Neuracore Logo

Downloads Python 3.10+ PyPI - Version License: MIT Last Commit

Join our community!

Discord

Getting started

Discord


🤖 What is Neuracore

✨ Neuracore is a powerful robot learning library that enables data collection and visualization, model training, deployment, and real-time inference with support for custom data types. Get started with Neuracore today, sign up for a Neuracore account!

Data Visualization

🌟 Features

  • 🚀 Streaming data logging with custom data types
  • 📊 Dataset visualization and synchronization
  • ☁️ Train robot learning algorithms on cloud
  • 🤖 Policy inference and deployment

🛠️ Installation

Neuracore has been tested on Ubuntu 24.04 and MacOS 26 (Arm64, Apple Silicon, M1 series Chips). If you're on Windows, please use Windows Subsystem for Linux (WSL)

To install the basic package for data logging and visualization:

pip install neuracore

Note: installing the ffmpeg binary is recommended for faster video encoding (during recording) and decoding (during playback/import). If not available, Neuracore falls back to PyAV for encoding.

Linux (Debian/Ubuntu):

sudo apt-get update && sudo apt-get install -y ffmpeg

For training and ML development:

pip install neuracore[ml]

For bulk importing datasets:

pip install neuracore[import]

To run our examples:

pip install neuracore[examples]

For MuJoCo MJCF model support:

pip install neuracore[mjcf]

Note: [examples] and [mjcf] cannot be installed together: the examples pin mujoco==2.3.7, while MJCF support requires mujoco>3. Use separate environments if you need both.

🍰 A Short Taste

Here is a short taste on what neuracore can do.
For a detailed walk-through, please refer to the tutorial and documentation, or try it yourself on Google Colab.

import neuracore as nc # pip install neuracore
import time

# ensure you have an account at neuracore.com
nc.login()

# Connect to a robot with URDF
nc.connect_robot(
    robot_name="MyRobot", 
    urdf_path="/path/to/robot.urdf",
)

# Create a dataset for recording
nc.create_dataset(
    name="My Robot Dataset",
    description="Example dataset with multiple data types"
)

# Recording and streaming data
nc.start_recording()
t = time.time()
nc.log_joint_positions(positions={'joint1': 0.5, 'joint2': -0.3}, timestamp=t)
nc.log_rgb(name="top_camera", rgb=image_array, timestamp=t)
# Stop recording, the dataset is automatically uploaded to the cloud
nc.stop_recording()

# Kick off cloud training
job_data = nc.start_training_run(
    name="MyTrainingJob",
    dataset_name="My Robot Dataset",
    algorithm_name="diffusion_policy",
    num_gpus=5,
    frequency=50,
    ...
)

# Load a trained model locally
policy = nc.policy(
    train_run_name="MyTrainingJob",
    ...
)

# Get model inputs
nc.log_joint_positions(positions={'joint1': 0.5, 'joint2': -0.3})
nc.log_rgb(name="top_camera", rgb=image_array)
# Model Inference
predictions = policy.predict(timeout=5)

📚 Documentation

💬 Community

We are building Neuracore to help everyone accelerate their robot learning workflows, and we'd love to hear from you! Join our community to get help, share ideas, and stay updated:

  • Discord - Chat with the community and get support
  • GitHub Issues - Report bugs and request features

🧾 Citation

If you use Neuracore in your research, please consider citing:

@software{Neuracore,
  author = {Neuracore Team},
  title = {Neuracore},
  month = {January},
  year = {2026},
  url = {https://github.com/NeuracoreAI/neuracore}
}

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (17.0.1)

Owner

PyPI data
Data sourced directly from PyPI's database.

Credits

Author: Stephen James

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

dev examples import mjcf ml

Tags

robotics machine-learning ai client-library

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

neuracore-15.0.0-cp314-cp314-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

neuracore-15.0.0-cp314-cp314-macosx_11_0_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.14macOS 11.0+ x86-64

neuracore-15.0.0-cp314-cp314-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

neuracore-15.0.0-cp313-cp313-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

neuracore-15.0.0-cp313-cp313-macosx_11_0_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.13macOS 11.0+ x86-64

neuracore-15.0.0-cp313-cp313-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

neuracore-15.0.0-cp312-cp312-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

neuracore-15.0.0-cp312-cp312-macosx_11_0_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.12macOS 11.0+ x86-64

neuracore-15.0.0-cp312-cp312-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

neuracore-15.0.0-cp311-cp311-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

neuracore-15.0.0-cp311-cp311-macosx_11_0_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.11macOS 11.0+ x86-64

neuracore-15.0.0-cp311-cp311-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

neuracore-15.0.0-cp310-cp310-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

neuracore-15.0.0-cp310-cp310-macosx_11_0_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.10macOS 11.0+ x86-64

neuracore-15.0.0-cp310-cp310-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

