semvec/pypi-packages huggingface dataset:
ECmean4 0.1.16
ECmean4 Global Climate Model lightweight evaluation tool
Requires Python: >=3.9

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![ECmean4](docs/ecmean4_smallest.png)

*A lightweight climate model evaluation tool*

ECmean4 is a lightweight parallelized tool for evaluation of basic properties of Global Climate Models, such as global mean and climate model performance indices.

It builds on the original ECmean which has been used for EC-Earth2 and EC-Earth3 evaluation, but it uses Python3 as a scripting language to perform lazy calls with ``Xarray``+``Dask`` and makes use of YML configuration files, with parallelization support with ``Multiprocess``. 
It works both on raw EC-Earth4 output and on CMOR model output from CMIP5 and CMIP6.

ECmean4 is under development, so please use it with caution!

A complete [ReadTheDocs Documentation](https://ecmean4.readthedocs.io/en/latest/index.html) is available, please refer to this.
turboseo 0.3.0
SEO content toolkit that writes human, not AI
Requires Python: >=3.10
Keywords: ai-detection, claude-code, content, marketing, seo, writing

# TurboSEO

An open-source SEO content toolkit that helps you write content that ranks—and sounds human.

## Why TurboSEO?

Most SEO tools help you optimize for search engines. TurboSEO also optimizes for **not sounding like AI wrote it**.

Based on [Wikipedia's "Signs of AI Writing"](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) guidelines, TurboSEO checks your content for:

- AI vocabulary (delve, tapestry, pivotal, etc.)
- Puffery patterns ("plays a vital role", "stands as a testament")
- Superficial analysis (sentences ending with "highlighting...", "emphasizing...")
- Structural clichés ("In conclusion", "Despite challenges...")

## Features

- **Human Writing Score** (0-100) - Detect AI-sounding patterns
- **SEO Analysis** - Keywords, readability, structure
- **CLI Tool** - Quick analysis from terminal
- **Claude Code Integration** - Slash commands and agents

## Installation

```bash
pip install turboseo
```

For development:

```bash
git clone https://github.com/wavyrai/turboseo.git
cd turboseo
pip install -e ".[dev]"
```

## Quick Start

### Check if content sounds human

```bash
turboseo check article.md
```

### Full SEO analysis

```bash
turboseo analyze article.md --keyword "podcast hosting"
```

### Use with Claude Code

```bash
cd your-content-project
# Copy .claude/ directory from turboseo
/write podcast monetization strategies
```

## Commands

| Command | Description |
|---------|-------------|
| `turboseo check <file>` | Check for AI writing patterns |
| `turboseo analyze <file>` | Full SEO analysis |
| `turboseo readability <file>` | Readability analysis |
| `turboseo keywords <file> -k <keyword>` | Keyword analysis |

## Human Writing Score

TurboSEO scores your content from 0-100:

| Score | Grade | Meaning |
|-------|-------|---------|
| 90-100 | A | Sounds human |
| 80-89 | B | Minor AI tells |
| 70-79 | C | Noticeable AI patterns |
| 60-69 | D | Obvious AI writing |
| <60 | F | Clearly AI-generated |

## Documentation

- [Getting Started](docs/getting-started.md)
- [Human Writing Standards](docs/human-writing-standards.md)
- [CLI Reference](docs/cli-reference.md)
- [Claude Code Integration](docs/claude-code-integration.md)
- [Analyzers Reference](docs/analyzers.md)

## Contributing

Contributions are welcome! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

## License

MIT License - see [LICENSE](LICENSE) for details.
cdes-c 0.1.0
CDES Commerce Extension - GS1/EDI/Inventory data models for cannabis commerce
Requires Python: >=3.10
Keywords: cannabis, commerce, compliance, edi, gs1, inventory

﻿# CDES-C: Cannabis Data Exchange Standard - Commerce Extension

Enterprise commerce SDK for cannabis retail integration. Part of the [CDES](https://cdes.dev) ecosystem.

