semvec/pypi-packages huggingface dataset:
gclfs 0.1.1
Git LFS for large files that need cloud storage.
License: MIT
Requires Python: >=3.6, <4
Keywords: GIT,LFS,CLOUD,STORAGE,AWS,S3

# Git Cloud Large File Storage

Git LFS for large files that need cloud storage.

## Setup

### AWS S3

1. [Install AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html).
2. Create an [S3 bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/create-bucket-overview.html) and 
[AWS access keys](https://docs.aws.amazon.com/IAM/latest/UserGuide/getting-started.html#gs-get-keys).
3. Put the access keys in `~/.aws/credentials` as described [here](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html). 
Note, the profile used by gclfs is `gclfs`. This can be overridden in `gclfs.config`. See example below.
4. Add bucket name to `gclfs.config`.

Example credentials file:

```ini
# ~/.aws/credentials
[default]
aws_access_key_id=AKIAASSFODNN7EXAMPLE
aws_secret_access_key=wJalrP0dnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

[gclfs]
aws_access_key_id=BTIAIOSFODNN7EXAMPLE
aws_secret_access_key=xyalrXUghdEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
```

Example config file with overridden profile name:
```ini
# gclfs.config
[s3]
bucket=my-awesome-bucket
profile=default
```

## Usage

### Tracking

To track files with a specific extension that will be uploaded to cloud storage, run `gcl track *.<file_extension>`

For example, to track wav files:

`gcl track "*.wav"`

This adds the extension to `.gitattributes`. When pushing to remote repo, this will sync all wav files to S3.

**Important**: To keep the large files from getting committed to the git repo, you still have to add them to 
`.gitignore`.

### Commands

Your normal git commands work here and a remote git repo should be setup as usual 
(with `git init` and `git remote add`, etc.).

## Example

`gcl init` (initialize repo)

`gcl track "*.wav"` (track wav files)

`gcl add .` (add files to commit)

`gcl status` (get repo status)

`gcl commit -m "init commit"` (commit changes)

`gcl remote add origin git@github.com:me/my-awesome-project` (add remote repo)

`gcl push` (push git repo and sync files with cloud)

`gcl fetch` (fetch changes)

`gcl pull` (pull remote changes and sync files with cloud)

## Limitations

Currently, only AWS S3 is supported.

## License

See the [LICENSE](LICENSE.md) file for license rights and limitations (MIT).
dtwinpy 0.0.3.7
First Functional mydt.run
License: MIT

dtwinpy: Digital Twin Library

Library for creating Digital Twins of productions systems and simulations models based on Discrete Even Simulation and Simpy. 

The project is being developed by Pedro Bacelar and Alex Chalissery, both Master studetns at Politecnico di Milano.

Contact us:
pedroluis.bacelar@mail.polimi.it
yapy-fuzz 0.1.1
Python wrapper for junegunn's fuzzyfinder (fzf)
License: MIT

Yapy-Fuzz
=======

![](https://img.shields.io/badge/license-MIT-green.svg?style=flat)
<!-- ![https://pypi.python.org/pypi/pyfuzzy](https://img.shields.io/pypi/dm/pyfuzzy.svg?style=flat) -->

##### Yet another python wrapper for *junegunn*'s  [fzf](https://github.com/junegunn/fzf) ***pronunced yaa-pee fuzz*** with handlers for python lists, sqlite3 and postgres

#### Why create another wrapper lib?
I wanted a quick way to do fuzzy search on any data source from text files to databases and I couldn't find a single tool that has support for various different inputs/sources for fzf.

<!-- ![](https://raw.githubusercontent.com/nk412/pyfuzzy/master/pyfuzzy.gif) -->

Requirements
------------

* Python 3.6+
* [fzf](https://github.com/junegunn/fzf)
* sqlite3
* pandas (for postgres support)

*Note*: fzf and sqlite3 must be installed and available on PATH.

Installation
------------
	pip install yapy-fuzz

Usage
-----
    >>> from yapyfuzz.core import Fuzzy
    >>> fzf = Fuzzy()

If `fzf` is not available on PATH, you can specify a location

    >>> fzf = Fuzzy(exec_path="/path/to/fzf")

Initiate a handler depending on your requirements, for e.g., python lists.

    >>> from yapyfuzz.core import ListHandler
    >>> list_handler = ListHandler()
    >>> list_handler.reader(range(0,10))

    >>> fzf = Fuzzy(list_handler)
    >>> fzf.get_selection(list_handler)

SQLite DB Handler

    >>> from yapyfuzz.core import SQLiteHandler
    >>> name = f"{root_dir}/yapy/fuzzy.db"
    >>> query = "select * from albums"
    >>> db_handler = SQLiteHandler()
    >>> db_handler.reader(name, query)

    >>> fp = Fuzzy(db_handler)
    >>> fp.get_selection()

Postgres DB Handler

    >>> from yapyfuzz.core import PostgresHandler

    >>> db_settings = {
        "user":"postgres",
        "password":"postgres",
        "host":"localhost",
        "port":"5432",
        "dbname":"dellstore",
    }

    >>> pg_handler = PostgresHandler()

    >>> pg_handler.reader(query="select * from categories", **db_settings)
    >>> pg_handler.reader(query="select * from inventory", **db_settings)

    >>> fp = Fuzzy(pg_handler)
    >>> fp.get_selection()

You can pass additional arguments to fzf as a second argument

    >>> fzf.prompt(range(0,10), '--multi --cycle')

Input items are written to a temporary file which is then passed to fzf.
The items are delimited with `\n` by default.

License
-------
MIT

Todo
-------
- [X] Add support for postgres db
- [ ] CLI table explorer tool to navigate db and tables


CHANGES
=======

2023.03.21: Initial release