semvec/pypi-packages huggingface dataset:
code-qa 0.3.1
CodeQA: Unleash the power of AI in your codebase. Ask questions & get insights from your document.
Requires Python: >=3.8.1,<4.0

# CodeQA

**CodeQA** is a **powerful command-line tool** designed to help **developers understand and navigate their codebase**
more efficiently. **By asking questions** directly about your project, you can **gain insights and deepen your
understanding of the codebase** without the need for extensive manual exploration. CodeQA is built on top of LangChain,
leveraging its capabilities to provide accurate and insightful responses.

**Besides code,** CodeQA is engineered to be **universally applicable across various text documents**. It enables you to
effortlessly navigate through:

- PDF documents
- Markdown files
- And any other form of text-based documents.

## Getting Started

Follow these steps to install and set up CodeQA:

1. **Install CodeQA**: Use pip to install CodeQA. Run the following command in your terminal:

    ```bash
    pip install code-qa
    ```

2. **Set up OpenAI Token**: CodeQA uses OpenAI's API to generate responses. You need to add your OpenAI token to your
   virtual environment. Replace `YOUR_TOKEN` with your actual OpenAI token:

    ```bash
    export OPENAI_TOKEN=YOUR_TOKEN
    ```

3. **Navigate to your project folder**: Use the `cd` command to navigate to your project's directory:

    ```bash
    cd PATH/TO/MY/PROJECT
    ```

4. **Initialize CodeQA Index**: This will generate a `.code_qa` folder within your project. The folder contains your
   project embeddings stored as parquet files. Run the following command:

    ```bash
    code_qa init
    ```

## Usage

With CodeQA, you can ask questions directly about your code. For example, if you want to know how to test a particular
part of your code, you can ask:

```bash
code_qa query "How can I test this?"
```

## Ignoring Files

If there are certain files or directories that you want CodeQA to ignore, you can specify them in a `.codeqaignore`
file. This file follows the same syntax and rules as the `.gitignore` file. Simply create a `.codeqaignore` file in your
project's root directory and list the files or directories you want to ignore.

## License

CodeQA is licensed under the Apache License Version 2.0. For more details, see the [LICENSE](LICENSE) file.
meddlr-viz 0.0.2
Interfaces for the Meddlr library built with Meerkat.
Requires Python: >=3.6

# MeddlrViz
MeddlrViz is a visualization suite for medical imaging datasets, machine learning models, and algorithms built with [Meddlr](https://github.com/ad12/meddlr) and [Meerkat](https://github.com/HazyResearch/meerkat).


## ⚡ QuickStart
We recommend downloading MeddlrViz in a virtual environment, 
```bash
# Install Meddlr with basic dependencies
# This will also install meddlr and meerkat-ml
pip install meddlr-viz
```

## Why MeddlrViz?
MeddlrViz offers interfaces for visualizing and interacting with data, machine learning models, and algorithm outputs. These interfaces are built with [Meerkat](https://github.com/HazyResearch/meerkat), an open-source Python library, designed to help technical teams interactively wrangle images, videos, text documents and more with foundation models.

**(1) Complex medical dataset visualization.** Medical images and associated data and model outputs (e.g. segmentations, raw data, etc.) are high-dimensional and difficult to visualize. MeddlrViz provides useful tools for visualizing, formatting, and interacting with complex data types in your medical imaging dataset.

<div align="center">

<image src="static/brats.gif" height=400 alt="A gallery of images from the BRATS dataset" />
</div>

**(2) Interactive demos in native Python.** Building interactive demos can be challenging. MeddlrViz provides built-in interfaces for easily demoing models and algorithms on your data and conducting high-level analyses, like reader studies.

<div align="center">

<image src="static/vortex.gif" height=400 alt="MRI reconstruction under noise and motion perturbation" />
</div>


## ✉️ About
Please reach out to `arjundd [at] stanford [dot] edu` if you would like to use MeddlrViz for a project, at your company or if you have any questions.
awscli-plugin-granica 2.0.6
Granica plugin for AWS CLI
Requires Python: >=3

# awscli-plugin-granica

This AWS CLI plugin provides an authentication and authorization solution for accessing Granica securely using the AWS CLI.

It uses the standard AWS CLI configuration to store the URL for accessing Granica. Active profiles disable regular S3 request signing, and instead provide a presigned STS `GetCallerIdentity` API call to securely authenticate requests using Granica.

## Prerequisites

The minimum supported version of Python is version 3.

