semvec/pypi-packages huggingface dataset:
poetry-jupyter-plugin 0.2.2
Poetry plugin to manage Jupyter kernels
License: MIT
Requires Python: <4.0,>=3.10
Keywords: poetry, poetry-plugin, plugin, jupyter, jupyter-kernel

# 📦 poetry-jupyter-plugin

## overview

This is a really simple plugin to allow you to install your
[Poetry](https://python-poetry.org) virtual environment as a
[Jupyter](https://jupyter.org) kernel. You may wish to do this to keep your
dependencies locked down for reproducible notebooks, or to set up a single
"data science" notebook for one-off calculations without fiddling about with
installing packages globally or dealing with `ipykernel` directly.

[![asciicast](https://asciinema.org/a/gZ79uCyWFZFTtp6J295YS5wpO.svg)](https://asciinema.org/a/gZ79uCyWFZFTtp6J295YS5wpO)

## getting started

Install the plugin with:

```sh
$ poetry self add poetry-jupyter-plugin
```

Then, from within your poetry project:

```sh
$ poetry add ipykernel -G dev
$ poetry jupyter install
```

Remove the kernelspec with:

```sh
$ poetry jupyter remove
```

### configuration

By default, the installed kernel will use the name of the project and a default
Poetry icon. To configure these options, add this block to your `pyproject.toml`:

```toml
[tool.jupyter.kernel]
name = "my-cool-kernel"
display = "My cool kernel"
icon = "/path/to/icon.png"
```

## prior art

There are other projects in this space, notably Pathbird's [`poetry-kernel`].
`poetry-kernel` installs a single kernelspec globally which then patches the
virtualenv based on the specific project folder that you're running Jupyter in.
This has some pros and cons over this project.

Pros:

1. Single kernelspec, avoiding polluting the kernelspec list with lots of specs.
2. Easy context switching between projects.

Cons:

1. Notebooks have to be in the same folder (or a subfolder from) as the
   `pyproject.toml` folder.
2. Requires forwarding signals from the launcher into Jupyter, introducing a
   layer of complexity and is brittle to changes in Jupyter protocol/underlying
   OS.
3. Implicit dependency on `ipykernel`, and may fail to start without it.

In contrast, this project installs one kernelspec per virtualenv and leaves it
up to Jupyter to launch the kernel normally without interception. This design
decision also allows multiple projects to be based out of one kernel.
Additionally, the tool checks for the existence of `ipykernel` to make sure
that the kernel can be installed properly.

## who?

This was written by [patrick kage](//ka.ge).
skymith 0.0.1
Flexible AI-driven services, everywhere, and for everyone.
License: MIT
Requires Python: <3.12,>=3.10

<p align="center">
  <!-- Login Badge -->
  <a href="https://skymith.com/login"><img src="../../docs/assets/favicon.png" alt="Login Badge"></a>
  <!-- Docker Badge -->
  <a href="https://hub.docker.com/u/skymith">
    <img src="https://img.shields.io/badge/Docker-2496ED?style=for-the-badge&logo=docker&logoColor=white" alt="Docker Badge">
  </a>
  <!-- LangChain Badge -->
  <a href="https://langchain.com/">
    <img src="https://img.shields.io/badge/LangChain-005A9C?style=for-the-badge&logo=langchain&logoColor=white" alt="LangChain Badge">
  </a>
</p>

# Skymith

## Description

Skymith provides advanced AI capabilities to developers and companies alike. Learn more at https://skymith.com.

## Development

  1. Install [PDM](https://pdm.fming.dev/latest/#installation).

  2. Clone the project and install necessary packages:
```bash
# clone project
git clone https://github.com/Mitheithel/skymith.git
cd skymith

# install pdm
pip install pdm

# install package
pdm install -dG :all
```
loggex 0.1.0
A flexible experiment logging library for research and machine learning projects
License: MIT
Requires Python: >=3.7

# Loggex

Loggex helps you track your research experiments across multiple scripts by providing a central log file to record which script produced what results with which configuration.

