semvec/pypi-packages huggingface dataset:
houseprices2023xx 0.11.0
Using Machine Learning to predict the SalePrice of properties
Keywords: house-prices machine-learning prediction

The aim of this project is to explore the train dataset by performing preprocessing operations, including data mining techniques like removing irrelevant data and updating missing values. Subsequently, we will apply various machine learning algorithms to the preprocessed dataset. The ultimate goal is to determine the best model for predicting property prices based on their features, including factors like location.
gpyt 0.2.23
GPT on the command line.
Requires Python: >=3.11,<4.0

# gpyt

### GPT in your terminal.


> **Note**
> WIP

<img src="https://img.shields.io/badge/dynamic/json.svg?label=downloads&url=https%3A%2F%2Fpypistats.org%2Fapi%2Fpackages%2Fgpyt%2Frecent&query=data.last_month&colorB=brightgreen&suffix=%2FMonth"/>
<img src="https://img.shields.io/pypi/v/gpyt.svg"/>

---

Try out the new (experimental and buggy) **FREE** model using [GPT4Free](https://github.com/xtekky/gpt4free):

`$ gpyt --free`

^ NO API KEY required

OR Try out PaLM 2 (requires Google MakerSuite API KEY)

`$ gpyt --palm`

If you have access, you can try out GPT4

`$ gpyt --gpt4`

Uses [Textual](https://textual.textualize.io).

## Demo

![gpyt demo](https://github.com/JustinStitt/gpyt/blob/master/media/gpyt-show-1.gif?raw=true)



### Markdown Support

![markdown support](https://github.com/JustinStitt/gpyt/blob/master/media/md-support.png?raw=true)

![markdown support (showing table)](https://github.com/JustinStitt/gpyt/blob/master/media/md-support-2.png?raw=true)


### Installation & Usage
1) `$ pip install gpyt`

2) add `OPENAI_API_KEY="<your_openai_api_key>"` in a `.env` at $HOME or `export OPENAI_API_KEY=<your_key>`

3) `$ gpyt`

Or try this *optional* method for running **gpyt** if you don't have an api key:

4) `$ gpyt --free`

Or try this *optional* method for running **PaLM 2**, Google's premier LLM:

5) `$ gpyt --palm`
     - Be sure to set an api key at `~/.env` with the field `PALM_API_KEY`

Or try out GPT4 w/ gpyt!

6) `$ gpyt --gpt4`

### Keybindings

* `ctrl-b` -> Toggle Dark/Light Mode
* `ctrl-n` -> Open Past Conversations Sidebar
* `ctrl-c` -> Quit
* `ctrl-o` -> Model Selection Menu
* `ctrl-t` -> Open External Editor (for input)
* `ctrl-x` -> hide input box (helpful for small screens)


### TODO

- [ ] add gpt jailbreaks (DAN-esque)
- [ ] add special flags like -t (terse) or -v (verbose) or -d (detailed) or -i
osgood 1.3.0
A small collection of useful functions
Requires Python: >=3.8

# Overview

[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![image](https://img.shields.io/pypi/v/osgood.svg)](https://pypi.org/project/osgood)
[![image](https://img.shields.io/pypi/l/osgood.svg)](https://pypi.org/project/osgood)
[![](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![Downloads](https://static.pepy.tech/badge/osgood/month)](https://pepy.tech/project/osgood)

This is a small package of useful components.

## Docker

This package comes with a `Dockerfile` and `docker-compose` files to allow dockerized development if desired. Simply run `docker compose up -d` to run the containers in the `docker-compose.yml` in detached mode. See which containers are running by using `docker ps`. If you want to open a bash session inside one of the containers run `docker-compose exec <container-name> /bin/bash`. To stop all containers run `docker compose down`.

The build command in the `docker-compose.yml` takes care of building the `Dockerfile`. If you'd like to force a rebuild run `docker-compose up --build`.

To test:
Run `pytest` at the root of the repo.
poetry-creator 0.1.1
The quickest way to get up and running with Python


# Poetry Creator

Poetry Creator is a Python package that makes it super easy to get started with a new Poetry project. It helps you initialize a new project with a basic structure and install some common Python packages that you might need.

## Installation

To install Poetry Creator, simply run:

`pip install poetry-creator` 

## Usage

Once Poetry Creator is installed, you can use it to create a new project like this:

`poetry-creator my_project_name` 

This command will:

1.  Create a new directory called `my_project_name`.
2.  Initialize a new Poetry project in that directory.
3.  Create a `pyproject.toml` file with the required dependencies.
4.  Initialize a basic FastAPI project structure.

The `pyproject.toml` file includes dependencies for a variety of common Python packages, including:

-   FastAPI
-   Uvicorn
-   Gunicorn
-   OpenAI and OpenAI-Async
-   Redis
-   Black
-   Termcolor
-   Python-dotenv
-   Websockets
-   Aiofiles
-   Loguru
-   Webrtcvad

After creating the project, Poetry Creator will automatically install these dependencies and then run your new project using Uvicorn.

Remember to replace `"<your name here> <your email here>"` in the `pyproject.toml` file with your actual name and email.

## Errors

If there's a problem during project creation (for example, if the project directory already exists), Poetry Creator will print an error message and exit.
ipfsclient 0.1.1
IPFS RPC Client
Requires Python: >=3.11

# ipfsclient

IPFS RPC Client

![](https://img.shields.io/readthedocs/ipfsclient?label=readthedocs)
![](https://img.shields.io/github/actions/workflow/status/nanoswap/ipfsclient/test.yml?label=tests)
![](https://img.shields.io/snyk/vulnerabilities/github/nanoswap/ipfsclient)
![](https://img.shields.io/pypi/pyversions/ipfsclient)

- [Installation](#installation)
- [Documentation](#documentation)
  * [Build docs locally](#build-docs-locally)
- [Tests](#tests)
  * [Before running tests:](#before-running-tests-)
    + [Regenerate pb2.py files](#regenerate-pb2py-files)
    + [Ipfs setup](#ipfs-setup)
    + [Run the ipfs daemon](#run-the-ipfs-daemon)
- [IPFS troubleshooting](#ipfs-troubleshooting)

## Installation

```
pip install ipfsclient
```

## Documentation

https://ipfsclient.readthedocs.io/

### Build docs locally
`mkdocs serve`

## Tests
To only run tests: `pytest`  
To run all checks: `nox`

### Before running tests:

#### Regenerate pb2.py files 
```
cd protobuf;
protoc --python_out=../proto --proto_path=protobuf protobuf/sample.proto
```

#### Ipfs setup
https://docs.ipfs.tech/install/  

#### Run the ipfs daemon
```
ipfs daemon --api /ip4/0.0.0.0/tcp/5001
```
Check the status of your node at:
  - http://localhost:5001/webui
  - https://webui.ipfs.io/#/status


## IPFS troubleshooting

Set the log level, send the logs to a file, and search the file for relevant messages
```
export IPFS_LOGGING=<debug|info|error>
ipfs daemon --debug 2>&1 | tee ipfs.log
cat ipfs.log | grep test_directory
```

If you find something important, you can show the first few lines around that message
```
grep -C 10 '2023-04-13T17:31:49.712-0400' ipfs.log
```

Here is an example of an error message in these logs:
```
2023-04-13T17:31:49.712-0400	DEBUG	cmds/http	http/handler.go:90	incoming API request: /files/mkdir?arg=test_directory
2023-04-13T17:31:49.712-0400	DEBUG	cmds	go-ipfs-cmds@v0.8.2/command.go:161	error occured in call, closing with error: paths must start with a leading slash
```