## Features

- **GS1 Standards** - GTIN, GLN, SSCC, DataMatrix barcodes
- **EDI X12** - Purchase orders (850), acknowledgments (855), ASN (856), invoices (810)
- **Product Catalog** - Cannabis product management with COA links
- **Inventory** - Real-time stock tracking and movements
- **Compliance** - License verification, chain of custody

## Platform Integrations

| Platform | Type | Status |
|----------|------|--------|
| Shopify | E-commerce |  Coming |
| WooCommerce | E-commerce |  Coming |
| BigCommerce | E-commerce |  Coming |
| Square | POS |  Coming |
| Dutchie | Cannabis POS |  Coming |
| Treez | Cannabis POS |  Coming |

## Installation

```bash
pip install cdes-c
```

## Quick Start

```python
from cdes_c import CannabisProduct, PurchaseOrder, ProductCategory
from cdes_c.gs1 import GTINManager

# Create a product with GS1 identifiers
product = CannabisProduct(
    sku="FL-OG-3.5",
    gtin=GTINManager.generate_gtin14("0012345"),
    name="OG Kush - 3.5g",
    category=ProductCategory.FLOWER,
    strain_name="OG Kush",
    thc_percentage=Decimal("24.5"),
    coa_url="https://lab.example.com/coa/12345"
)

# Create a purchase order
po = PurchaseOrder(
    po_number="PO-2026-001",
    buyer_gln="0012345000001",
    seller_gln="0098765000001"
)
```

## Documentation

- [Full Documentation](https://cdes.dev/docs/commerce)
- [GS1 Integration Guide](https://cdes.dev/guides/gs1)
- [EDI Implementation](https://cdes.dev/guides/edi)

## License

MIT License - see [LICENSE](LICENSE) for details.
cdes-fs 0.1.0
CDES Food Service Extension - Cannabis ingredient and recipe data models for culinary applications
Requires Python: >=3.10
Keywords: COA, cannabis, dosing, edibles, food-service, recipes, terpenes

﻿# CDES-FS: Cannabis Data Exchange Standard - Food Service Extension

Food service SDK for cannabis-infused culinary applications. Part of the [CDES](https://cdes.dev) ecosystem.

## Features

- **COA Integration** - Link recipes to lab test data
- **Terpene Pairing** - Flavor suggestions based on terpene profiles
- **Dosage Calculation** - Precise THC/CBD per serving
- **Recipe Management** - Cannabis-infused recipe database
- **Compliance** - Food safety and lot tracking

## Use Cases

- Cannabis-infused restaurants and cafes
- Edible manufacturers
- Catering services with cannabis offerings
- Recipe development with precise dosing
- Flavor pairing based on terpene science

## Installation

```bash
pip install cdes-fs
```

## Quick Start

```python
from cdes_fs import (
    CannabisIngredient, Recipe, TerpeneProfile,
    IngredientType, RecipeCategory
)
from decimal import Decimal

# Create a cannabis ingredient with COA reference
butter = CannabisIngredient(
    name="Cannabis-Infused Butter",
    ingredient_type=IngredientType.BUTTER,
    thc_mg_per_gram=Decimal("10.0"),
    coa_reference=CannabisCOAReference(
        coa_id="COA-2026-001",
        batch_number="BATCH-001",
        strain_name="Blue Dream"
    )
)

# Get terpene-based food pairing suggestions
profile = TerpeneProfile(
    coa_reference=butter.coa_reference,
    limonene=Decimal("0.8"),
    myrcene=Decimal("0.5")
)
pairings = profile.suggest_pairings()
# ["citrus desserts", "seafood", "mangoes", "tropical fruits"]

# Create a recipe with automatic dosage calculation
recipe = Recipe(
    name="Cannabis Lemon Bars",
    category=RecipeCategory.DESSERT,
    servings=12,
    cannabis_ingredients=[(butter, Decimal("50.0"))]  # 50g of butter
)
dosage = recipe.calculate_total_dosage()
# 500mg total THC / 12 servings = ~42mg per serving (high_dose_warning=True)
```

## Documentation

- [Full Documentation](https://cdes.dev/docs/food-service)
- [Dosage Calculator](https://cdes.dev/tools/dosage)
- [Terpene Pairing Guide](https://cdes.dev/guides/terpene-pairing)

## License

MIT License - see [LICENSE](LICENSE) for details.
samsara-fn 0.16.1
A CLI tool for Samsara Functions
Requires Python: >=3.12

A CLI tool for Samsara Functions.
Streamlines local development, testing and packaging.

