semvec/pypi-packages huggingface dataset:
mass-assignment 1.0.3
Single-process mass assignment (NGP/CIC/TSC/PCS) with OpenMP
Requires Python: >=3.9

# mass_assignment

A Python library for 3D mass assignment and velocity moment estimation using C++ and OpenMP.

## Features

- **Multiple Assignment Schemes**: Supports NGP, CIC, TSC, and PCS.
- **High-Order Moments**: Compute Density (0th order), Velocity (1st), Velocity Dispersion (2nd), Skewness (3rd), and Kurtosis (4th).
- **Optimized Performance**: Core routines implemented in C++ with OpenMP for efficient multi-threading.

## Installation

```bash
pip install mass-assignment
```

## Usage

1. Density Field

- Map particle masses to a 128^3 3D mesh.

```python
import numpy as np
import mass_assignment as ma

pos = np.random.uniform(0, 100, (1000000, 3))
mass = np.random.uniform(0.5, 1.5, 1000000)

# Compute density
# lbox: Box size, nmesh: Grid resolution
grid_density = ma.dens(pos, nmesh=128, lbox=100.0, method="TSC", mass=mass)
```

2. Velocity Dispersion Field

- Compute the 2nd-order moment tensor

```python
import numpy as np
import mass_assignment as ma

pos = np.random.uniform(0, 100, (1000000, 3))
vel = np.random.normal(0, 10, (1000000, 3))

# Returns an array of shape (nmesh, nmesh, nmesh, 6)
# Component order: xx, xy, xz, yy, yz, zz
dispersion_tensor = ma.sigma_norm(pos, vel, nmesh=128, lbox=100.0, method="TSC")
```

3. Sample a mesh field at particle positions

- `mesh_to_ptcl` interpolates a scalar field defined on a regular 3D grid to arbitrary particle positions.

```python
import numpy as np
import mass_assignment as ma

nmesh = 128
lbox = 1.0

# Example scalar field on the mesh (nmesh, nmesh, nmesh)
mesh = np.random.randn(nmesh, nmesh, nmesh).astype(np.float32)

# Particle positions (N,3) in [0, lbox)
pos = np.random.rand(200000, 3).astype(np.float32) * lbox
val = ma.mesh_to_ptcl(pos, mesh, lbox=lbox, method="TSC", nthreads=0)
print(val.shape)  # (N,)
```


## API Parameters

- Assignment Schemes (`method`)
  You can pass the scheme as a string or an integer.
  - `NGP` (1): Nearest Grid Point
  - `CIC` (2): Cloud-In-Cell
  - `TSC` (3): Triangular Shaped Cloud
  - `PCS` (4): Piecewise Cubic Spline

- Mass (`mass`)
  - If mass is set to None (default), the library assumes uniform mass (weight = 1.0 for every particle).


- Parallelization (`nthreads`)
  - 0 (Default): Automatically uses all available CPU threads via OpenMP.
  - N: Uses a specific number of threads.

- Normalization Mode (`norm_mode`)
  This parameter defines how high-order moments are normalized in `_norm` functions:
  - `diag_norm` (Default): Normalizes each tensor component by the mass in that cell. This corresponds to the Frobenius norm calculation for each independent component.
  - `tr_norm`: Normalizes the tensor using the trace-based scaling.


*Disclaimer*: The implementations for Skewness (3rd order) and Kurtosis (4th order) are currently untested.
emailagent-sdk 0.1.0
Official Python SDK for EmailAgent
Requires Python: >=3.10

# emailagent-sdk (Python)

Official Python SDK for EmailAgent.