`awscli` must be installed. e.g. `pip3 install awscli --user`

## Installation

To install the plugin package, run: `python3 -m pip install awscli-plugin-granica --user`.

## Configuration

To configure the plugin after it has been installed, use `aws configure`:

```bash
aws configure set plugins.granica awscli-plugin-granica
aws [--profile PROFILE] configure set granica_custom_domain <Granica custom domain>
aws [--profile PROFILE] configure set region <Region>
```

For example, to activate a Granica service using an internal load balancer hosted at `https://quicksilver.us-east-1.mydomain.mycompany.com` for the `staging` AWS profile, run:
```bash
aws --profile staging configure set granica_custom_domain mydomain.mycompany.com
aws --profile staging configure set region us-east-1
```

## AWS CLI v2

This plugin has been tested for compatibility with [AWS CLI version 2](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html), but please take note of the [[plugins] configuration breaking changes](https://docs.aws.amazon.com/cli/latest/userguide/cliv2-migration.html#cliv2-migration-profile-plugins). In particular, you will need to add a block like:

```
[plugins]
cli_legacy_plugin_path = /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages
```

in your `~/.aws/config` file for the plugin registration to succeed.

To find the correct location for `cli_legacy_plugin_path` after installing the plugin, run:

```bash
pip3 show awscli-plugin-granica | grep Location:
```
treecker 1.3.0
Package to check the integrity of a directory.
Requires Python: >=3.9

# Treecker

> What does it mean?

The name "Treecker" comes from the contraction of "tree" and "tracker".

> What is it for?

Treecker is a Python package to control the integrity of a directory.

> Is it hard to use?

Just type one of the available commands in a terminal.

## Background

Have you ever wondered if you had accidentally destroyed or altered a part of the data contained in your favorite directory without realizing it?
Do you want to be able to stamp a part of your data and to control at any time that they are still in the state where you had left them?
Do you think that one of your files has been corrupted, but you don't know which one?
If so, this package is for you.

## Features

This Python package is for inspecting and tracking the organization of files in a directory.
A snapshot of the tree structure is saved in a file placed at the root of the tracked directory.
At any time it is possible to compare the current state of the directory with the latest snapshot, and to save the new state.
The program can also check that the file and folder names match a regular expression.
This allows to detect errors in the naming of files.
These features are accessible via the following commands:

* `init`: To create the first snapshot of a directory.
* `status`: To display the changes since last snapshot.
* `commit`: To save the change in a new snapshot.
* `issues`: To display misnamed or unreadable files.

## Installation

You can find how to install the package in the [installation section](https://dustils.gitlab.io/treecker/practice/installation/index.html) of the documentation.

## Usage

You can find how to use the package in the [examples section](https://dustils.gitlab.io/treecker/practice/examples/index.html) of the documentation.

## Credits

* Dunstan Becht

## License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.
paradigm-data-portal 0.2.2
pdp downloads and manages datasets from the Paradigm Data Portal
Requires Python: >=3.7


# Paradigm Data Portal

The Paradigm Data Portal is a collection of open source crypto datasets for researchers and tool builders

## Datasets
- [`ethereum_contracts`](https://github.com/paradigmxyz/paradigm-data-portal/tree/main/datasets/ethereum_contracts): all historical contract deployments
- [`ethereum_native_transfers`](https://github.com/paradigmxyz/paradigm-data-portal/tree/main/datasets/ethereum_native_transfers): all native transfers in similar format to ERC20 Transfers (excluding tx fees)
- [`ethereum_slots`](https://github.com/paradigmxyz/paradigm-data-portal/tree/main/datasets/ethereum_slots): all slots of each contract, including historical usage metadata

All datasets are released under a [CC0](https://creativecommons.org/share-your-work/public-domain/cc0/) license into the public domain unless otherwise noted.

## `pdp`

`pdp` is a CLI tool that can be used to obtain and manage PDP datasets

To install: `pip install paradigm-data-portal`


#### Example Usage

- List available datasets `pdp ls`
- List dataset files `pdp ls <dataset_name>`
- Download a dataset `pdp download <dataset_name>`

Each command has multiple options, view help with `pdp <command> -h`


## Dataset Versioning

Every dataset has a version in `<major>.<minor>.<patch>` format, e.g. `1.2.8`
- when a schema is updated, the major version is increased
- when rows are added, removed, or modified, the minor version is increased
- when rows are added due to new blocks, the patch is increased

Updates will be documented in dataset changelogs