| Name | ssm-simulators JSON |
| Version |
0.10.2
JSON |
| download |
| home_page | None |
| Summary | SSMS is a package collecting simulators and training data generators for cognitive science, neuroscience, and approximate bayesian computation |
| upload_time | 2025-07-11 15:29:45 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.10 |
| license | MIT License
Copyright (c) 2021 Alexander Fengler
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
|
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# SSMS (Sequential Sampling Model Simulators)
Python Package which collects simulators for Sequential Sampling Models.
Find the package documentation [here](https://lnccbrown.github.io/ssm-simulators/).
[](https://github.com/astral-sh/ruff)
[](https://opensource.org/licenses/MIT)
[](https://codecov.io/gh/lnccbrown/ssm-simulators)
### Quick Start
The `ssms` package serves two purposes.
1. Easy access to *fast simulators of sequential sampling models*
2. Support infrastructure to construct training data for various approaches to likelihood / posterior amortization
A number of tutorial notebooks are available under the `/notebooks` directory.
#### Installation
```sh
pip install ssm-simulators
```
> [!NOTE]
> Building from source or developing this package requires a C compiler (such as GCC).
> On Linux, you can install GCC with:
> ```bash
> sudo apt-get install build-essential
> ```
> Most users installing from PyPI wheels do **not** need to install GCC.
#### Command Line Interface
The package exposes a command-line tool, `generate`, for creating training data from a YAML configuration file.
```bash
generate --config-path <path/to/config.yaml> --output <output/directory> [--log-level INFO]
```
- `--config-path`: Path to your YAML configuration file (required).
- `--output`: Directory where generated data will be saved (required).
- `--n-files`: (Optional) Number of data files to generate. Default is `1` file.
- `--log-level`: (Optional) Set the logging level (`DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`). Default is `WARNING`.
Below is a sample YAML configuration you can use with the `generate` command:
```yaml
MODEL: 'ddm'
N_SAMPLES: 2000
N_PARAMETER_SETS: 100
DELTA_T: 0.001
N_TRAINING_SAMPLES_BY_PARAMETER_SET: 200
N_SUBRUNS: 20
GENERATOR_APPROACH: 'lan'
```
**Example:**
```bash
generate --config-path myconfig.yaml --output ./output --n-files 10 --log-level INFO
```
This will generate training data according to your configuration and save it in the specified output directory.
### Tutorial
Check the basic tutorial [here](docs/basic_tutorial/basic_tutorial.ipynb).
### Advanced: Dependency Management with uv
We use `uv` for fast and efficient dependency management. To get started:
1. Install `uv`:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. Install dependencies (including development):
```bash
uv sync --all-groups # Installs all dependency groups
```
Raw data
{
"_id": null,
"home_page": null,
"name": "ssm-simulators",
"maintainer": null,
"docs_url": null,
"requires_python": "<3.14,>=3.10",
"maintainer_email": null,
"keywords": null,
"author": null,
"author_email": "Alexander Fengler <alexander_fengler@brown.edu>",
"download_url": "https://files.pythonhosted.org/packages/b9/ce/1a43c400d421d32e008fec31d354a0a421d5a4344bf71672f0ec734bb218/ssm_simulators-0.10.2.tar.gz",
"platform": null,
