semvec/pypi-packages huggingface dataset:
py-xline 0.1.0
py-xline is an official xline client sdk, written in Python.
Requires Python: >=3.7

# py-xline

[![Apache 2.0 licensed][apache-badge]][apache-url]
[![codecov][cov-badge]][cov-url]

[apache-badge]: https://img.shields.io/badge/license-Apache--2.0-brightgreen
[apache-url]: https://github.com/datenlord/Xline/blob/master/LICENSE
[cov-badge]: https://codecov.io/gh/xline-kv/xline/branch/master/graph/badge.svg
[cov-url]: https://codecov.io/gh/xline-kv/go-xline

py-xline is an official xline client sdk, written in Python.

## Features

`py-xline` runs the CURP protocol on the client side for maximal performance.

## Supported APIs

- KV
  - [x] Put
  - [x] Range
  - [x] Delete
  - [x] Txn
  - [x] Compact
- Auth
  - [x] AuthEnable
  - [x] AuthDisable
  - [x] AuthStatus
  - [x] Authenticate
  - [x] UserAdd
  - [x] UserAddWithOptions
  - [x] UserGet
  - [x] UserList
  - [x] UserDelete
  - [x] UserChangePassword
  - [x] UserGrantRole
  - [x] UserRevokeRole
  - [x] RoleAdd
  - [x] RoleGet
  - [x] RoleList
  - [x] RoleGrantPermission
  - [x] RoleRevokePermission
- Lease
  - [x] Grant
  - [x] Revoke
  - [x] KeepAlive
  - [x] KeepAliveOnce
  - [x] TimeToLive
  - [x] Leases
- Watch
  - [x] Watch
- Lock
  - [x] Lock
  - [x] Unlock
- Cluster
  - [ ] MemberAdd
  - [ ] MemberAddAsLearner
  - [ ] MemberRemove
  - [ ] MemberUpdate
  - [ ] MemberList
  - [ ] MemberPromote
- Maintenance
  - [ ] Alarm
  - [ ] Status
  - [ ] Defragment
  - [ ] Hash
  - [x] Snapshot
  - [ ] MoveLeader

## Installation

``` bash
pip install py-xline
```

## Quickstart

``` python
from py_xline import client

async def main():
  curp_members = ["172.20.0.3:2379", "172.20.0.4:2379", "172.20.0.5:2379"]
  cli = await client.Client.connect(curp_members)
  kv_client = cli.kv_client

  await kv_client.put(b"key", b"value")

  res = await kv_client.range(b"key")

  kv = res.kvs[0]
  print(kv.key.decode(), kv.value.decode())
```

## Compatibility

We aim to maintain compatibility with each corresponding Xline version, and update this library with each new Xline release.

| py-xline | Xline |
| --- | --- |
| v0.1.0 | v0.6.1 |
enviRobot-scoop 1.0.9
enviRobot service that can be held by Scoop.
Requires Python: >=3.9

# eco_ask

.env檔請填入以下資訊, 並放置於你終端機的工作目錄
```
LINE_CHANNEL_TOKEN=
LINE_CHANNEL_SECRET=
OPENAI_KEY=
GOOGLE_API_KEY=Geocoding API key
IMGUR_ID=
#DEVICE_MAP_CSV_PATH=有device_id,lat,lon對應的csv位置 如果需要使用get_rawdata mode=10min的話
```
使用pip安裝
```
pip install enviRobot-scoop
```
使用scoop-handler
```
from enviRobot_scoop import enviRobot_scoop
enviRobot_scoop.handle_enviRobot(dic_params, question, websocket)
```

requirements 裡面要根據不同作業系統設定 kaleido 套件的版號
kaleido==0.2.1 <-- linux
kaleido==0.1.0post1 <-- windows
baler-compressor 0.0.6
Machine Learning Based Data Compression
Requires Python: >=3.8

[![DOI](https://zenodo.org/badge/576188110.svg)](https://zenodo.org/badge/latestdoi/576188110)\
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\
![example workflow](https://github.com/baler-compressor/baler/actions/workflows/test_and_lint.yaml/badge.svg)
![example workflow](https://github.com/baler-compressor/baler/actions/workflows/docker.yaml/badge.svg)

# Introduction
Baler is a tool used to test the feasibility of compressing different types of scientific data using machine learning-based autoencoders. Baler provides you with an easy way to:
1. Train a machine learning model on your data
2. Compress your data with that model, and save the model
3. Decompress the file using the model at a later time


# Getting Started #
Baler now exists as a *pip package* which you can install through:
```console
pip install baler-compressor
```

For examples on how to use Baler we recommend following the tutorial from our baler-demo repository: https://github.com/baler-collaboration/baler-demo


# Contributing
If you wish to contribute, please see the [contribution guidelines](https://github.com/baler-collaboration/baler/blob/main/docs/CONTRIBUTING.md).