rpy2-robjects
Python interface to the R language (embedded R)
Decision gist · record as of 2026-08-14
Yes, if you need to call R from Python and have R already installed on your system. The package is actively maintained, has low install friction, and carries no known vulnerabilities. The GPLv2+ copyleft license requires careful consideration if you plan to distribute your code—ensure your project's license is compatible. The main blocker is the external R dependency and potential library path configuration on non-standard R installations.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- R must be installed and accessible on the system; if R is not in a standard location, LD_LIBRARY_PATH may need to be configured before importing.
- Low install friction with a pure-wheel distribution.
- Actively maintained with recent commits and releases.
License · maintenance · safety
GPLv2+ (copyleft) — Released under GPLv2+, a copyleft license. Any code that links or distributes this package must comply with GPL terms, including potential source code disclosure obligations.
last release 2026-03-27 (140 days) · last repo commit 2026-03-26 · 702 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 120,582 downloads/mo, #12,018 on PyPI
Alternatives
Verify before relying
pip install rpy2-robjects
from rpy2.robjects import r
result = r('sum')- Whether rpy2-robjects works as a standalone package or requires the parent rpy2 package to be installed separately.
- Performance characteristics and overhead when calling R functions from Python in tight loops.
- Compatibility with specific R versions and whether version mismatches cause runtime failures.
What it is and what it does
rpy2-robjects is the object-oriented layer of the rpy2 Python-to-R bridge, built on top of rpy2-rinterface. It allows Python code to call R functions, manipulate R objects, and work with R data structures as if they were native Python objects. The package depends on rpy2-rinterface, jinja2, tzlocal, and packaging.
Typical use involves importing R functions or running R code snippets from within Python scripts, making it useful for data analysis workflows that combine Python and R. The package supports Python 3.9, 3.10, 3.11, 3.12, and 3.13, and is actively maintained. Installation is straightforward via pip, though it requires a working R installation on the system and may need library path configuration if R is not in a standard location.
Use it for
- Call R statistical functions and packages from Python without leaving your Python environment.
- Combine Python data processing with R's statistical modeling and visualization capabilities.
- Prototype or migrate R code to Python incrementally by running R functions directly.
- Access R objects and data structures in Python for further manipulation or integration.
- Build Python applications that leverage specialized R packages not available in Python.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to call R from Python and have R already installed on your system.
The package is actively maintained, has low install friction, and carries no known vulnerabilities. The GPLv2+ copyleft license requires careful consideration if you plan to distribute your code—ensure your project's license is compatible. The main blocker is the external R dependency and potential library path configuration on non-standard R installations.
Install
rpy2-robjects on PyPI
Before you install
Low install friction with a pure-wheel distribution. Actively maintained with recent commits and releases. Requires R to be installed and accessible on the system; if R is not in a standard location, library path configuration may be needed.
R must be installed and accessible on the system; if R is not in a standard location, LD_LIBRARY_PATH may need to be configured before importing.
License in practice
Released under GPLv2+, a copyleft license. Any code that links or distributes this package must comply with GPL terms, including potential source code disclosure obligations.
Quickstart
pip install rpy2-robjects
from rpy2.robjects import r
result = r('sum')Verify before relying
- Whether rpy2-robjects works as a standalone package or requires the parent rpy2 package to be installed separately.
- Performance characteristics and overhead when calling R functions from Python in tight loops.
- Compatibility with specific R versions and whether version mismatches cause runtime failures.
Package facts
| License | GPLv2+ copyleft |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesrpy2-rinterfacejinja2tzlocalpackaging |
| Maintenance | Actively maintained 140 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 120,582 / month, #12,018 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)Programming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: rpy2_robjects-3.6.5-py3-none-any.whl
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