## Install

```bash
pip install emailagent-sdk==0.1.0
```

## Usage

```python
from emailagent_sdk import EmailAgentClient

client = EmailAgentClient(
    api_key="<api_key>",
    base_url="https://api.emailagent.dev",
)

print(client.list_inboxes())

emails = client.list_emails(inbox_id="<inbox_uuid>")
print(emails)

client.update_email_read(
    email_id="<email_uuid>",
    is_read=True,
    idempotency_key="mark-read-001",
)
```

## Idempotency

```python
client.create_inbox(
    local_part="agent-1",
    idempotency_key="create-inbox-agent-1",
)
```
nox 2026.2.9
Flexible test automation.
Requires Python: >=3.8
Keywords: automation, testing, tox

<p align="center">
<img src="https://github.com/wntrblm/nox/raw/main/docs/_static/alice.png" alt="logo" width=50%>
</p>

# Nox

[![Nox](https://img.shields.io/badge/%F0%9F%A6%8A-Nox-D85E00.svg)](https://github.com/wntrblm/nox)
[![License](https://img.shields.io/github/license/wntrblm/nox)](https://github.com/wntrblm/nox)
[![PyPI](https://img.shields.io/pypi/v/nox.svg?logo=python)](https://pypi.python.org/pypi/nox)
[![GitHub](https://img.shields.io/github/v/release/wntrblm/nox?logo=github&sort=semver)](https://github.com/wntrblm/nox)
[![Code Style](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/wntrblm/nox)
[![CI](https://github.com/wntrblm/nox/workflows/CI/badge.svg)](https://github.com/wntrblm/nox/actions?query=workflow%3ACI)
[![Downloads](https://static.pepy.tech/personalized-badge/nox?period=total&units=international_system&left_color=grey&right_color=green&left_text=Downloads)](https://pepy.tech/project/nox)

*Flexible test automation with Python*

* **Documentation:** [https://nox.readthedocs.io](https://nox.readthedocs.io)

* **Source Code:** [https://github.com/wntrblm/nox](https://github.com/wntrblm/nox)

## Overview

`nox` is a command-line tool that automates testing in multiple Python environments, similar to [tox][]. Unlike tox, Nox uses a standard Python file for configuration:

```python
import nox


@nox.session
def tests(session: nox.Session) -> None:
    session.install("pytest")
    session.run("pytest")

@nox.session
def lint(session: nox.Session) -> None:
    session.install("flake8")
    session.run("flake8", "--import-order-style", "google")
```

## Installation

Nox is designed to be installed globally (not in a project virtual environment), the recommended way of doing this is via [pipx], a tool designed to install python CLI programs whilst keeping them separate from your global or system python.

To install Nox with [pipx][]:

```shell
pipx install nox
```

You can also use [pip][] in your global python:

```shell
python3 -m pip install nox
```

You may want to user the [user-site][] to avoid messing with your Global python install:

```shell
python3 -m pip install --user nox
```

## Usage

### List all sessions

```shell
nox -l/--list
```

### Run all sessions

```shell
nox
```

### Run a particular session

```shell
nox -s/--session test
```

Checkout the [docs](https://nox.readthedocs.io) for more! 🎉

## Contributing

Nox is an open source project and welcomes contributions of all kinds, checkout the [contributing guide](CONTRIBUTING.md) for help on how to help us out!

All contributors must follow the [code of conduct](CODE_OF_CONDUCT.md) and be nice to one another! 😃

[tox]: https://tox.readthedocs.io
[pipx]: https://pypa.github.io/pipx/
[pip]: https://pip.pypa.io/en/stable/
[user-site]: https://packaging.python.org/en/latest/tutorials/installing-packages/#installing-to-the-user-site
piper-cli 0.0.5
Piper is a coding agent for data teams.
Requires Python: <3.15,>=3.12
Keywords: data-engineering, ai, cli, sql, pipelines

# Piper CLI

Coding agents for data engineers - write code, manage databases, connect to Airflow and more.