"description": "# SSMS (Sequential Sampling Model Simulators)\nPython Package which collects simulators for Sequential Sampling Models.\n\nFind the package documentation [here](https://lnccbrown.github.io/ssm-simulators/).\n\n\n\n[](https://github.com/astral-sh/ruff)\n[](https://opensource.org/licenses/MIT)\n[](https://codecov.io/gh/lnccbrown/ssm-simulators)\n\n### Quick Start\n\nThe `ssms` package serves two purposes.\n\n1. Easy access to *fast simulators of sequential sampling models*\n2. Support infrastructure to construct training data for various approaches to likelihood / posterior amortization\n\nA number of tutorial notebooks are available under the `/notebooks` directory.\n\n#### Installation\n\n```sh\npip install ssm-simulators\n```\n\n> [!NOTE]\n> Building from source or developing this package requires a C compiler (such as GCC).\n> On Linux, you can install GCC with:\n> ```bash\n> sudo apt-get install build-essential\n> ```\n> Most users installing from PyPI wheels do **not** need to install GCC.\n\n#### Command Line Interface\nThe package exposes a command-line tool, `generate`, for creating training data from a YAML configuration file.\n\n```bash\ngenerate --config-path <path/to/config.yaml> --output <output/directory> [--log-level INFO]\n```\n\n- `--config-path`: Path to your YAML configuration file (required).\n- `--output`: Directory where generated data will be saved (required).\n- `--n-files`: (Optional) Number of data files to generate. Default is `1` file.\n- `--log-level`: (Optional) Set the logging level (`DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`). Default is `WARNING`.\n\nBelow is a sample YAML configuration you can use with the `generate` command:\n\n```yaml\nMODEL: 'ddm'\nN_SAMPLES: 2000\nN_PARAMETER_SETS: 100\nDELTA_T: 0.001\nN_TRAINING_SAMPLES_BY_PARAMETER_SET: 200\nN_SUBRUNS: 20\nGENERATOR_APPROACH: 'lan'\n```\n\n**Example:**\n\n```bash\ngenerate --config-path myconfig.yaml --output ./output --n-files 10 --log-level INFO\n```\n\nThis will generate training data according to your configuration and save it in the specified output directory.\n\n### Tutorial\n\nCheck the basic tutorial [here](docs/basic_tutorial/basic_tutorial.ipynb).\n\n### Advanced: Dependency Management with uv\n\nWe use `uv` for fast and efficient dependency management. To get started:\n\n1. Install `uv`:\n```bash\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n```\n\n2. Install dependencies (including development):\n```bash\nuv sync --all-groups # Installs all dependency groups\n```\n",
"bugtrack_url": null,
"license": "MIT License\n \n Copyright (c) 2021 Alexander Fengler\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n ",
"summary": "SSMS is a package collecting simulators and training data generators for cognitive science, neuroscience, and approximate bayesian computation",
"version": "0.10.2",
"project_urls": {
"Bug Tracker": "https://github.com/lnccbrown/ssm-simulators/issues",
"Homepage": "https://github.com/lnccbrown/ssm-simulators"
},
"split_keywords": [],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "61b684a90cadc5088f1b4cf5cd0f9b22209af18c6ad0eebc26d1bbf52b5f64b4",
"md5": "febd67505c58ac1b88fca6274ee13578",
"sha256": "edbf20a2febe7e98f9e19e19eab5156c4063e0080df3812e9cb5ab308cc53dd8"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp310-cp310-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "febd67505c58ac1b88fca6274ee13578",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": "<3.14,>=3.10",
"size": 405195,
"upload_time": "2025-07-11T15:29:27",
"upload_time_iso_8601": "2025-07-11T15:29:27.982696Z",
"url": "https://files.pythonhosted.org/packages/61/b6/84a90cadc5088f1b4cf5cd0f9b22209af18c6ad0eebc26d1bbf52b5f64b4/ssm_simulators-0.10.2-cp310-cp310-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "4998c18fc27047d34fdd2bb70c38692f6093917a2d8c6ebe0744b34571982134",
