semvec/pypi-packages huggingface dataset:
splunkhecwriter 0.4
Library for sending events to Splunk HEC
License: MIT
Requires Python: >=3.6
Keywords: splunk,hec

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# splunkhecwriter
Library for sending log events to Splunk

## Example Code block 1
```python

  from splunkhecwriter import SplunkHECWriter
  hec_token = '<HEC-TOKEN-HERE>'
  splunk_server = '127.0.0.1'

  hec_writer = SplunkHECWriter(splunk_host=splunk_server, splunk_hec_token=hec_token)

  msg =  { 'foo': 'bar' }
  hec_writer.send_msg(msg=msg)

```

## Example Code block 2
```python

  from splunkhecwriter import SplunkHECWriter
  hec_token = '<HEC-TOKEN-HERE>'
  splunk_server = '127.0.0.1'

  hec_writer = SplunkHECWriter(splunk_host=splunk_server, splunk_hec_token=hec_token)

  msgs = []
  msgs.append({ 'foo': 'bar' })
  msgs.append({ 'bar': 'foo'})
  hec_writer.send_msgs(msgs=msgs)

```

## Example Code block 3
```python

  from splunkhecwriter import SplunkHECWriter
  hec_token = '<HEC-TOKEN-HERE>'
  splunk_server = '127.0.0.1'
  sourcetype= 'foobar:json'
  source = 'hec'
  host = 'foobar'

  hec_writer = SplunkHECWriter(
    splunk_host=splunk_server,
    splunk_hec_token=hec_token,
    sourcetype=sourcetype,
    source=source,
    host=host)

  msg =  { 'foo': 'bar' }
  hec_writer.send_msg(msg=msg)

```

## License

This project is licensed under the Apache License - see the [LICENSE.md](LICENSE.md) file for details

## Disclaimer
This custom component is neither affiliated with nor endorsed by Splunk.
rctmodelpool 0.1.9
Hub for rct models
License: MIT
Keywords: artificial intelligence,deep learning,attention free transformer,self-attention,transformer,natural language processing

# rct-modelpool

## Installation
You can git install `rctmodelpool` via `pip`:

```bash
pip install git+https://github.com/rct-ai/rct-modelpool
```
or
```bash
pip install rctmodelpool
```

## Usage
You can import the *rctmodelpool.modelpool* from the package like so:

### `sync_model`
```python
from rctmodelpool import modelpool

path = modelpool.sync_model("rcthub://CPM.csv")
print(path)

```

### sync tgz
```python
import os
import tarfile
from rctmodelpool import modelpool
from pathlib import Path

local_path = modelpool.sync_model("rcthub://"+config.bert_model_path)
parent_path = Path(local_path).parent
print("rcthub sync:",local_path)
modeltar = tarfile.open(local_path)
inside_folder = os.path.commonprefix(modeltar.getnames())
real_model_path = os.path.join(parent_path, inside_folder)
print('model folder:', real_model_path)
if not os.path.exists(real_model_path):
    modeltar.extractall(parent_path)
    print('tar extraction:', parent_path, local_path)

```