## Install

**Requirements:** macOS or Linux, Python 3.12, [ripgrep](https://github.com/BurntSushi/ripgrep):

```bash
brew install ripgrep          # macOS
sudo apt install ripgrep      # Ubuntu / Debian
```

You need a **Solo plan** subscription at [data-engineer.ai](https://data-engineer.ai).

```bash
pip install piper-cli
```

## Setup

Set at least one LLM API key:

```bash
export ANTHROPIC_API_KEY="sk-ant-..."
export OPENAI_API_KEY="sk-proj-..."
export GEMINI_API_KEY="...
```

Then run:

```bash
piper
```

## Configuration

Piper stores config in `~/.piper/`:

```
~/.piper/
├── charts/               # Generated charts and visualizations
├── mcp/
│   └── servers.json      # MCP server configurations
├── plans/                # Saved execution plans
├── projects/             # Project-specific context
├── skills/               # User-defined reusable skills
├── .env                  # Environment variables (API keys, credentials)
├── chats.db              # Conversation history (SQLite)
├── config.json           # User preferences (model)
├── credentials.json      # Auth credentials (managed by CLI)
└── databases.yaml        # Database connections (Jinja2 templated)
```

## Commands

`/help` `/model` `/database` `/mcp` `/chats` `/subagents` `/tokens` `/upgrade` `/clear` `/logout` `/exit`

## Links

[Docs](https://docs.data-engineer.ai) · [Pricing](https://data-engineer.ai/pricing) · [data-engineer.ai](https://data-engineer.ai)
climate-ref-pmp 0.10.0
PMP diagnostic provider for the Rapid Evaluation Framework
Requires Python: >=3.11

# climate-ref-pmp

[![PyPI version](https://badge.fury.io/py/climate-ref-pmp.svg)](https://badge.fury.io/py/climate-ref-pmp)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

This package integrates the [PCMDI Metrics Package (PMP)](https://github.com/PCMDI/pcmdi_metrics) as a metrics provider for the Climate REF (Rapid Evaluation Framework).

## Installation

```bash
pip install climate-ref-pmp
```

## Prerequisites

- PMP must be installed in your environment
- Required climate data files must be available in the specified input directory

## Usage

PMP has some additional preprocessed climatology datasets that should be ingested so the REF compute engine
can find them.

```
ref datasets fetch-data --registry pmp-climatology --output directory data/pmp-climatology
ref datasets ingest --source-type pmp-climatology data/pmp-climatology
```

For detailed usage instructions, see [Running Metrics Locally](https://climate-ref.readthedocs.io/en/latest/how-to-guides/running-metrics-locally/).

## Documentation

For detailed documentation, please visit:
- [Climate REF Documentation](https://climate-ref.readthedocs.io/)
- [PMP Documentation](http://pcmdi.github.io/pcmdi_metrics/)

## Contributing

Contributions are welcome! Please see the main project's [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
climate-ref-ilamb 0.10.0
ILAMB diagnostic provider for the Rapid Evaluation Framework
Requires Python: >=3.11

# climate-ref-ilamb

[![PyPI version](https://badge.fury.io/py/climate-ref-ilamb.svg)](https://badge.fury.io/py/climate-ref-ilamb)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

This package integrates [ILAMB](https://github.com/rubisco-sfa/ilamb3) as a metrics provider for the Climate REF (Rapid Evaluation Framework).

## Installation

```bash
pip install climate-ref-ilamb
```

## Usage

For detailed usage instructions, see [Running Metrics Locally](https://climate-ref.readthedocs.io/en/latest/how-to-guides/running-metrics-locally/).

## Documentation

For detailed documentation, please visit:
- [Climate REF Documentation](https://climate-ref.readthedocs.io/)
- [ILAMB Documentation](https://www.ilamb.org/)

## Contributing

Contributions are welcome! Please see the main project's [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
climate-ref-esmvaltool 0.10.0
ESMValTool diagnostic provider for the Rapid Evaluation Framework
Requires Python: >=3.11

# climate-ref-esmvaltool

[![PyPI version](https://badge.fury.io/py/climate-ref-esmvaltool.svg)](https://badge.fury.io/py/climate-ref-esmvaltool)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

This package integrates [ESMValTool](https://esmvaltool.org/) as a metrics provider for the Climate REF (Rapid Evaluation Framework).

