semvec/pypi-packages huggingface dataset:
brk-client 0.1.9
Python client for the Bitcoin Research Kit
Requires Python: >=3.9
Keywords: analytics, bitcoin, blockchain, on-chain

# brk-client

Python client for the [Bitcoin Research Kit](https://github.com/bitcoinresearchkit/brk) API.

Requires Python 3.9+. Zero dependencies.

[PyPI](https://pypi.org/project/brk-client/) | [API Reference](https://github.com/bitcoinresearchkit/brk/blob/main/packages/brk_client/DOCS.md)

## Installation

```bash
pip install brk-client
# or
uv add brk-client
```

Or just copy [`brk_client/__init__.py`](./brk_client/__init__.py) into your project - it's a single file with no dependencies.

## Quick Start

```python
from brk_client import BrkClient

# Use the free public API or your own instance
# Has optional `, timeout=60.0` argument
client = BrkClient("https://bitview.space")

# Blockchain data (mempool.space compatible)
block = client.get_block_by_height(800000)
tx = client.get_tx("abc123...")
address = client.get_address("bc1q...")

# Metrics API - typed, chainable
prices = client.metrics.price.usd.split.close \
    .by.dateindex() \
    .tail(30) \
    .fetch()  # Last 30 items

# Generic metric fetching
data = client.get_metric("price_close", "dateindex", -30)
```
extraetf-scraper 0.1.3
Web scraper for ETF data from extraetf website.
Requires Python: >=3.12

# extraetf-scraper

This is a web scraper for ETF (and stock) data from the extraetf website.

[Extraetf](https://extraetf.com) is a German website, that provides information
about ETFs, stocks, funds and crypto. It offers the ability to search, sort and filter ETFs 
and stocks by many metrics.

This Python package makes accessing the data from extraetf easier.  

## Usage

Install the package from PyPi

    $ pip install extraetf-scraper

To import do 

    >>> from extraetf import etfs, stocks

Search for 100 stocks with highest performance last year and a marketcap > 10 billion EUR. 

    >>> response = stocks.search(sort_by="calculated_return_price_1y", ordering="desc", limit=100, filters={"ms_marketcap": {"gt": 10000000000}})

You can then show the top10 results like

    >>> for entry in response[:10]:
    ...     print(entry["year_1"], entry["isin"], entry["name"])
    ... 
    994.8275862 JP3236330001 Kioxia Holdings Corp
    513.3682831 US7731221062 Rocket Lab USA Inc
    495.1188986 US5017971046 L Brands Inc
    435.3982301 CNE100001T72 Yangtze Optical Fibre and Cable Joint Stock Ltd Co
    370.2093398 GB00B2QPKJ12 Fresnillo PLC
    321.0526316 JP3148800000 Ibiden Co Ltd
    306.25 US78392B1070 SK Hynix Inc
    297.1493729 US5951121038 Micron Technology Inc.
    283.9276323 IE00BKVD2N49 Seagate Technology Holdings PLC
    274.3169399 US82575P1075 Sibanye Stillwater Ltd (ADR)

You can show all possible sort options for ETFs like

    >>> etfs.show_sort_options()
    ['symbol', 'market_cap', 'return_year_to_date_real', 'ter', ...

Search for 500 ETFs with highest Sharpe ratio last year

    >>> response = etfs.search(sort_by="sharpe_ratio_1_year", ordering="desc", limit=500)
    >>> for entry in response[:10]:
    ...     print(entry["sharpe_1"], entry["year_1"], entry["isin"], entry["name"])
    ... 
    18.42 None LU1190417599 Amundi Smart Overnight Return UCITS ETF C-EUR
    18.37 None LU2082999306 Amundi Smart Overnight Return UCITS ETF D-EUR
    12.34 2.44698 LU2898088419 Ossiam Serenity Euro
    4.55 38.01092 LU1812092168 Amundi Stoxx Europe Select Dividend 30 UCITS ETF
    4.54 2.50162 IE00BD9MMF62 JPMorgan EUR Ultra-Short Income Active UCITS ETF (Acc)
    4.53 38.30012 DE0002635299 iShares STOXX Europe Select Dividend 30 UCITS ETF (DE)
    4.47 2.56119 IE00BCRY6557 iShares € Ultrashort Bond UCITS ETF (Dist)
    4.42 2.56116 IE000RHYOR04 iShares € Ultrashort Bond UCITS ETF (Acc)
    4.36 45.89505 LU0592216393 Xtrackers Spain UCITS ETF (Acc)
    4.36 45.93412 LU0994505336 Xtrackers Spain UCITS ETF (Dist)

For more examples have a look at the jupyter notebooks in the [notebooks](https://github.com/asmaier/extraetf/tree/main/notebooks) directory.
tsp 1.10.5
Making permafrost data effortless

