object-symbols-parser
A command-line tool that reads symbol tables from object files and generates a sorted spreadsheet report of symbols. This is especially useful in embedded development when optimizing code size and memory usage is critical.
Usage
Object File
If your binary fails to compile due to code space constraints, this tool helps you identify large symbols by reading one or more object files and generating a sorted symbol table spreadsheet.
object_symbols_parser -f src/FileSystem.o -f src/cpp_config.o -f src/main.o -o /tmp/out.xlsx
ELF/AXF File
You can also provide a single ELF or AXF binary file:
object_symbols_parser -f project.axf -o /tmp/out.xlsx
Output
The tool aggregates symbol information into a Pandas DataFrame and writes it to an Excel .xlsx file. By default, the symbols are sorted by section type and size, so you can quickly identify the largest entries consuming your code or data space.
Requirements
- Python packages: click, pandas
- GNU Binutils (objdump must be installed and in your system path or toolchain directory)
Metadata
Release files for object-symbols-parser 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| object_symbols_parser-0.1.2.tar.gz | 130.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| object_symbols_parser-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 136.9 kB
Release files / object_symbols_parser-0.1.2.tar.gz
| Download URL | object_symbols_parser-0.1.2.tar.gz |
|---|---|
| Size | 130.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / object_symbols_parser-0.1.2-py3-none-any.whl
| Download URL | object_symbols_parser-0.1.2-py3-none-any.whl |
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| Size | 6.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 27, 2025.
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