semvec/pypi-packages huggingface dataset:
shopcloud-organize 0.0.0
CLI tool for task management @talk-point
License: MIT
Requires Python: >=3.10
Keywords: CLI

# Organize

Organize tasks @talk-point

## Install

```sh
$ pip3 install shopcloud-organize
```

## Usage

Monatlichen / wöchentliche tasks im Hauptrepo erzeugen

```sh
$ organize tasks list
$ organize tasks create-issues
```
forward-backward 0.1.0
A Python package for forward and backward operations
License: MIT
Requires Python: >=3.8

# forward-backward

A Python package for forward and backward operations

## Installation

```bash
uv pip install forward-backward
# or
pip install forward-backward
```

## Usage

```python
import forward_backward

# Your code here
```

## Development

```bash
# Install in development mode with uv
uv pip install -e ".[dev]"

# Run tests
uv run pytest

# Format code
uv run black src tests

# Type check
uv run mypy src
```

## Building and Publishing

```bash
# Build the package
uv build

# Publish to PyPI
uv publish
```

## License

MIT License - see LICENSE file for details.
llm-rpc 0.1.0
A Python package for LLM RPC operations
License: MIT
Requires Python: >=3.8

# llm-rpc

A Python package for LLM RPC operations

## Installation

```bash
uv pip install llm-rpc
# or
pip install llm-rpc
```

## Usage

```python
import llm_rpc

# Your code here
```

## Development

```bash
# Install in development mode with uv
uv pip install -e ".[dev]"

# Run tests
uv run pytest

# Format code
uv run black src tests

# Type check
uv run mypy src
```

## Building and Publishing

```bash
# Build the package
uv build

# Publish to PyPI
uv publish
```

## License

MIT License - see LICENSE file for details.
kyutils 0.1.121
kyu's utils
License: MIT
Requires Python: <3.14,>=3.9

# kyutils

kyu's utils

## examples
- behavior
  - given the extracted DIO dat files from a SpikeGadgets `rec` file, plots the time course of the animal's decisions in the W-track task and indicates rewarded trials
  - plots place field
  - figures out the 2d distance by constructing a graph from trajectories
- nwb
  - basic NWB conversion of ephys data
- probe
  - `probeinterface.Probe` objects for the 15um and 20um versions of the Livermore polymer probes
- spikegadgets
  - generates a trodesconf file based on a list of Livermore probe types; e.g. if implanting three Livermore probes (one 15um type and two 20um type) in alternating order, can pass the list `[20, 15, 20]` and will generate a trodesconf file with the contacts arranged geometrically
  - generate a trodesconf file given the number of channels; good for reconfiguring
  - parses the header of a SpikeGadgets `rec` file
- spikesorting
  - plots spike waveform in probe geometry
  - computes standard metrisc for frank lab
  - generates figurl

## installation
`pip install kyutils`

for the version that creates figurls, do `pip install "kyutils[figurl]"` and set up `kachery-cloud`.
prometheus-quick-analysis 0.1.0
A sample pip package
License: MIT
Requires Python: >=3.8

# prometheus-analyzer


- Parse metrics safely (supports counters/gauges/histograms/summaries)
- Produce a basic analysis report:

  - total families, total samples

  - top metrics by sample count

  - label cardinality (unique labelsets) per metric

  - optional filter by metric name regex

  - optional “diff” between two snapshots (helpful in PR context)
fyle-integrations-platform-connector 2.9.0
A common platform connector for all the Fyle Integrations to interact with Fyle Platform APIs
License: MIT
Keywords: fyle, api, python, integration, platform, connector

# Fyle Integrations Platform Connector

## Installation and Usage

A common platform connector for all the Fyle Integrations to interact with Fyle's Platform APIs

`pip install fyle-integrations-platform-connector`

##### In Django `settings.py`

    INSTALLED_APPS = [
        'django.contrib.admin',
        'django.contrib.auth',
        'django.contrib.contenttypes',
        'django.contrib.sessions',
        'django.contrib.messages',
        'django.contrib.staticfiles',
    
        # Installed Apps
        'rest_framework',
        'corsheaders',
        'fyle_rest_auth', # already existing reusable django app for authentication
        'fyle_accounting_mappings', # already existing mapping infra app,
        'fyle_integrations_platform_connector', # new platform connector
    
        # User Created Apps
        'apps.users',
        'apps.workspaces',
        'apps.mappings',
        'apps.fyle',
        'apps.quickbooks_online',
        'apps.tasks'
    ]


##### Usage

```
from fyle_integrations_platform_connector import PlatformConnector

connector = PlatformConnector(fyle_credential=fyle_credential)

# Get Expenses
expenses = connector.expenses.get(
    source_account_type=['PERSONAL_CASH_ACCOUNT', 'PERSONAL_CORPORATE_CREDIT_CARD_ACCOUNT'],
    state='PAID',
    last_synced_at='2021-08-22T00:00:000.000Z',
    filter_credit_expenses=True
)

# Import Fyle dimensions
connector.import_fyle_dimensions()

# Import specific Fyle dimensions
connector.employees.sync()
connector.projects.sync()
```

## Local Development
### Setup

Setup virtual environment and install dependencies -
```
python3 -m venv venv && source venv/bin/activate && pip install -r requirements.txt
```

Copy sample secrets file and add secret environment variables -
```
cp sample_secrets.sh secrets.sh
```

Copy sample script file -
```
cp script.py raw_script.py
```


##### Run a raw python script [(script.py)](https://github.com/fylein/fyle-integrations-platform-connector/blob/master/script.py)
```
bash run.sh
```

##### Open SQLITE db and check data
```
sqlite3 db.sqlite3

-- Example query
select attribute_type, count(*) from expense_attributes group by attribute_type;
```
tuto-python-setup-package 0.1.0
Tutorial package for Python setup workflow
License: MIT
Requires Python: >=3.12

