semvec/pypi-packages huggingface dataset:
automl-helpers 0.0.2
A small package to help with modeling pipelines
Requires Python: >=3.6

# automl-helpers
automl-helpers is a Python module for machine learning built on top of scikit-learn, numpy, pandas, and tf/keras designed to train various modeling pipelines to see what algorithms and pre-processing approaches work well for a given data set. The pipelines can either be saved for prediction purposes or just used as baselines for further refinement. 

### User installation
If you already have a working installation of scikit-learn, numpy and tf/keras, the easiest way to install automl-helpers is using pip:

pip install automl-helpers
spearhead 2.0.0
Simple socket-based communication
Requires Python: >=3.6,<4

# Description
Spearhead is a simple protocol for inter-process communication. It is not designed to be secure, and it should only be used locally behind a firewall.

# Server Example
```python
import spearhead

async def echo(cmd:str):
    return cmd

spearhead.run(echo, '127.0.0.1', 1234)
```

# Server Example with SplitRouter
```python
import spearhead

app = spearhead.SplitRouter()

@app.route
async def foo(args):
    return 'bar'

@app.route
async def bar(args):
    return 'foo'

@app.route
async def oops(args):
    raise Exception("Oops")

spearhead.run(app, '127.0.0.1', 1234)
```
pptx-template-python 0.0.1
Uses pptx templates and a context dictionary file to replace keywords
Requires Python: >=3.9
Keywords: powerpoint,pptx,template

# PowerPoint Template Engine

Use PowerPoint templates to generate PowerPoint files on the fly using "magic words". Magic words are specified by using the `$` sign symbol. This keyword becomes a special reserved symbol. If this is not suitable, it can be changed within the script. You can specify magic words in PowerPoint templates by wrapping the word like `$this$`. The tool expects a config file which contains the input pptx template file with magic words and an output pptx file.

To prepare to run the script, download or clone the repo to your local machine. Then use the command line to install the requirements in your desired Python environment using pip: `pip install -r /path/to/requirements.txt`

The script can be run from the command line entering: `main.py --config "path\\to\\config\\file.json"`
drf-manipulation 0.1.5
Tools to quickly add manipulation log fields to your Django project

# DRF Manipulation

It's really common to have fields like "inserted_at", "updated_at",
"created_at", "last_modification", "last_update", etc in tables. To avoid
repeatedly copy-past these fields, I made this package.

# Installation

```shell
pip install drf-manipulation
```

Or, if you want the latest version, you can directly install the package from
the source code:

```shell
pip install https://github.com/xanigo/drf-manipulation/archive/refs/heads/master.zip
```

Or using git:

```shell
pip install git+ssh://git@github.com/xanigo/drf-manipulation.git
```