semvec/pypi-packages huggingface dataset:
pycountry-wrapper 1.0.1
This is a wrapper for pycountry, to make said library more usable.
Requires Python: >=3.8

# Pycountry-Wrapper

![publishing workflow](https://github.com/hazel-noack/pycountry-wrapper/actions/workflows/python-publish.yml/badge.svg)

This is a wrapper for pycountry, to make said library more usable.

## Installation

You can install the library by using pip:

```bash
pip install pycountry-wrapper
```

## Usage

```python
from pycountry_wrapper import Country

germany = Country.from_alpha_2("DE")
print(germany)
print(germany.name)

try:
    does_not_exist = Country.from_alpha_2("EN")
except ValueError:
    # if the country wasn't found, a ValueError is raised
    pass
```

### Creating country class

You can call create an instance of `Country` in multiple slightly different ways.

The [**ISO 3166-1**](https://en.wikipedia.org/wiki/ISO_3166-1) standart can either use 2 or 3 letters (alpha_2 or alpha_3).

```python
from pycountry_wrapper import Country

# auto detects if alpha_2 or alpha_3
Country("DE")
Country("DEU")

# you can specify what to use, if required.
Country.from_alpha_2("DE")
Country.from_alpha_3("DEU")
```

If the country can't be found it will raise a `EmptyCountryException` or use the fallback defined in `config.fallback_country`.

Alternatively you can get an instance of `Country` by using `Country.search`. This will return `None` if no country was found.

I also implemented a null-object pattern of `Country`, meaning you can get an `EmptyCountry` object. If you create a country from this object you'll get an instance of `Country` if it was found, and an instance of `EmptyCountry` if it wasn't.

```python
empty = EmptyCountry("InvalidCountry")
print(type(empty))  # <class 'pycountry_wrapper.country.EmptyCountry'>

found = EmptyCountry("US")
print(type(found))  # <class 'pycountry_wrapper.country.Country'>
```

### Accessing information

There are only a handful (readonly) attributes.

```python
from pycountry_wrapper import Country

country = Country("DE")

country.name
country.alpha_2
country.alpha_3
country.official_name
```

If you have an `EmptyCountry` these attributes will all be `None`.

### Configuring behavior

If you want to set a fallback country or disable fuzzy search you can do that with the config module.

```python
from pycountry_wrapper import config

config.fallback_country = "US"
config.allow_fuzzy_search = False
```
STCastl 0.1.1
A Consensus Framework for Robust Identification of Spatially Variable Genes in Spatial Transcriptomics
Requires Python: >=3.8
Keywords: consensus, spatially variable genes, spatial transcriptomics

# Castl: A Consensus Framework for Robust Identification of Spatially Variable Genes in Spatial Transcriptomics

## 1 Overview
`Castl` is a novel consensus-based analytical framework designed to enhance the accuracy and robustness of spatially variable genes identification for spatially resolved transcriptomics through statistically rigorous algorithms, including **rank aggregation**, **p-value aggregation**, and **Stabl aggregation**. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems. 

![figure](./docs/figures/Figure1_workflow.png)

## 2 System Requirements
### Python
- Python >= 3.9.5
- pandas >= 1.3.0
- numpy >= 1.21.0
- rpy2 >= 3.5.0
- scipy >= 1.7.0
- statsmodels >= 0.13.0
- anndata >= 0.8.0
- scanpy >= 1.9.0
- matplotlib >= 3.5.0
- seaborn >= 0.12.0
- scikit-learn >= 1.0.0

### R
- R >= 4.0.5
- dplyr >= 1.0.0
- tidyverse >= 1.3.0
- clusterProfiler >= 3.18.0
- org.Hs.eg.db >= 3.12.0
- patchwork >= 1.1.0
- ggplot2 >= 3.3.0
- TissueEnrich >= 1.8.0
- SummarizedExperiment >= 1.20.0

## 3 Installation

### Python
`Castl` can be installed directly from PyPI：
```bash
pip install STCastl
```

or download from Github and install it:
```bash
git clone https://github.com/TheY11/Castl

cd Castl
pip install -e .
```

### R
We also provide the R package `castlRUtils` for calculating quality scores (QS) of SVGs.
```{r}
library(devtools)
devtools::install_github("TheY11/Castl", subdir = "Castl/r_utils", force = TRUE)
library(castlRUtils)
```

## 4 Tutorials
Detailed usage instructions and tutorials for `Castl` are available at: <https://castl-analysis.readthedocs.io/en/latest/>

## 5 Improvements
For questions or issues, please [open an issue](https://github.com/TheY11/Castl/issues).