## Features

- Track experiment runs in CSV, JSON, or Excel format
- Load and add to your experiment log from any script
- Automatic timestamp tracking for each run
- Simple querying and filtering capabilities
- Quick summary reports of your experiments

## Installation

```bash
pip install loggex
```

## Quick Start

### Creating a New Log

```python
from loggex import Project

# Create a new experiment log (defaults to CSV format)
project = Project.new(
    name="sentiment_experiments",
    path="logs",
    columns=["experiment", "script", "model", "lr", "bs", "max_len", "f1_score", "results_file"]
)

# Log an experiment run
project.add(
    experiment="bert_base",
    script="train_bert.py",
    model="bert-base-uncased",
    lr=2e-5,
    bs=16,
    max_len=128,
    f1_score=0.91,
    results_file="results/bert_base_full.csv"
)
```

### Adding Results from Another Script

```python
from loggex import Project

# Load the existing log
project = Project.load("sentiment_experiments", path="logs")

# Add results from this script
project.add(
    experiment="bert_large",
    script="train_bert_improved.py",
    model="bert-large-uncased",
    lr=3e-5,
    bs=8,
    max_len=256,
    f1_score=0.94,
    results_file="results/bert_large_full.csv"
)

# View latest runs
project.tail()
```

### Analyzing Your Experiments

```python
# Generate a summary report
project.report()

# Filter experiments
best_runs = project.filter("f1_score > 0.92")
print(best_runs)

# Remove failed runs
project.remove("f1_score < 0.5")

# Export filtered results
project.export(
    format='excel',  # 'csv', 'json', or 'excel'
    query="model == 'bert-base-uncased'",
    path="analysis/bert_base_results.xlsx"
)
```

### Using Different Formats

By default, Loggex uses CSV files, but you can choose other formats:

```python
# Create a new log in Excel format
project = Project.new(
    name="mnist_experiments",
    path="logs",
    columns=["experiment", "script", "accuracy"],
    format='excel'  # 'csv', 'json', or 'excel'
)
```

## Documentation

The `Project` class supports:
- Creating new logs (`new()`)
- Loading existing logs (`load()`)
- Adding log entries (`add()`) with automatic timestamp tracking
- Printing all logs (`print()`)
- Viewing latest entries (`tail(n=5)`)
- Removing entries (`remove(query)`)
- Generating detailed reports (`report()`)
- Exporting filtered results (`export(format, query, path)`)

See in-line docstrings in the source code for complete usage details.

## License

Licensed under the MIT License.
pymedx 0.5.1
PyMedX is a tool set for handling multimedia files.
License: MIT
Requires Python: <4,>3.9

> PyMedX is a fork from a archived project called PyMed:
> https://github.com/gijswobben/pymedx

# PyMedX - PubMed Access through Python

PyMedX is a Python library that provides access to PubMed through the PubMed
API.

## Why this library?

The PubMed API is not very well documented and querying it in a performant way
is too complicated and time consuming for researchers. This wrapper provides
access to the API in a consistent, readable and performant way.

## Features

This library takes care of the following for you:

- Querying the PubMed database (with the standard PubMed query language)
- Batching of requests for better performance
- Parsing and cleaning of the retrieved articles

## Examples

For full (working) examples have a look at the `examples/` folder in this
repository. In essence you only need to import the `PubMed` class, instantiate
it, and use it to query:

```python
from pymedx import PubMed
pubmed = PubMed(tool="MyTool", email="my@email.address")
results = pubmed.query("Some query", max_results=500)
```

## Notes on the API

The original documentation of the PubMed API can be found here:
[PubMed Central](https://www.ncbi.nlm.nih.gov/pmc/tools/developers/). PubMed
Central kindly requests you to:

> - Do not make concurrent requests, even at off-peak times; and
> - Include two parameters that help to identify your service or application to
>   our servers
>   - _tool_ should be the name of the application, as a string value with no
>     internal spaces, and
>   - _email_ should be the e-mail address of the maintainer of the tool, and
>     should be a valid e-mail address.

## Notice of Non-Affiliation and Disclaimer

The author of this library is not affiliated, associated, authorized, endorsed
by, or in any way officially connected with PubMed, or any of its subsidiaries
or its affiliates. The official PubMed website can be found at
https://www.ncbi.nlm.nih.gov/pubmed/.