semvec/pypi-packages huggingface dataset:
boto3-pydantic-kinesis-video-archived-media 1.0.2
Pydantic models for AWS Kinesis_video_archived_media
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kinesis_video_archived_media

# boto3-pydantic-kinesis_video_archived_media

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kinesis_video_archived_media.
boto3-pydantic-kinesis 1.0.2
Pydantic models for AWS Kinesis
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kinesis

# boto3-pydantic-kinesis

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kinesis.
boto3-pydantic-keyspaces 1.0.2
Pydantic models for AWS Keyspaces
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, keyspaces

# boto3-pydantic-keyspaces

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Keyspaces.
boto3-pydantic-kendra-ranking 1.0.2
Pydantic models for AWS Kendra_ranking
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kendra_ranking

# boto3-pydantic-kendra_ranking

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kendra_ranking.
boto3-pydantic-kendra 1.0.2
Pydantic models for AWS Kendra
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kendra

# boto3-pydantic-kendra

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kendra.
boto3-pydantic-kafkaconnect 1.0.2
Pydantic models for AWS Kafkaconnect
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kafkaconnect

# boto3-pydantic-kafkaconnect

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kafkaconnect.
boto3-pydantic-kafka 1.0.2
Pydantic models for AWS Kafka
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, kafka

# boto3-pydantic-kafka

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Kafka.
boto3-pydantic-ivschat 1.0.2
Pydantic models for AWS Ivschat
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, ivschat

# boto3-pydantic-ivschat

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Ivschat.
afterquote 0.2.1
Synthetic after-hours quote generator
Requires Python: >=3.8

# afterquote

**Synthetic after-hours quote generator based on an asset and its underlying security.**

[![PyPI version](https://img.shields.io/pypi/v/afterquote)](https://pypi.org/project/afterquote/)
[![CI](https://github.com/Junaid2005/afterquote/actions/workflows/pipeline.yml/badge.svg)](https://github.com/Junaid2005/afterquote/actions/workflows/pipeline.yml)

---

## 📦 What is this?

`afterquote` lets you estimate synthetic prices for a financial security based on the real-time performance of a given correlated underlying asset — useful when one market is closed and the other is still trading.

---

## 🚀 Installation

### From PyPI:
```bash
pip install afterquote
```

### Locally:

```bash
pip install -e .
```

## 🧪 Usage

```python
from afterquote import SecurityPair

pair = SecurityPair("MAG5.L", "MAGS")
print(pair.info())
print(pair.pricing())
```

## 📘 Example Output
```text
                          base_security underlying_security  base_is_live  leverage           base_close_time  base_close_price  adj_percent_return  quote_price
quote_time
2025-05-17 00:59:00+01:00        MAG5.L                MAGS         False         5 2025-05-16 16:30:00+01:00            1160.0           -9.524988  1049.510137
```

```text
                             Impl_Open    Impl_High     Impl_Low   Impl_Close
Datetime
2025-05-16 16:30:00+01:00  1160.000000  1161.112373  1160.000000  1160.000000
2025-05-16 16:31:00+01:00  1166.674491  1166.895738  1166.450943  1160.000000
2025-05-16 16:32:00+01:00  1168.417608  1168.417608  1168.068568  1162.845038
2025-05-16 16:33:00+01:00  1168.910139  1169.357836  1168.869835  1164.448536
2025-05-16 16:34:00+01:00  1170.029168  1170.029168  1169.805191  1163.333992
...                                ...          ...          ...          ...
2025-05-17 00:55:00+01:00  1055.186402  1055.934313  1055.108109  1049.593529
2025-05-17 00:56:00+01:00  1054.805236  1054.805236  1054.187307  1049.603777
2025-05-17 00:57:00+01:00  1053.775354  1055.833509  1053.775354  1058.827009
2025-05-17 00:58:00+01:00  1054.804431  1054.804431  1054.186503  1046.453387
2025-05-17 00:59:00+01:00  1051.714787  1052.331267  1051.714787  1049.510137
```

## 🤝 Contributing

Feel free to open issues or submit pull requests if you find bugs or want to improve the package - Junaid :)


## 📄 License

MIT License. See the [LICENSE](./LICENSE) file for full details.
boto3-pydantic-ivs-realtime 1.0.2
Pydantic models for AWS Ivs_realtime
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, ivs_realtime