"md5": "c1dd95ed91296adf27891c1c4d053760",
"sha256": "4b1c4bb23d2eeed4ee89c02d5bd965cc09d962bedff01e75f0cf1c5b7951463a"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp310-cp310-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "c1dd95ed91296adf27891c1c4d053760",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": "<3.14,>=3.10",
"size": 350813,
"upload_time": "2025-07-11T15:29:29",
"upload_time_iso_8601": "2025-07-11T15:29:29.533936Z",
"url": "https://files.pythonhosted.org/packages/49/98/c18fc27047d34fdd2bb70c38692f6093917a2d8c6ebe0744b34571982134/ssm_simulators-0.10.2-cp310-cp310-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "2cd45303ffcc7de5a258dd92532cdb0ee8a75c158b4ba43bcb1d468222cf86be",
"md5": "bd4a6b88ad42a85bb57cd8e9be5cd271",
"sha256": "5c3a6ce063a6cad37a7c629c6f1a0e8e274605ac26e98f00ff6083387e60f0ca"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "bd4a6b88ad42a85bb57cd8e9be5cd271",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": "<3.14,>=3.10",
"size": 2284129,
"upload_time": "2025-07-11T15:29:30",
"upload_time_iso_8601": "2025-07-11T15:29:30.845368Z",
"url": "https://files.pythonhosted.org/packages/2c/d4/5303ffcc7de5a258dd92532cdb0ee8a75c158b4ba43bcb1d468222cf86be/ssm_simulators-0.10.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "f2c7ca7055ae14c1c07d0b921bf0a9eddac1118a19dd13d6b1cf1a65e1116943",
"md5": "3a42f5b477f0b6f3e566d94774eea003",
"sha256": "b87466e8da24d3184098da1cd22ebb56a022db036f47dcba1f91ae0b9e9eb3df"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp310-cp310-musllinux_1_2_x86_64.whl",
"has_sig": false,
"md5_digest": "3a42f5b477f0b6f3e566d94774eea003",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": "<3.14,>=3.10",
"size": 2405958,
"upload_time": "2025-07-11T15:29:31",
"upload_time_iso_8601": "2025-07-11T15:29:31.873973Z",
"url": "https://files.pythonhosted.org/packages/f2/c7/ca7055ae14c1c07d0b921bf0a9eddac1118a19dd13d6b1cf1a65e1116943/ssm_simulators-0.10.2-cp310-cp310-musllinux_1_2_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "67468220647e5b7cbfd4ce8e9d1e8900473e978f93aa047407c691ec191aea7b",
"md5": "d0bceef2a20058e1ae9b1f2eb8510401",
"sha256": "389e54faa31da2d5e051f2f98ac6d4d1c0cecc21b5a866fd84848c0f6c99f0a7"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp310-cp310-win_amd64.whl",
"has_sig": false,
"md5_digest": "d0bceef2a20058e1ae9b1f2eb8510401",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": "<3.14,>=3.10",
"size": 329611,
"upload_time": "2025-07-11T15:29:32",
"upload_time_iso_8601": "2025-07-11T15:29:32.964921Z",
"url": "https://files.pythonhosted.org/packages/67/46/8220647e5b7cbfd4ce8e9d1e8900473e978f93aa047407c691ec191aea7b/ssm_simulators-0.10.2-cp310-cp310-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "c1a4397857b078670d420b6e9f46d08cf7c0f76063e297ddf2b339e1b9ddd8a2",
"md5": "87255c37f3982b9c52e826286a6566e3",
"sha256": "dc202c15fa4bcc09bee0ed1d3ac2cc51a639d67a5b47857767927baf9e32d4d8"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp311-cp311-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "87255c37f3982b9c52e826286a6566e3",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": "<3.14,>=3.10",
"size": 408995,
"upload_time": "2025-07-11T15:29:34",
"upload_time_iso_8601": "2025-07-11T15:29:34.476284Z",
"url": "https://files.pythonhosted.org/packages/c1/a4/397857b078670d420b6e9f46d08cf7c0f76063e297ddf2b339e1b9ddd8a2/ssm_simulators-0.10.2-cp311-cp311-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "d8121c33025a7a5ac0383c956897b880a78cf92a0752f549d2799fcca948368e",