File details

Details for the file neuracore-15.0.0-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e0dfa932a7b2c080592c4b26c82bce520f3326dbc74f2a46a9f7f4abed71a013
MD5 cc9c7548d440cc14a05e4e15d55bc281
BLAKE2b-256 5b22f3b7ab5941eb1b878b13d06f53befbd1984e6cce61bea2fc49599de97f9d

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp314-cp314-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp314-cp314-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 551bfb5ccf02243009f556d10278a3f779c0fb98d282afdc1180e36a781c4e27
MD5 514e9bc8cad599b8cdff93a022e83140
BLAKE2b-256 59e97ade4e20ecf64e0bc3e96d7aef20dc4722aa5205cacc3a899a07f74a0d3c

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 05a78a301cecf5bd85aa0e67875940dc31891456506a9fefa53830ab9e7dd70f
MD5 ef2e3d69872199ffcb9ab8281ec58c54
BLAKE2b-256 8071e39e35d2ec74aa1d09b3c11a7fc7bb4be4493f1c351b5b91ba529c8c5768

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 742eabce9139f6adb610d8fb16205c78deef363d50c13f7649b79b1ef5998c0e
MD5 bc36800c54e87dede2d8875576490533
BLAKE2b-256 e164e776cf1cc7b1603e212b9701e8a7d1805c138679ff2661463fa79ab78138

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp313-cp313-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp313-cp313-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 d8df3d6019c80d7e6f1cbed81a98a12d2f0a77756dfcd26507721c065df2744b
MD5 60643ab249edecc50fa329456cfcdf54
BLAKE2b-256 493e9533125c745415f80731e38779b6b5055811d4e7f41551d4b8b5feec9907

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7481203e7cd7a08399c49152bb45b6efeda82d5ddcc0b29f359912114b9dcfeb
MD5 2482c550dfdd68b215cb667a98a685c8
BLAKE2b-256 768b370cc5cba82f8ed624e1a4d25865f83452316a385db26b1937908bf9ac4d

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 6d63f62b0ee33421a62c7d05dff513d4ec4931832060fc67d939b4edcddf9249
MD5 be0267dc7ab3c4af57dd9c2e8667129b
BLAKE2b-256 01220c9d64387b8440673b310f7ac578430569f3cd8a15f003ef9e02819d5b8e

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp312-cp312-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp312-cp312-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 7ee3b92bbee1d87f84e223a08aca4d52b1da343d6bcdfd09ab8d792b838dba94
MD5 eb8909d5af3f49b1abc66daa9ff1d3f3
BLAKE2b-256 0aa446c0f21ed0e5c9266f5e2b269dff734fcabe6537a5708b2dcad1519ba504

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 794e76930831ed62c770ca7b6a1a470da120c99a1950010bb6838b384895fd65
MD5 001d39c27f6cee3406cdf0e45f652655
BLAKE2b-256 e6886ac4e31853a37510c3460be4b7e4251ffd121f05e35ebbfa6603dac7383f

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 286c86ad92c0e6f5ee9e8a724e69a61f4e95e8d4969e2f1ef8b2b83b02d1cee0
MD5 b2b72c262a9012e2549886ce9f53299a
BLAKE2b-256 6d7442ef221bb571d33082dc88d5b4a1228bf2c0e6b12ccb2c6837ba134353f9

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp311-cp311-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp311-cp311-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 10c6ffa10028677e546154b85b8151e883bbc1803834fd2be7055de83d4e1d56
MD5 7d8e64f1ce63bd8dc7558ac000d7b83b
BLAKE2b-256 5167091df03d8ad1c88db4d38c21d717781e65570ea47be7f459fbc4342fce64

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3a3d1d857b65ee56f8a45da17f7dc21a5b904e59cb84fb0b2e33991975351da0
MD5 b79fd50f64a464565d6b8d6749375623
BLAKE2b-256 7776d03180ce7dab5e0aa1e298ba5aae57f69f6927a1e5becc194890812cd2fc

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 129485d87e5c251e1a74131bff2dc71232361715c7dce35d5f4739f9c1f0023e
MD5 3df79b50c7945281309eaa00f455f515
BLAKE2b-256 97b0366f66fc0a641981a87ffc0006ff26cea6d9cb519a52d7a5e0780a4b3267

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp310-cp310-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp310-cp310-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 201868e26939989284550a9fd8eeb3af646ef7d306ff835ea38c60b881029b8f
MD5 93770455e749c19dfa4a094a49151ac6
BLAKE2b-256 cb4dca574c39b4375eccc4e24126bda82f1d2702f6fb425d31c09f3198dad916

See more details on using hashes here.