## Installation

```bash
pip install climate-ref-esmvaltool
```


## Usage


For detailed usage instructions, see [Running Metrics Locally](https://climate-ref.readthedocs.io/en/latest/how-to-guides/running-metrics-locally/).

## Documentation

For detailed documentation, please visit:
- [Climate REF Documentation](https://climate-ref.readthedocs.io/)
- [ESMValTool Documentation](https://docs.esmvaltool.org/)

## Contributing

Contributions are welcome! Please see the main project's [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
climate-ref-core 0.10.0
Core library for the CMIP Rapid Evaluation Framework
Requires Python: >=3.11

# climate-ref-core

[![PyPI version](https://badge.fury.io/py/climate-ref-core.svg)](https://badge.fury.io/py/climate-ref-core)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

This package provides the core functionality for the Climate REF (Rapid Evaluation Framework).
It is designed as a library that can be used by other packages to implement metrics providers and extend the framework's capabilities.

## Installation


```bash
pip install climate-ref-core
```


## Usage

This package is primarily intended to be used as a dependency by other packages implementing diagnostic providers.
See the [example diganotic provider](https://github.com/Climate-REF/climate-ref/tree/main/packages/ref-metrics-example).


## Documentation

For detailed documentation, please visit [https://climate-ref.readthedocs.io/](https://climate-ref.readthedocs.io/)

## Contributing

Contributions are welcome! Please see the main project's [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
climate-ref-celery 0.10.0
Celery app for mananging tasks and workers
Requires Python: >=3.11

# climate-ref-celery

[![PyPI version](https://badge.fury.io/py/climate-ref-celery.svg)](https://badge.fury.io/py/climate-ref-celery)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

This package provides Celery task generation and worker management for the Climate REF (Rapid Evaluation Framework).

The `climate_ref_celery` package provides a CLI tool(`ref-celery`) to start a worker instance for a diagnostics provider.
This worker instance will listen for tasks related to a provider and execute them.
The compute engine worker will then collect the results of these tasks and store them in the database.
This allows for the REF to be run in a distributed manner,
with multiple workers running on different machines with a centrally managed database.

## Installation

```bash
pip install climate-ref-celery
```

## Features

- Distributed task execution for metrics providers
- Worker management and monitoring
- Automatic task routing and scheduling
- Results collection and storage
- Support for multiple worker instances

## Usage

### Starting a Worker

To start a worker instance for a specific metrics provider:

```bash
# Using the standalone CLI
ref-celery start-worker --package climate_ref_pmp

# Or using the main REF CLI
ref celery start-worker --package climate_ref_pmp
```

### Configuration

Each worker instance may not share the same configuration as the orchestrator.
This is because the worker may be running on a different machine with different resources available or
directories.

Each worker instance requires access to a shared input data directory and the output directory.
If the worker is deployed as a docker container these directories can be mounted as volumes.

Each worker instance can be configured independently. Required configurations include:

- Shared input data directory
- Output directory for results
- Database connection settings


## Documentation

For detailed documentation, please visit [https://climate-ref.readthedocs.io/](https://climate-ref.readthedocs.io/)

## Contributing

Contributions are welcome! Please see the main project's [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
climate-ref 0.10.0
Application which runs the CMIP Rapid Evaluation Framework
Requires Python: >=3.11

# Climate REF (Rapid Evaluation Framework)

[![PyPI version](https://badge.fury.io/py/climate-ref.svg)](https://badge.fury.io/py/climate-ref)
[![Documentation Status](https://readthedocs.org/projects/climate-ref/badge/?version=latest)](https://climate-ref.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://www.python.org/downloads/)

**Status**: This project is in active development. We expect to be ready for beta releases in Q2 2025.

The Rapid Evaluation Framework (REF) is a set of Python packages that provide the ability to manage the execution of calculations against climate datasets.
The aim is to be able to evaluate climate data against a set of reference data in near-real time as datasets are published,
and to update any produced data and figures as new datasets become available.
This is somewhat analogous to a CI/CD pipeline for climate data.