# boto3-pydantic-ivs_realtime

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Ivs_realtime.
boto3-pydantic-ivs 1.0.2
Pydantic models for AWS Ivs
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, ivs

# boto3-pydantic-ivs

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Ivs.
boto3-pydantic-iotwireless 1.0.2
Pydantic models for AWS Iotwireless
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotwireless

# boto3-pydantic-iotwireless

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotwireless.
my_chrome_bookmarks 1.2.0
Utils to load local chrome bookmarks.
Requires Python: >=3.8
Keywords: google, chrome, bookmarks

# my-chrome-bookmarks

[![PyPI version](https://badge.fury.io/py/my_chrome_bookmarks.svg)](https://badge.fury.io/py/my_chrome_bookmarks)

Python module to read local Chrome bookmarks.

Installation:

```sh
pip install my-chrome-bookmarks
```

Usage:

```python
import my_chrome_bookmarks

# Get the top-level folder.
# Equivalent to `my_chrome_bookmarks.bookmarks().bookmark_bar`
bookmarks = my_chrome_bookmarks.bookmark_bar()

# Note: `bookmarks.urls` and `bookmarks.folders` also exists
for bookmark in bookmarks:
    if bookmark.is_folder:  # Folder
        print(f'{bookmark.name} contain {bookmark.num_urls} urls')
    else:  # Url
        print(f'{bookmark.name}: {bookmark.url}')


bookmark = bookmarks['My folder']  # Access a specific bookmark or folder
```

See the [source code](https://github.com/Conchylicultor/my-chrome-bookmarks/blob/main/my_chrome_bookmarks/bookmarks.py) for the full API.
llm-fragments-pdf 0.1
Use PyMuPDF to insert PDFs as markdown
Requires Python: >=3.9

# llm-fragments-pdf

A fragment loader for [LLM](https://llm.datasette.io/) that converts PDF files into markdown plaintext using [PyMuPDF4LLM](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/index.html).

This is especially useful for models which don't support [attachments](https://llm.datasette.io/en/stable/python-api.html#attachments).

[![PyPI](https://img.shields.io/pypi/v/llm-fragments-pdf.svg)](https://pypi.org/project/llm-fragments-pdf/)
[![Changelog](https://img.shields.io/github/v/release/daturkel/llm-fragments-pdf?include_prereleases&label=changelog)](https://github.com/daturkel/llm-fragments-pdf/releases)
[![Tests](https://github.com/daturkel/llm-fragments-pdf/actions/workflows/test.yml/badge.svg)](https://github.com/daturkel/llm-fragments-pdf/actions/workflows/test.yml)
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/daturkel/llm-fragments-pdf/blob/main/LICENSE)

## Installation

Install this plugin in the same environment as [LLM](https://llm.datasette.io/):

```bash
llm install llm-fragments-pdf
```

## Usage

Use `-f 'pdf:filepath'` convert a pdf file to markdown text and insert that text as a fragment.

Example:

```bash
llm -f 'pdf:my_pdf.pdf' "What is this document about?"
```

The output includes:
- Filename
- PDF contents as markdown

## Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

```bash
cd llm-fragments-pdf
python -m venv venv
source venv/bin/activate
```

Install the dependencies and test dependencies:

```bash
pip install -e '.[test]'
```

To run the tests:

```bash
pytest
```

## Dependencies

- [PyMuPDF4LLM](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/index.html): For extracting markdown from PDFs
- [llm](https://llm.datasette.io/): The LLM CLI tool this plugin extends
boto3-pydantic-iottwinmaker 1.0.2
Pydantic models for AWS Iottwinmaker
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iottwinmaker

# boto3-pydantic-iottwinmaker

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iottwinmaker.
boto3-pydantic-iotthingsgraph 1.0.2
Pydantic models for AWS Iotthingsgraph
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotthingsgraph

# boto3-pydantic-iotthingsgraph

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotthingsgraph.
boto3-pydantic-iotsitewise 1.0.2
Pydantic models for AWS Iotsitewise
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotsitewise

# boto3-pydantic-iotsitewise

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotsitewise.
sampex 1.1.1
Programs to load and plot the SAMPEX satellite data.
Requires Python: >=3.9
Keywords: data science, SAMPEX, satellite, HILT, PET, LICA

# sampex
Easily load and plot data from the Solar Anomalous and Magnetospheric Particle Explorer (SAMPEX) satellite that operated from 1992-2012. This library currently downloads and loads data from the `HILT`, `PET`, and `LICA` instruments, as well as the `attitide` files.  

