc49 Inquire about Hancom Data Loader implementation<\/a><\/p>\n\n

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References<\/strong><\/p>\n\n

    \n
  1. AWS<\/strong><\/a>, “What is Python?”<\/li>\n\n\n\n
  2. Python Software Foundation<\/strong><\/a>, “PEP 373 \u2013 Python 2.7 Release Schedule”<\/li>\n\n\n\n
  3. pyhwp Official Documentation<\/strong><\/a><\/li>\n\n\n\n
  4. pyhwp Converter Documentation<\/strong><\/a><\/li>\n\n\n\n
  5. pyhwp PyPI Page<\/strong><\/a><\/li>\n\n\n\n
  6. Hancom Tech<\/strong><\/a>, “Hangul Document File Format: Parsing HWP Format via Python (1)”<\/li>\n\n\n\n
  7. Hancom Tech<\/strong><\/a>, “Hangul Document File Format: Parsing HWP Format via Python (2)”<\/li>\n\n\n\n
  8. Hancom<\/strong><\/a>, “Hangul Document File Format 5.0 revision 1.3”<\/li>\n\n\n\n
  9. Smock et al.<\/strong>, <\/a>“PubTables-1M: Towards Comprehensive Table Extraction from Unstructured Documents”<\/li>\n\n\n\n
  10. Lewis et al.<\/strong>,<\/a> “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”<\/li>\n\n\n\n
  11. Liu et al.<\/strong>, <\/a>“Lost in the Middle: How Language Models Use Long Contexts”<\/li>\n<\/ol>\n\n

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    What is pyhwp, and where does it fall short? We have summarized everything from pyhwp installation and usage for HWP\/HWPX text extraction to the limitations of Linux environments, library comparison and selection criteria, and practical alternatives for air-gapped environments. <\/p>\n","protected":false},"author":2,"featured_media":1069,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-1068","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ax-insight"],"_links":{"self":[{"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/posts\/1068","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/comments?post=1068"}],"version-history":[{"count":6,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/posts\/1068\/revisions"}],"predecessor-version":[{"id":1176,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/posts\/1068\/revisions\/1176"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/media\/1069"}],"wp:attachment":[{"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/media?parent=1068"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/categories?post=1068"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.hancom.com\/en\/wp-json\/wp\/v2\/tags?post=1068"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}