semvec/pypi-packages huggingface dataset:
EveryQuery 0.1.0
A framework for training and evaluating foundation models, using the MEDS ecosystem for data processing and PyTorch Lightning for training.
Requires Python: >=3.12

# EveryQuery

.env

```
PROJECT_DIR="/home/pac4279/EveryQuery"
DATA_DIR="/n/data1/hms/dbmi/zaklab/payal/mimic"
SAVE_DIR="/n/data1/hms/dbmi/zaklab/payal/EveryQuery/results"
RAW="${DATA_DIR}/raw"
INTERMEDIATE="${DATA_DIR}/intermediate"
PROCESSED="${DATA_DIR}/processed"
```

run for processing data

```
MEICAR_process_data input_dir="$RAW" intermediate_dir="$INTERMEDIATE" output_dir="$PROCESSED"
```

run for training

```
source .env; set -a; . ./.env; set +a; python source/train.py
```
ruru 0.3.6
A collection of Python utilities ported from the R ecosystem.
Requires Python: >=3.10

<h1 align="center">
  <img width="237" height="92" alt="ruru" src="https://github.com/user-attachments/assets/499805bd-23f5-4868-9ec6-c2f1ba151203"><br>
</h1>

# ruru

[![PyPI Version](https://img.shields.io/pypi/v/ruru.svg)](<https://pypi.python.org/pypi/ruru>)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![usethis](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/usethis-python/usethis-python/main/assets/badge/v1.json)](https://github.com/usethis-python/usethis-python)

A collection of Python utilities ported from the R ecosystem.

## Features

### `base` module

The `ruru.base` module provides core utilities:

- `match_arg`: A Python equivalent of R's [`match.arg`](https://stat.ethz.ch/R-manual/R-devel/library/base/html/match.arg.html) function for verifying function arguments against a set of valid options. Recommended usage:

```python
from ruru.base import match_arg

user_choice = "apple"
available_choices = ["Apple", "Banana", "Cherry"]

# Normalize user input before passing it to match_arg.
# Which transformation to use depends on the style of available_choices:
#   - .title() if choices look like "Apple"
#   - .upper() if choices look like "APPLE"
#   - .lower() if choices look like "apple"

user_choice = match_arg(user_choice.title(), available_choices)
```

- `pmatch`: A Python equivalent of R's [`pmatch`](https://stat.ethz.ch/R-manual/R-devel/library/base/html/pmatch.html) function for finding partial substring matches against a set of reference strings.



Inspired by the R [`base`](https://stat.ethz.ch/R-manual/R-devel/library/base/html/00Index.html) package.

### `config` module

The `ruru.config` module gives an easy way to manage of configuration settings in Python applications via YAML files.

Recommended usage:

```python
from importlib.resources import files
from ruru import config

config_path = files("<mypkg>.cli").joinpath("config.yml") 
config_dict = config.get(file = config_path)
```

Inspired by the R [`config`](https://rstudio.github.io/config/index.html) package.

### `cli` module

The `ruru.cli` module provides utilities for enhanced command-line interface output, including colored text, formatted headings, alert messages, and bullet-point lists.

Recommended usage:

```python
from ruru import cli
cli.h1("Heading")
cli.alert("This is an alert message")
```

Inspired by the R [`cli`](https://cli.r-lib.org/reference/index.html) package.
solax-py-library 1.0.0.84
some common tool
Requires Python: <4.0,>=3.8

### solax common module

#### install

```shell
pip install solax_py_library
```

#### struction

module:
- api: provide the api
- core: core code
- errors: define errors
- test: unit tests
- types: modle define

#### module

This package provide some general modules to help us can focus on the real project coding.It`s our own package,we can add more and more general modules.

- upload: The module define the upload tool.It support the way by Ftp.


#### quick start

```python
await upload(
    upload_type=UploadType.FTP,
    configuration=ftp_config,
    upload_data=UploadData(
        upload_type=UploadType.FTP,
        data=dict(
            file_type=FTPFileType.CSV,
            file_name="new_file.csv",
            data=[
                {
                    "EMS1000序列号": "XMG11A011L",
                    "EMS1000本地时间": "2025-02-11 15:39:10",
                    "EMS1000版本号": "V007.11.1",
                    "电站所在国家和地区": None,
                    "电站所在当前时区": None,
                    "电站系统类型": None,
                }
            ],
        ),
    ),
)
```