# Teaspoon

## See the full documentation on the [ReadTheDocs Pages](https://permafrostnet.gitlab.io/teaspoon/source/about.html)

## [What is it?](https://permafrostnet.gitlab.io/teaspoon/source/about.html)
`tsp` ('teaspoon') is a python library designed to make working with permafrost ground temperature time series data more straightforward, efficient, and reproduceable. Some of the features include:

* Read a variety of common published data formats, datalogger outputs, and model results into a common data structure
    * GEOtop model output
    * GTN-P database export csv
    * NTGS ground temperature report csv
    * Geoprecision datalogger export
    * HoboWare datalogger export
* Export data in a variety of common formats
    * TSP-recommended csv format
    * netcdf
    * 'GTN-P'-style csv
    * 'NTGS'-style csv
* Perform common data transformations
    * Calculate daily, monthly, or yearly means, ignoring averaging periods with missing data
    * Switch between "long" and "wide" dataframes
* Visualize and explore your data with commonly used plots
    * Trumpet curves
    * Temperature-time graphs
    * Colour-contour profiles

## [Installation](https://permafrostnet.gitlab.io/teaspoon/source/install.html)

## [Usage Examples](https://permafrostnet.gitlab.io/teaspoon/source/examples.html)

## [How to contribute](https://permafrostnet.gitlab.io/teaspoon/source/contributions.html)

## Data Standard
TSP also defines a recommended csv format for ground temperature data (which can also be extended to many other kinds of permafrost data). It is described in the [DATA_STANDARD.md](./DATA_STANDARD.md) file in this directory. Files can be read (using the `TSP.to_csv` method) and written (using `read_tsp`) using the teaspoon software package. 

## Citation
If you find this software helpful, please consider using the following citation:

> Brown, N., (2022). tsp ("Teaspoon"): A library for ground temperature data. Journal of Open Source Software, 7(77), 4704, [https://doi.org/10.21105/joss.04704](https://doi.org/10.21105/joss.04704)
pachinkoagentic 0.0.4
agentic toolkit built on MCP that provides description and status of work
Requires Python: >=3.12
Keywords: agentic, mcp

PachinkoAgentic is an agentic workflow package.



Usage:



1.)  Build a class derived from pachinkoagentic.AIWrapper.  This exposes get\_response and get\_streaming\_response methods and handle interactions with an SLM for generating python code.  (see https://github.com/drwilliamroney/PachinkoTestClient/blob/main/localollama.py)

2.)  Instantiate an instance of pachinkoagentic.Library and use .add(fastmcp.Client()) for each MCP server you want to include.

3.)  Create a pachinkoagent.Workflow object passing in a link to an LM for generating code, and another for LLM Samples (per MCP definition, calls from agentic workflow to an LLM for an answer).

4.)  There are 2 async generator calls:

&nbsp;    a.)  workflow.generate(question)

&nbsp;    b.)  workflow.process()



Workflow generate calls the agentic\_code\_generator asking it to construct both a Python function and a SVG flowchart which return on the generator.  See pachinkoagentic.WorkflowEventType.



Workflow process executes the returned python function wrapping any calls to the MCP services.
TyphoonTest 1.35.3
Typhoon Testing Utilities
Requires Python: <3.13,>=3.10

Description
===========
TyphoonTest is a testing framework that provides high-level functions to test power electronics
and power systems equipment. It also provides integration with pytest and Allure framework.
Thanks to this integration, all Typhoon HIL API and TyphoonTest functions used in pytest tests are automatically logged
in Allure report.

Requirements
============
Typhoon API requires Typhoon HIL Control Center (with an appropriate license)
to be installed.
For other requirements, they will be automatically installed when you perform
installation using pip.

Installation
============
Package is available on PyPI

To install TyphoonTest library use:
    ``pip install typhoontest``
test-uv-app2 0.0.1
A short description of the project
Requires Python: >=3.10

# test-uv-app2

A short description of the project

## Overview

This documentation covers the test-uv-app2 application.

## Installation

```bash
pip install test-uv-app2
```

Or, if you use UV:

```bash
uv add test-uv-app2
```

## Usage

Run the application:

```bash
test_uv_app2
```

Or run as a module:

```bash
python -m test_uv_app2
```

## Quick Start

```bash
pip install test-uv-app2

test_uv_app2
```
test-poetry-app 0.0.1
A short description of the project
Requires Python: >=3.10

# test-poetry-app

A short description of the project

## Overview

This documentation covers the test-poetry-app application.

## Installation

```bash
pip install test-poetry-app
```

Or, if you use Poetry:

```bash
poetry add test-poetry-app
```

## Usage

Run the application:

```bash
test_poetry_app
```

Or run as a module:

```bash
python -m test_poetry_app
```

## Quick Start

```bash
pip install test-poetry-app

test_poetry_app
```