"md5": "ba1d7e27f3d73c7c82cf63ba9c0c5ba1",
"sha256": "3fe7ec9800a9c58f6f499bd2df5d8d810af66117fd2974216f401677cb97e52f"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp311-cp311-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "ba1d7e27f3d73c7c82cf63ba9c0c5ba1",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": "<3.14,>=3.10",
"size": 354763,
"upload_time": "2025-07-11T15:29:35",
"upload_time_iso_8601": "2025-07-11T15:29:35.862503Z",
"url": "https://files.pythonhosted.org/packages/d8/12/1c33025a7a5ac0383c956897b880a78cf92a0752f549d2799fcca948368e/ssm_simulators-0.10.2-cp311-cp311-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "7bfd450881353af7380a942e3685df045075f5d4a5f9408d9dc1e64cd784b58f",
"md5": "156a93dde9e503c4d60ce2374a702de8",
"sha256": "b30b917ac884792b9242038fd12886cfd68c88a16dd89acc64c3280889b8e78e"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "156a93dde9e503c4d60ce2374a702de8",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": "<3.14,>=3.10",
"size": 2391489,
"upload_time": "2025-07-11T15:29:36",
"upload_time_iso_8601": "2025-07-11T15:29:36.846096Z",
"url": "https://files.pythonhosted.org/packages/7b/fd/450881353af7380a942e3685df045075f5d4a5f9408d9dc1e64cd784b58f/ssm_simulators-0.10.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "27897b7fb1ea13d06ecf8886c51262a1ee153de34112a59bbfc9e78ccec610b4",
"md5": "09808f748774ec4311b11cff1dad8cb2",
"sha256": "83444ced3cbdb9f0472fdf2c35a80e5652958a01a8e2ccde6a11ed230932f174"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp311-cp311-musllinux_1_2_x86_64.whl",
"has_sig": false,
"md5_digest": "09808f748774ec4311b11cff1dad8cb2",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": "<3.14,>=3.10",
"size": 2548391,
"upload_time": "2025-07-11T15:29:38",
"upload_time_iso_8601": "2025-07-11T15:29:38.381740Z",
"url": "https://files.pythonhosted.org/packages/27/89/7b7fb1ea13d06ecf8886c51262a1ee153de34112a59bbfc9e78ccec610b4/ssm_simulators-0.10.2-cp311-cp311-musllinux_1_2_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "886a3ae51dff7d6fd3780d3af36b0b556b4c24b15c8c2e47740e8e253c9bd235",
"md5": "07bb5cd0e0a1ee87c1e977c00da92157",
"sha256": "d5393baf8fa421f7f33d5f1bef61a2b4ccad654e09cc8c2e6852fe6c7db352d8"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp311-cp311-win_amd64.whl",
"has_sig": false,
"md5_digest": "07bb5cd0e0a1ee87c1e977c00da92157",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": "<3.14,>=3.10",
"size": 330754,
"upload_time": "2025-07-11T15:29:39",
"upload_time_iso_8601": "2025-07-11T15:29:39.347780Z",
"url": "https://files.pythonhosted.org/packages/88/6a/3ae51dff7d6fd3780d3af36b0b556b4c24b15c8c2e47740e8e253c9bd235/ssm_simulators-0.10.2-cp311-cp311-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "a7b78b02069777a5debe4cf99c9f941c84e07097094043f7af7378f140b7a272",
"md5": "cbf7b062a35e3e2410515d83ed8adb87",
"sha256": "9bb14d3c0ab862879aec5cca80b6852adeb9c674803a9f5f2df9a4519fadb29f"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp312-cp312-macosx_10_13_x86_64.whl",
"has_sig": false,
"md5_digest": "cbf7b062a35e3e2410515d83ed8adb87",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": "<3.14,>=3.10",
"size": 378248,
"upload_time": "2025-07-11T15:29:40",
"upload_time_iso_8601": "2025-07-11T15:29:40.363790Z",
"url": "https://files.pythonhosted.org/packages/a7/b7/8b02069777a5debe4cf99c9f941c84e07097094043f7af7378f140b7a272/ssm_simulators-0.10.2-cp312-cp312-macosx_10_13_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "458ed5e824edd8e2beb02b68d26770ab6a59cbfa5d26f44ce25b050e9d628cf3",
"md5": "5c23cd1f1431229a838813c5bd7ab9db",