## Installation

```bash
pip install climate-ref
```

If you want to use the diagnostic providers for the Assessment Fast Track, you can install them with:

```bash
pip install "climate-ref[aft-providers]"
```

## Quick Start

```bash
# Ingest some observation datasets
ref datasets fetch-data --registry obs4ref ---output-directory datasets/obs4ref
ref datasets fetch-data --registry sample-data ---output-directory datasets/sample-data

# Run metrics against your climate data
ref solve
```

## Features

- Real-time evaluation of climate datasets
- Support for multiple metrics providers (PMP, ILAMB, ESMValTool)
- Distributed processing capabilities
- Extensible architecture for adding new metrics providers
- Command-line interface for easy interaction

## Documentation

For detailed documentation, please visit [https://climate-ref.readthedocs.io/](https://climate-ref.readthedocs.io/)

## Contributing

REF is a community project, and we welcome contributions from anyone. Please see our [Contributing Guide](https://climate-ref.readthedocs.io/en/latest/contributing/) for more information.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
gpubackendtools 0.1.1
GPU Backend Tools
Requires Python: >=3.10

# GPUBackendTools: Backend tools for GPU/CPU agnostic codes.


## Getting Started


### Prerequisites


### Installing


## Running the Tests


## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/mikekatz04/GPUBackendTools/tags).

Current Version: 0.0.1

## Authors

* Michael Katz
* Maxime Pigou
* Mathieu Dubois

## Contributors


## License

This project is licensed under the Apache License - see the [LICENSE](https://github.com/mikekatz04/GPUBackendTools/blob/master/LICENSE) file for details.
types-networkx 3.6.1.20260210
Typing stubs for networkx
Requires Python: >=3.10

## Typing stubs for networkx

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`networkx`](https://github.com/networkx/networkx) package. It can be used by type checkers
to check code that uses `networkx`. This version of
`types-networkx` aims to provide accurate annotations for
`networkx==3.6.1`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/networkx`](https://github.com/python/typeshed/tree/main/stubs/networkx)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`665cb9b0110b3311b09df9fd774da1cd3768364a`](https://github.com/python/typeshed/commit/665cb9b0110b3311b09df9fd774da1cd3768364a).
types-convertdate 2.4.1.20260210
Typing stubs for convertdate
Requires Python: >=3.10

## Typing stubs for convertdate

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`convertdate`](https://github.com/fitnr/convertdate) package. It can be used by type checkers
to check code that uses `convertdate`. This version of
`types-convertdate` aims to provide accurate annotations for
`convertdate==2.4.1`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/convertdate`](https://github.com/python/typeshed/tree/main/stubs/convertdate)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`665cb9b0110b3311b09df9fd774da1cd3768364a`](https://github.com/python/typeshed/commit/665cb9b0110b3311b09df9fd774da1cd3768364a).
types-setuptools 82.0.0.20260210
Typing stubs for setuptools
Requires Python: >=3.10

## Typing stubs for setuptools

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`setuptools`](https://github.com/pypa/setuptools) package. It can be used by type checkers
to check code that uses `setuptools`. This version of
`types-setuptools` aims to provide accurate annotations for
`setuptools==82.0.*`.

Given that `pkg_resources` is typed since `setuptools >= 71.1`, it is no longer included with `types-setuptools`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/setuptools`](https://github.com/python/typeshed/tree/main/stubs/setuptools)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`665cb9b0110b3311b09df9fd774da1cd3768364a`](https://github.com/python/typeshed/commit/665cb9b0110b3311b09df9fd774da1cd3768364a).