semvec/pypi-packages huggingface dataset:
ArseinRubika 7.5.1
library Robot Rubika
License: MIT
Keywords: Arsein,Arseinrubika,ArseinRubika,arsein,bot,Bot,BOT,Robot,ROBOT,robot,self,api,API,Api,rubika,Rubika,RUBIKA,Python,python,aiohttp,asyncio



## ArseinRubika

> Elegant, modern and asynchronous Rubika MTProto API framework in Python for users and bots

<p align="center">
    <img src="https://s6.uupload.ir/files/img_20240111_123815_369_5ni9.jpg" alt="ArseinRubika" width="128">
    <br>
    <b>library Arsein Rubika</b>
    <br>
</p>

###  Arsein library documents soon...


### How to import the Rubik's library

``` bash
from arsein import Messenger

Or

from arsein import Robot_Rubika
```

### How to import the anti-advertising class

``` bash
from arsein.Zedcontent import Antiadvertisement
```

### How to install the library

``` bash
pip install ArseinRubika==7.5.1
```

### My ID in Telegram

``` bash
@Team_Arsein
```
## An example:
``` python
from arsein import Messenger

bot = Messenger("Your Auth Account"," key Account")

gap = "your guid or gap or pv or channel"

bot.sendMessage(gap,"libraryArsein")
```

## And Or:
``` python
from arsein import Robot_Rubika

bot = Robot_Rubika("Your Auth Account"," key Account")

gap = "your guid or gap or pv or channel"

bot.sendMessage(gap,"libraryArsein")
```
Made by Team ArianBot

Address of our team's GitHub :

https://github.com/Arseinlibrary/Arsein__library.git


### Key Features

- **Ready**: Install ArseinRubika with pip and start building your applications right away.
- **Easy**: Makes the Rubika API simple and intuitive, while still allowing advanced usages.
- **Elegant**: Low-level details are abstracted and re-presented in a more convenient way.
- **Fast**: Boosted up by pycryptodome, a high-performance cryptography library written in C.
- **Async**: Fully asynchronous (also usable synchronously if wanted, for convenience).
- **Powerful**: Full access to Rubika's API to execute any official client action and more.


### Our channel in messengers

``` bash
Our channel in Ita

https://eitaa.com/ArseinTeam

Our channel in Soroush Plus

https://splus.ir/ArseinTeam

Our channel in Rubika

https://rubika.ir/Support_libdaryArseinRubika

Our channel in the Gap

https://gap.im/ArseinTeam

Our channel on Telegram

https://t.me/ArseinTeam
```
SPremiRNA 0.1
A simple example package
License: MIT

## Overview of the SPremiRNA workflow  
(1) Perform basic analysis of the spatial transcriptome data from Visium, and in using the bulk sequenced data, pick out the common mRNA genes and miRNA genes between them.  
(2) Build an xgboost model, train it using the bulk sequencing dataset, and then perform migration learning to predict miRNAs from the spatial transcriptome data.  
(3) Use single-cell expression profiles of the same tissue to get the cell type in each spot in the spatial transcriptome data using cell2location.  
(4) Correlation analysis of miRNA and mRNA expression for malignant cell types.  
## Installation

We suggest using a separate conda environment for installing SPremiRNA.

Create conda environment and install?`SPremiRNA`?package

```shell
conda create -y -n SPremiRNA_env python=3.9

conda activate SPremiRNA_env
pip install SPremiRNA
```

Finally, to use this environment in jupyter notebook, add jupyter kernel for this environment:

```shell
conda activate SPremiRNA_env
python -m ipykernel install --user --name=SPremiRNA_env --display-name='Environment (SPremiRNA)'
```
Before installing cell2location and it's dependencies, it could be necessary to make sure that you are creating a fully isolated conda environment by telling python to NOT use user site for installing packages by running this line before creating conda environment and every time before activatin conda environment in a new terminal session:

```shell
export PYTHONNOUSERSITE="literallyanyletters"
```

## Usage and Tutorial
SPremiRNA Steps to run the package:
- spatial_process  
Input：Visium_FFPE_Human_X_Cancer_filtered_feature_bc_matrix.h5  
Output：X_mrna.h5ad，X_ranked_tcga_ccle_mirna.csv，X_ranked_tcga_ccle_mrna.csv，X_st_mrna.csv  
 
- spatial_xgboost   
Input：X_ranked_tcga_ccle_mirna.csv，X_ranked_tcga_ccle_mrna.csv，X_st_mrna.csv  
Output：X_Prest_mirna.csv  
In the model parameters, the depth of the tree is set smaller to help improve the model prediction accuracy.  

- cell2loc   
Input：single cell expression profile X_expression.loom    
Output：X_analysis directory  
 
- malig_mirna   
Input：X_mrna.h5ad，PreXst_mirna.csv，sp.h5ad in X_analysis directory  
Output：X_mirna.h5ad  

- ccle_gct2csv.R（Process CCLE data）    
- tcga_xena2csv.R（Process TCGA data）  
- sc_process.R（Process single cell data）
robin-sd-download 0.4.2
Package to download files to the Robin Radar API
License: MIT
Keywords: python,robin,radar,download,software,sd

# Python package to download via SD API. (robin-sd-download)

A package to download files to the Robin Radar API.

## Installation

Make sure you have Python 3.6 or higher, and pip installed.

Install the package with:

```bash
pip install robin-sd-download
```

## Usage

The package can be used as a command line tool, or as a Python package.

```bash
robin-sd-download --help
```

Use the documentation to find out how to use the package.

## Development

Use the Vagrantfile to create a development environment, and run the tests.

Select the VM you want to use, and run the following commands:

```bash
vagrant up vm1/2/3
vagrant ssh
cd /vagrant
```