semvec/pypi-packages huggingface dataset:
oilwell 0.0.3
A small data loader
Requires Python: >=3.6

# oilwell
#### A simple opinionated data loader for ELT flows

This project is early, mostly redundant, and built around my own invented needs. 
You probably should use singer.io, perhaps using Meltano.

This is currently more of an idea/structure than something useful at this time (although I'm using it just fine!)

Oilwell fits a data load that expects (nearly) nothing to be guaranteed during "EL", pushing (nearly) all validation to "T".

In this flow:
 - We pull all (non-excluded) columns. Schemas are not descried by default.
 - We dump all to a partitioned file store as parquet (e.g. S3, GCS, Azure Blob)
 - These files have two columns only: `meta_load_at_utc`, and `data`. 
 - The `data` column is a JSON representation of non-null values from that row.
 - Structuring and testing data is pushed to the "T" step in "ELT".

This solves two problems with external data:
 - Newly added columns don't break any automated flows, but are available for use later 
 - Removed columns are identified during "T", e.g. use `dbt test`

## How to run
Use oilwell to run an oilwell project. 

An oilwell project consits of yaml files that define pipelines. These include:
 - a `project.yml` file in the root directory. This defines things like where data goes. 
 - a `pipelines` directory consisting of pipelines config files. 

See example-project/ for what this might look like.

To run oilwell, use `oilwell run` and the `--pipelines` selector:
    oilwell run --pipelines owid-covid

Omitting the --pipelines parameter will select all pipelines.
TwilioToEmail 0.0.7
A middle man service that acts as a Twilio wrapper
Requires Python: >=3.6

# About the Project
As I was going through Zapier's most popular projects, I came across one that caught my eye. They had an application that could forward a text message to an email address using the Twilio API. Having experience with the Twilio API, I decided I'd make a similar project.

<!-- GETTING STARTED -->
## Getting Started

### Prerequisites
The only external package you need is the requests library. Also, you will need a [Twilio account](https://www.twilio.com/), and an [email](https://support.google.com/accounts/answer/6010255) that allows you to send emails.

### Quick Start
Simply import TwilioToEmail and pass the decoded Twilio body into the SmsMessage class. Then forward the message via the Email class's send_email function. Check out the example below.

```python
from TwilioToEmail import SmsMessage

sms_body = SmsMessage(Twilio.decode('utf-8').split("&"))

email = twilio_mail.Email("from_email","to_email","subject line")
email.send_email(sms_body)
```

### Some Nice Features
TwilioToEmail can also handle media messages as well. Files like images, videos, audio, and others are saved as either MP4 or JPG. If a path location is not given to the SmsMessage class then the default **home/last_four_digits_of_number** directory is used to save media files.


<!-- ROADMAP -->
## Roadmap
- [x] Allow user to parse through SMS body via a dictionary
- [ ] Add all default keys in the dictionary that Twilio API sends
- [ ] Allow user to compress media files
- [ ] Let user save info in CSV
XiangshiFast 1.1.3
相识极速版本
Requires Python: >=3.4

# 相识极速版(XiangshiFast)

#### 相识极速版是相识的加速版本。

## 相识极速版只是相识的阉割 + 极速版，正式版本请到
## https://pypi.org/project/xiangshi/

相识与极速版的比较：
```
功能          | 相识       | 相识极速版
Cossim        | ✅        | ✅
Simhash       | ✅        | ❌
Minhash       | ✅        | ❌
GetTF         | ✅        | ✅
GetIDF        | ✅        | ✅
GetTFIDF      | ✅        | ✅
input2list    | ✅        | ✅
dict2file     | ✅        | ❌
SortDict      | ✅        | ❌
HashString    | ✅        | ❌
Logging       | ✅        | ❌
```

### 下载与安装
```sh
$ pip3 install XiangshiFast
```

### 使用方法
##### 计算文本相似度
```py
import xiangshifast as xsf
xsf.cossim(Input1, Input2):
# 或以下代码可以无缝连接
import xiangshifast as xs
xs.cossim(Input1, Input2):
```
 - 计算文本相似度时自动由TFIDF过滤
 - Input1 - 第一个输入值，可以是文件的地址或是一个列表
 - Input2 - 第二个输入值，可以是文件的地址或是一个列表

### MIT License
Copyright (c) [2020] [Kiwirafe]

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.