## Installation

It is recommended to use a separate virtual environment.

```bash
python3.12 -m venv venv
source venv/bin/activate
pip install samsara-fn
```

### Shell autocompletion

If you're using bash or zsh, you can opt-in to shell autocompletion.
To enable it, first install the package with an optional dependency set:

```bash
pip install 'samsara-fn[shell-completion]'
```

And enable autocompletions via [`argcomplete`](https://kislyuk.github.io/argcomplete/#installation). You need to either:

1. Run this command every time you need the completion to work.

> Make sure that the virtual Python environment was already sourced before running `eval`.

```bash
eval "$(register-python-argcomplete samsara-fn)"
```

2. Enable global completion for argcomplete-supported Python scripts with a one time installation script:

```bash
activate-global-python-argcomplete
```

## Usage

The simulator provides a command-line interface.
Each command supports various options. Use `--help` with any command to see detailed usage:

```bash
samsara-fn --help
samsara-fn run manual --help
```
cdes-mk 0.1.0
CDES Marketing Extension - Cannabis loyalty, campaigns, and analytics SDK
Requires Python: >=3.10

﻿# CDES-MK: Cannabis Data Exchange Standard - Marketing Extension

Marketing and demand generation SDK for the cannabis industry. Part of the [CDES](https://cdes.dev) ecosystem.

## Features

- **Customer Profiles** - Unified customer data with consent management
- **Loyalty Programs** - Points, tiers, rewards, and redemptions
- **Campaigns** - Email, SMS, push notification campaign management
- **Deals & Promotions** - Discount engine with complex conditions
- **Analytics** - Marketing attribution and performance tracking

## Platform Integrations

| Platform | Status | Description |
|----------|--------|-------------|
| AlpineIQ |  Ready | Largest cannabis loyalty platform |
| Springbig |  Coming | SMS marketing and loyalty |
| Headset |  Ready | Market intelligence and analytics |
| Fyllo |  Coming | Programmatic cannabis advertising |
| Surfside |  Coming | CDP and audience data |

## Installation

```bash
pip install cdes-mk
```

## Quick Start

```python
from cdes_mk import Customer, LoyaltyProgram, Campaign, Deal

# Create a customer
customer = Customer(
    external_id="POS-12345",
    profile=CustomerProfile(
        first_name="Jane",
        email="jane@example.com",
        preferred_terpenes=["limonene", "myrcene"]
    )
)

# Create a deal
deal = Deal(
    name="First Time Patient",
    deal_type=DealType.PERCENTAGE_OFF,
    value=Decimal("20.00"),
    conditions=DealCondition(first_time_only=True)
)
```

## Documentation

- [Full Documentation](https://cdes.dev/docs/marketing)
- [API Reference](https://cdes.dev/api/cdes-mk)
- [Integration Guides](https://cdes.dev/guides/marketing)

## License

MIT License - see [LICENSE](LICENSE) for details.

## Part of CDES

This SDK is part of the Cannabis Data Exchange Standard ecosystem:

- **CDES** (Core) - Strains, batches, terpenes, cannabinoids
- **CDES-M** - Medical/healthcare (FHIR, HL7)
- **CDES-C** - Commerce (GS1, EDI, e-commerce)
- **CDES-MK** - Marketing (this SDK)
- **CDES-FS** - Food Service (recipes, dosing)

Learn more at [cdes.dev](https://cdes.dev)