# tuto-python-setup-package

<p align="center">
  <a href="https://github.com/JarryGabriel/tuto-python-setup-package/actions/workflows/ci.yml"><img src="https://github.com/JarryGabriel/tuto-python-setup-package/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
  <a href="https://coveralls.io/github/JarryGabriel/tuto-python-setup-package?branch=main"><img src="https://coveralls.io/repos/github/JarryGabriel/tuto-python-setup-package/badge.svg?branch=main" alt="Coverage"></a>
  <a href="https://pypi.org/project/tuto-python-setup-package/"><img src="https://img.shields.io/pypi/v/tuto-python-setup-package" alt="PyPI"></a>
  <img src="https://img.shields.io/badge/python-3.12%2B-blue" alt="Python 3.12+">
  <img src="https://img.shields.io/badge/typed-strict-blue" alt="Typed">
  <a href="https://github.com/astral-sh/ruff"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff"></a>
  <a href="https://github.com/astral-sh/uv"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json" alt="uv"></a>
  <a href="https://JarryGabriel.github.io/tuto-python-setup-package/"><img src="https://img.shields.io/badge/docs-live-brightgreen" alt="Docs"></a>
</p>

> Tutorial package for Python setup workflow

## Installation

```bash
uv add tuto-python-setup-package
```

## Quick Start

```python
from tuto_python_setup_package import hello

print(hello())
```

## Development

```bash
git clone https://github.com/JarryGabriel/tuto-python-setup-package.git
cd tuto-python-setup-package
make install
make check
```

## License

MIT - See [LICENSE](LICENSE) for details.
vidhash 0.3.2
A package for hashing videos and checking for similarity
License: MIT
Requires Python: <4.0,>=3.10

# Vidhash
[Vidhash](https://pypi.org/project/vidhash/) is a perceptual video hashing and checking library, to detect similar videos, or videos containing similar scenes.

## How it works
Basically, this video hashing works by scaling the video down a bit, and taking 5 frames a second as images, and performing image hashes on those frames.
Then it can do checks by checking how many image hashes from one video match up with image hashes from another.

## How to use
This documentation is a little sparse at the moment, but the basic summary is that to hash a video, use `video_hash = hash_video(video_path)`.  
This returns a `VideoHash` object.  
You can also provide a `HashSettings` object. HashSettings need to match for two video hashes to be compared.
Currently HashSettings allow specifying the

When checking video hashes against each-other, use `video_hash.check_match(other_hash)`.
You can optionally provide a `MatchOptions` object as a second argument, or use a MatchOptions object and call the `MatchOptions.check_match(hash1, hash2)` method on it.

There are 3 supported types of MatchSettings:
- `FrameCountMatch`
  - Checks whether a specified number of frames match between the two videos
  - Allows specifying the hamming distance between two frames which should be considered a "match"
  - Allows ignoring blank frames
- `PercentageMatch`
  - Checks whether a specified percentage of the shorter video's frames match the longer video
  - Allows specifying the hamming distance between two frames which should be considered a "match"
  - Allows ignoring blank frames
- `DurationMatch`
  - Checks whether a specified "duration" of frames match up in order between the two videos
    - e.g. 3 seconds duration, at 5 fps, would check whether 15 frames match, in a row, between the two videos
  - Allows specifying the hamming distance between two frames which should be considered a "match"


## Todo
- Code
  - Wrapper for imagehash.ImageHash
  - Datastore
    - (For looking up matching videos from a collection)
- More documentation
- More tests
python-tuto-agent-init 0.1.0
A modern Python tutorial for agent initialization
License: MIT
Requires Python: >=3.12

# python-tuto-agent-init

<p align="center">
  <a href="https://github.com/JarryGabriel/python-tuto-agent-init/actions/workflows/ci.yml"><img src="https://github.com/JarryGabriel/python-tuto-agent-init/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
  <a href="https://coveralls.io/github/JarryGabriel/python-tuto-agent-init?branch=main"><img src="https://coveralls.io/repos/github/JarryGabriel/python-tuto-agent-init/badge.svg?branch=main" alt="Coverage"></a>
  <a href="https://pypi.org/project/python-tuto-agent-init/"><img src="https://img.shields.io/pypi/v/python-tuto-agent-init" alt="PyPI"></a>
  <img src="https://img.shields.io/badge/python-3.12%2B-blue" alt="Python 3.12+">
  <img src="https://img.shields.io/badge/typed-strict-blue" alt="Typed">
  <a href="https://github.com/astral-sh/ruff"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff"></a>
  <a href="https://github.com/astral-sh/uv"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json" alt="uv"></a>
  <a href="https://JarryGabriel.github.io/python-tuto-agent-init/"><img src="https://img.shields.io/badge/docs-live-brightgreen" alt="Docs"></a>
</p>

> A modern Python tutorial for agent initialization

## Installation

```bash
uv add python-tuto-agent-init
```

## Quick Start

```python
from python_tuto_agent_init import hello

print(hello())
```

## Development

```bash
git clone https://github.com/JarryGabriel/python-tuto-agent-init.git
cd python-tuto-agent-init
make install
make check
```

## License

MIT - See [LICENSE](LICENSE) for details.
prometheus-analysis-1 0.1.3
A sample pip package
License: MIT
Requires Python: >=3.8

# prometheus-analyzer


- Parse metrics safely (supports counters/gauges/histograms/summaries)
- Produce a basic analysis report:

  - total families, total samples

  - top metrics by sample count

  - label cardinality (unique labelsets) per metric

  - optional filter by metric name regex

  - optional “diff” between two snapshots (helpful in PR context)