[Documentation](https://sampex.readthedocs.io/en/latest/)

The example plot below sums up what this library does. I generated it with this console command: ```plot_sampex 2007 1 20 --yscale log```
![Example SAMPEX data from the HILT, PET, and LICA instruments](https://github.com/mshumko/sampex/blob/aba90331438b1cc1152e99469df5a65847bc9535/sampex_example.png?raw=true)

# Install
Installing this package is as simple as
```bash
python3 -m pip install sampex
```

If you want to develop this package, run
```bash
git clone git@github.com:mshumko/sampex.git
cd sampex
```

Then one of these commands to install sampex into a virtual environment:
```bash
python3 -m pip install -e .
```
or 
```bash
python3 -m pip install -r requirements.txt 
```
# Get started
You can configure this package so it knows the top-level directory to search for (or save) the data to.

```bash
python3 -m sampex config
```
and paste the top-level SAMPEX data directory in the prompt.

## Examples
There are a handful of examples in the [documentation](https://sampex.readthedocs.io/en/latest/examples.html)
boto3-pydantic-iotsecuretunneling 1.0.2
Pydantic models for AWS Iotsecuretunneling
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotsecuretunneling

# boto3-pydantic-iotsecuretunneling

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotsecuretunneling.
boto3-pydantic-iotfleetwise 1.0.2
Pydantic models for AWS Iotfleetwise
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotfleetwise

# boto3-pydantic-iotfleetwise

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotfleetwise.
boto3-pydantic-iotfleethub 1.0.2
Pydantic models for AWS Iotfleethub
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotfleethub

# boto3-pydantic-iotfleethub

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotfleethub.
boto3-pydantic-iotevents-data 1.0.2
Pydantic models for AWS Iotevents_data
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotevents_data

# boto3-pydantic-iotevents_data

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotevents_data.
boto3-pydantic-iotevents 1.0.2
Pydantic models for AWS Iotevents
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotevents

# boto3-pydantic-iotevents

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotevents.
boto3-pydantic-iotanalytics 1.0.2
Pydantic models for AWS Iotanalytics
Requires Python: <4.0,>=3.9
Keywords: aws, boto3, pydantic, models, iotanalytics

# boto3-pydantic-iotanalytics

This package was automatically generated by aws-resource-validator repository.

For more information, visit:
- Package homepage: https://coreoxide.github.io/aws_resource_validator/
- GitHub repository: https://github.com/CoreOxide/aws_resource_validator
- PyPI project: https://pypi.org/project/aws-resource-validator/

Pydantic models for AWS Iotanalytics.
SplatLLM 0.1.0
SplatLLM makes text generated by large language models (LLMs) appear more authentically human via heuristic-based formatting.
Requires Python: >=3.10.12
Keywords: filter, invisible, mcp, text, watermark

# SplatLLM

SplatLLM makes text generated by large language models (LLMs) appear more authentically human via heuristic-based formatting. Broadly, this involves:

* Removal of [invisible characters](https://invisible-characters.com/) that can be used for watermarking and/or hiding information in plain text.
* Remapping of unusual characters typically produced my LLMs but not typically used by human writers. For example, the Unicode dash punctuations commonly generated by LLMs are remapped to standard ASCII hyphens.
* Removal of certain markdown formatting characteristically used by LLMs.

SplatLLM can also be used to reveal invisible characters and other unusual formatting via the ``splat --show-invisibles`` / ``splat -s`` command:

![SplatLLM text analysis sample](https://raw.githubusercontent.com/theobjectivedad/splat-llm/refs/heads/master/images/splat_llm_dump.webp)

*Coming soon will be an MCP version that will expose SplatLLM as a callable tool for agent-driven post-formatting.*

## Quickstart

Install/run via ``uvx``:

```shell
uvx splatllm
```

Or, install via pip:

```shell
pip install SplatLLM
```

Then run:

```shell
splatllm
```

## Development Setup

First, clone this repository:

```shell
git clone https://github.com/theobjectivedad/splat-llm.git
```

Change directory to the cloned repository:

```shell
cd splat-llm
```

Next, setup your local virtual environment. Note that [uv](https://github.com/astral-sh/uv) will be installed if it isn't found in the environment:

```shell
make venv
```