File details

Details for the file neuracore-15.0.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for neuracore-15.0.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 11959b5bf1d4f14e4b1ca455c8a856011852769406e867124d7cb3e03df86f6f
MD5 483c1137e3a30ce2a0c3d7ba943a9da6
BLAKE2b-256 bd03e53706ff704fb2136b80c5a17b9440a4dd6a222983b5f63ea336af26570f

See more details on using hashes here.

Release history Release notifications | RSS feed

17.0.1

20 files

Pre-release

17.0.1a85

20 files

17.0.0

20 files

Pre-release

16.1.1a83

20 files

Pre-release

16.1.1a82

20 files

Pre-release

16.1.1a81

20 files

Pre-release

16.1.1a80

20 files

Pre-release

16.1.1a79

20 files

16.1.0

15 files

Pre-release

16.0.1a77

15 files

16.0.0

15 files

This release

15.0.0 This release

15 files

14.0.0

15 files

13.7.2

15 files

13.7.1

10 files

13.7.0

10 files

13.6.0

10 files

13.5.0

10 files

13.4.0

10 files

13.3.0

2 files

13.2.0

2 files

13.1.0

2 files

13.0.0

2 files

12.2.2

2 files

12.2.1

2 files

12.2.0

2 files

12.1.0

2 files

12.0.0

2 files

11.0.0

2 files

10.1.0

2 files

10.0.0

2 files

9.2.0

2 files

9.1.0

2 files

9.0.0

2 files

8.0.3

2 files

8.0.2

2 files

8.0.1

2 files

8.0.0

2 files

7.14.1

2 files

7.13.0

2 files

7.12.0

2 files

7.11.2

2 files

7.11.1

2 files

7.11.0

2 files

7.10.4

2 files

7.10.3

2 files

7.10.2

2 files

7.10.1

2 files

7.10.0

2 files

7.9.1

2 files

7.9.0

2 files

7.8.0

2 files

7.7.1

2 files

7.7.0

2 files

7.6.0

2 files

7.5.3

2 files

7.5.2

2 files

7.5.1

2 files

7.5.0

2 files

7.4.1

2 files

7.4.0

2 files

7.3.4

2 files

7.3.3

2 files

7.3.2

2 files

7.3.1

2 files

7.3.0

2 files

7.2.0

2 files

7.1.3

2 files

7.1.2

2 files

7.1.1

2 files

7.1.0

2 files

7.0.1

2 files

7.0.0

2 files

6.2.0

2 files

6.1.2

2 files

6.1.1

2 files

6.1.0

2 files

6.0.2

2 files

6.0.1

2 files

6.0.0

2 files

5.0.1

2 files

5.0.0

2 files

4.1.4

2 files

4.1.3

2 files

4.1.2

2 files

4.1.1

2 files

4.1.0

2 files

4.0.0

2 files

3.6.1

2 files

3.6.0

2 files

3.5.6

2 files

3.5.5

2 files

3.5.4

2 files

3.5.3

2 files

3.5.2

2 files

3.5.1

2 files

3.5.0

2 files

3.4.0

2 files

3.3.2

2 files

3.3.1

2 files

3.3.0

2 files

3.2.0

2 files

3.1.2

2 files

3.1.1

2 files

3.1.0

2 files

3.0.2

2 files

3.0.1

2 files

3.0.0

2 files

2.0.2

2 files

2.0.1

2 files

2.0.0

2 files

1.6.5

2 files

1.6.4

2 files

1.6.3

2 files

1.6.2

2 files

1.6.1

2 files

1.6.0

2 files

1.5.3

2 files

1.5.2

2 files

1.5.1

2 files

1.5.0

2 files

1.4.3

2 files

1.4.2

2 files

1.4.1

2 files

1.4.0

2 files

1.3.1

2 files

1.3.0

2 files

1.2.2

2 files

1.2.1

2 files

1.2.0

2 files

1.1.1

2 files

1.1.0

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page