"sha256": "debfcb16aedce383dc3be1f38496c5ff8676f574ae98354d8dc406b3bc433bf9"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp312-cp312-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "5c23cd1f1431229a838813c5bd7ab9db",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": "<3.14,>=3.10",
"size": 332576,
"upload_time": "2025-07-11T15:29:41",
"upload_time_iso_8601": "2025-07-11T15:29:41.279675Z",
"url": "https://files.pythonhosted.org/packages/45/8e/d5e824edd8e2beb02b68d26770ab6a59cbfa5d26f44ce25b050e9d628cf3/ssm_simulators-0.10.2-cp312-cp312-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "2b28fe3d279c8978baa556ad40ae9299f46923de8bbb01a1b70f094dca0b741f",
"md5": "46baf99aa25a9e78ab4aed302e803ad2",
"sha256": "c85c98a0edc78750a6e28eb3edf4bc1346b9a8238a3107ee1c5ec3fda6da9707"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "46baf99aa25a9e78ab4aed302e803ad2",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": "<3.14,>=3.10",
"size": 2350802,
"upload_time": "2025-07-11T15:29:42",
"upload_time_iso_8601": "2025-07-11T15:29:42.275404Z",
"url": "https://files.pythonhosted.org/packages/2b/28/fe3d279c8978baa556ad40ae9299f46923de8bbb01a1b70f094dca0b741f/ssm_simulators-0.10.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "69c3521d126d87878a1986f305f9922e8f14155110baafc44b0735d55d326749",
"md5": "87c878fee76e1fd3ba0ba0b437160d85",
"sha256": "b47778c862ceeff5e7760afb80179e8901229ebe03bb61791712799e1734f21f"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp312-cp312-musllinux_1_2_x86_64.whl",
"has_sig": false,
"md5_digest": "87c878fee76e1fd3ba0ba0b437160d85",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": "<3.14,>=3.10",
"size": 2404314,
"upload_time": "2025-07-11T15:29:43",
"upload_time_iso_8601": "2025-07-11T15:29:43.287417Z",
"url": "https://files.pythonhosted.org/packages/69/c3/521d126d87878a1986f305f9922e8f14155110baafc44b0735d55d326749/ssm_simulators-0.10.2-cp312-cp312-musllinux_1_2_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "18c06440659a29679a479855b68fb3b810707a899f79d0a0c4d0d905d8781e8f",
"md5": "5ee07324920ca06c70686d8123facf1a",
"sha256": "126354830f2e00635a128315f76680fbea7dd38c6bd611d33eb4c3f9d6fb114e"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2-cp312-cp312-win_amd64.whl",
"has_sig": false,
"md5_digest": "5ee07324920ca06c70686d8123facf1a",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": "<3.14,>=3.10",
"size": 311467,
"upload_time": "2025-07-11T15:29:44",
"upload_time_iso_8601": "2025-07-11T15:29:44.627406Z",
"url": "https://files.pythonhosted.org/packages/18/c0/6440659a29679a479855b68fb3b810707a899f79d0a0c4d0d905d8781e8f/ssm_simulators-0.10.2-cp312-cp312-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "b9ce1a43c400d421d32e008fec31d354a0a421d5a4344bf71672f0ec734bb218",
"md5": "8ca60ba2f6798782a9cddf9f83c0b943",
"sha256": "aad68e5e8b3759d8f9063836192fce9fcbf873a005e28b0d8d19e6730863d065"
},
"downloads": -1,
"filename": "ssm_simulators-0.10.2.tar.gz",
"has_sig": false,
"md5_digest": "8ca60ba2f6798782a9cddf9f83c0b943",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<3.14,>=3.10",
"size": 1228633,
"upload_time": "2025-07-11T15:29:45",
"upload_time_iso_8601": "2025-07-11T15:29:45.716717Z",
"url": "https://files.pythonhosted.org/packages/b9/ce/1a43c400d421d32e008fec31d354a0a421d5a4344bf71672f0ec734bb218/ssm_simulators-0.10.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-07-11 15:29:45",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "lnccbrown",
"github_project": "ssm-simulators",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "ssm-simulators"
}
