Install & Compatibility
Where this runs
tested against v2025.1.1 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.920 runs
build_error
glibcpy 3.10–3.920 runs
installs and imports cleanly · install 3.7s · import 0.286s · 86MB
87MB installed
● package 87MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
transformations
✓ import transformations as tf
Common practice to alias for brevity and to distinguish from other transformation libraries.
This quickstart demonstrates how to create rotation and translation matrices and apply them to a 3D point using homogeneous coordinates. It also shows how to concatenate transformations.
import numpy as np
import transformations as tf
# Create a rotation matrix around the Z-axis by 90 degrees (pi/2 radians)
angle = np.pi / 2
rotation_matrix = tf.rotation_matrix(angle, [0, 0, 1])
# Define a point in homogeneous coordinates (x, y, z, w=1)
point = np.array([1.0, 0.0, 0.0, 1.0])
# Apply the transformation
transformed_point = np.dot(rotation_matrix, point)
print(f"Original point: {point[:3]}")
print(f"Rotation matrix:\n{rotation_matrix}")
print(f"Transformed point: {transformed_point[:3]}")
# Create a translation matrix
translation_matrix = tf.translation_matrix([5.0, 2.0, 0.0])
# Concatenate transformations (apply rotation then translation)
combined_matrix = np.dot(translation_matrix, rotation_matrix)
combined_transformed_point = np.dot(combined_matrix, point)
print(f"\nCombined transformation matrix:\n{combined_matrix}")
print(f"Combined transformed point: {combined_transformed_point[:3]}")
Debug
Known issues
deprecatedThe 'transformations' library is no longer actively developed and is largely superseded by other, more actively maintained modules like Pytransform3d, Scipy.spatial.transform, Transforms3d, or Numpy-quaternion. Consider using these alternatives for new projects.fixMigrate to a more actively maintained library such as `scipy.spatial.transform` or `transforms3d` for new development. For existing code, be aware that support may be limited.
affects: 2024.1.6 and later
breakingThe API is explicitly stated as 'not stable yet and is expected to change between revisions.' This means minor version updates might introduce breaking changes.fixPin the library version in your `requirements.txt` (e.g., `transformations==2026.1.18`) and thoroughly test after any upgrade. Review the `CHANGES` file on GitHub before updating.
affects: All versions
gotchaQuaternions in this library are represented as `[w, x, y, z]`. This differs from some other common libraries (e.g., older ROS `tf.transformations` used `[x, y, z, w]`), which can lead to incorrect calculations if not handled carefully.fixAlways verify the quaternion convention when integrating with other libraries or systems. Convert components if necessary to match the expected order.
affects: All versions
gotchaThe Python implementation of transformations is not optimized for speed. For performance-critical applications, consider using the `transformations.c` module (if available in your distribution) or alternative libraries that offer optimized (e.g., C/Cython backed) implementations.fixFor speed-critical paths, profile your code and consider rewriting parts using a faster library or the `transformations.c` module. The core `numpy` operations are generally fast, but some high-level functions might have overhead.
affects: All versions
gotchaTransformation matrices generated by this library might require transposing when interfacing with some other graphics systems, such as OpenGL's `glMultMatrixd()`, due to differing column-major/row-major conventions.fixWhen passing matrices to external graphics APIs, test and, if necessary, transpose the matrix (e.g., `M.T`) to ensure correct orientation and position.
affects: All versions
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Version history
2026.1.18latest on PyPI · released Jan 17, 2026
Audit
Dependencies
numpyrequiredRequired for array manipulations and mathematical operations.