semvec/pypi-packages huggingface dataset:
python-self-use 0.0.1
A small example package
Requires Python: >=3.6

# python-self-use

#### 介绍

#### 软件架构
软件架构说明


#### 安装教程

1.  pip install stephenithub

#### 使用说明

"""
import stephenithub

ocrtext2df(text, 3)

"""

#### 参与贡献

1.  Fork 本仓库
2.  新建 Feat_xxx 分支
3.  提交代码
4.  新建 Pull Request
mymetal 1.0.9
MeBiPred
Keywords: python,metal binding prediction package

##Metal Binding Predictor, using neural network

#A simple way to test:

from mymetal import mbp

mbp.predict('fasta_file')

This will return a list, first 3 lines are a summary of the hits and the rest are predictions for each protein supplied.

-----------

In case you wish to output a CSV file:

from mymetal import mbp,iof

a = mbp.predict('fasta_file')
iof.save_out_csv(a,'out_filename.csv')
pdp-kafka-reader 0.0.5
PDP Kafka package
Requires Python: >=3.6

# PDP Kafka Reader

## Requirements

* git
* python 3.6+
* pip

Also, you need access to the git repository. Generate and use ssh keys in Skyway Bitbucket.

## Install

```bash
pip install pdp_kafka_reader
```

## Usage

### CLI

You can use `kafka-reader` CLI tool to extract data into from a specific topic. An example of usage:

```bash
kafka-reader export-avro -k kafka-options.json -s schema.json -t my_kafka_topic -o out.parquet
```

Check all options with `kafka-reader -h`.

### Python KafkaReader

```python
import json

from pdp_kafka_reader.kafka_reader import KafkaAvroReader

kafka_options = {
    "kafka.bootstrap.servers": "my-kafka-server:9092",
    "subscribe": "test_avro"
}

avro_schema = open("schema.json").read()

reader = KafkaAvroReader(spark)
df = reader.read_avro(kafka_options, avro_schema, "my_kafka_topic")
df.show()
```

## Testing

Testing environment in defined in `docker-compose.yml`. Start docker containers and run `tox`.