semvec/pypi-packages huggingface dataset:
promethiite 0.2.0
Promethiite Ingests Prometheus metrics, converts them to Graphite metrics, and sends them to a configured Graphite server over TCP
Requires Python: >=3.6

promethiite
===========

Promethiite ingests [Prometheus] metrics, converts them to [Graphite] metrics, and sends them to a configured Graphite server over TCP

Requires Python 3.6+

# Installation

You can install with [pip]:

```sh
python3 -m pip install promethiite
```

Or install from source:

```sh
git clone <url>
pip install promethiite
```

# Usage

Promethiite is intended to be run at an interval, via e.g. cron or Systemd timers. There is no daemon mode.

```
usage: promethiite [-h] [--file FILE_PATH] --prefix PREFIX --server SERVER [--port PORT] [--proto {tcp,udp}] [--verbose]

        Ingests Prometheus metrics, converts them to Graphite metrics, and
        sends them to a configured Graphite server over TCP


options:
  -h, --help            show this help message and exit
  --file FILE_PATH, -f FILE_PATH
                        A file path from which to get the stats. By defaults expects STDIN
  --prefix PREFIX, -p PREFIX
                        Value to prepend to the value name on send to Graphite
  --server SERVER, -s SERVER
                        Graphite server
  --port PORT, -o PORT  Graphite server port
  --proto {tcp,udp}, -r {tcp,udp}
                        Protocol to use to reach the Graphite server
  --verbose, -v         Set output verbosity (-v=warning, -vv=debug)

examples:

        promethiite <args>
```

# Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

To run the test suite:

```bash
# Dependent targets create venv and install dependencies
make
```

Please make sure to update tests along with any changes.

# License

License :: OSI Approved :: MIT License


[Graphite]: https://graphite.readthedocs.io/en/latest/overview.html
[Prometheus]: https://prometheus.io/docs/introduction/overview/
[pip]: https://pip.pypa.io/en/stable/
tinyjsondb 0.1.3
A lightweight, JSON-based Python ORM library
Requires Python: >=3.10
Keywords: json, database, orm, tinydb

# tinyjsondb

tinyjsondb is a minimal Python ORM for working with JSON files as a simple database.
It allows defining models with typed fields, creating, reading, updating, and deleting records, all stored in JSON.

## Installation

```bash
pip install tinyjsondb
```

or from source:

```bash
git clone https://github.com/Waland2/tinyjsondb.git
cd tinyjsondb
pip install .
```

## Quick Start

```python
from tinyjsondb import Model, IntegerField, StringField, ListField

class User(Model):
    name = StringField(default="Anonymous")
    hobbies = ListField(default=[])

# Initialize the storage file and sync schema
User.sync()

# Create a record
User.objects.create(name="Alice", hobbies=["reading"])

# Get a record
user = User.objects.get(id=1)
print(user.name)  # Alice

# Update a record
user.update(name="Alice Wonderland")

# Delete a record
user.delete()
user = User.objects.get(id=1)
print(user is None)  # True

# Get all records
users = User.objects.all()
```

## Overview

**Model methods:**

* `sync()` - create or update the JSON file with data.
* `save()` - insert or update the record.
* `update(**kwargs)` - update fields and save.
* `delete()` - remove the record.
* `pk()` - return the primary key value.

**Manager methods (`Model.objects`):**

* `create(**kwargs)` - insert a new record.
* `get(**kwargs)` - return the first matching record or `None`.
* `get_or_create(**kwargs)` - return an existing record or create it.
* `all()` - return all records.
* `update(obj)` - update an existing record.
* `delete(**kwargs)` - remove a record by field values.
* `clear()` - remove all records.

### Field types

* `IntegerField()` - integer field.
* `StringField()` - string field.
* `ListField()` - list field.
* `DictField()` - dictionary field.

## License

This project is licensed under the [MIT License](LICENSE.md).
gdm-robotics 1.0.1
Google DeepMind Robotics Interfaces and utilities.
Requires Python: >=3.10
Keywords: RL, Reinforcement Learning, AI, ML

# `gdm_robotics`: The Google DeepMind Robotics interfaces

This package describes a set of interfaces for Python reinforcement learning
(RL) environments. It consists of the following core components:

*   `gdm_robotics.interfaces.Environment`: An abstract base class for RL environments.
*   `gdm_robotics.interfaces.Policy`: An abstract base class for Agent policies.
*   `gdm_robotics.interfaces.EpisodicLogger`: An abstract base class for loggers for Agent/Environment interaction.
*   `gdm_robotics.runtime.RunLoop`: A concrete RunLoop class to run a policy against an environment and logging their interaction.

## Adapters

Common RL environment libraries such as `dm_env.Environment` and `gymnasium.Env`
can be exposed as `gdm_robotics.interfaces.Environment`s by using the provided
environment wrappers in the `adapter` sub-package, e.g. to wrap a
`dm_env.Environment` object:

```py
from gdm_robotics.adapters import dm_env_to_gdmr_env_wrapper

original_env: dm_env.Environment = ...
env = dm_env_to_gdmr_env_wrapper.DmEnvToGdmrEnvWrapper(original_env)
```

## Installation

`gdm_robotics` can be installed from PyPI using `pip`:

```bash
pip install gdm_robotics
```

## Licence and Disclaimer

Copyright 2025 Google LLC

All software is licensed under the Apache License, Version 2.0 (Apache 2.0); you
may not use this file except in compliance with the Apache 2.0 license. You may
obtain a copy of the Apache 2.0 license at: https://www.apache.org/licenses/LICENSE-2.0

All other materials are licensed under the Creative Commons Attribution 4.0
International License (CC-BY). You may obtain a copy of the CC-BY license at:
https://creativecommons.org/licenses/by/4.0/legalcode

Unless required by applicable law or agreed to in writing, all software and
materials distributed here under the Apache 2.0 or CC-BY licenses are
distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
either express or implied. See the licenses for the specific language governing 
permissions and limitations under those licenses.

This is not an official Google product.
sdcp-printer 0.4.1
API to communicate with 3D printers using the SDCP protocol.
Requires Python: >=3.11

# sdcp-printer-api
API to communicate to devices (mostly 3D printers) via the SDCP protocol.

See the following for the spec:
https://github.com/cbd-tech/SDCP-Smart-Device-Control-Protocol-V3.0.0/blob/main/SDCP(Smart%20Device%20Control%20Protocol)_V3.0.0_EN.md