semvec/pypi-packages huggingface dataset:
geturl 0.2.1
A CLI tool to get a public link for any file
License: MIT

## geturl  - provide path. get url.
### A CLI tool to get a public link for any file

Uses [filepicker.io](https://www.filepicker.io) to store the files. It's a cool uploading tool that I've been using on my website and this is a hack on top of it.

#### Use Cases

- You need a quick way to send a file to someone. Instead of attaching it to an email or starting up your FTP server, use this to get a public URL.

- Another tool in your arsenal of `scp`, yousendit, and flash drives for quickly exchanging files.

#### Usage

You provide a path, it returns a URL

    geturl path/to/file

It also tries to use `pbcopy` on a mac, `xsel` or `xclip` on Linux to put the url into your clipboard.

<img src="https://raw.github.com/uams/geturl/master/static/example.png">

#### Installation

    sudo curl https://raw.github.com/uams/geturl/master/geturl -o /usr/local/bin/geturl;
    sudo chmod +x /usr/local/bin/geturl

Enable Clipboard Access (Only necessary on Linux)

    sudo apt-get install xclip

<img src="https://raw.github.com/uams/geturl/master/static/install.png">

#### Notes

It uses Filepicker.io as a storage backend. (They have a 5000 file free limit so it shouldn't be a problem)
binder 0.6
Binder is a lightweight mapping engine for SQL databases.
License: MIT


# Binder - A Python SQL Mapper.

Binder is a lightweight SQL mapper for Python that lets you perform SQL
operations using native Python data types and methods:

    >>> conn.select(Trades, AND(Trades.q.symbol=='RHAT', Trades.q.trans=='BUY'))
    [{'date': datetime.date(2006, 1, 5), 'symbol': u'RHAT', 'trans': u'BUY', 'price'
    : 35.0, 'qty': 100}]

A database row is mapped to a Python dictionary containing native Python data
types.  Binder gives you control of what SQL query is executed, while taking
care of query generation, parameter passing and data conversion.

Currently, Binder supports the SQLite (via Python's built-in sqlite3 module),
PostgreSQL (via psycopg2) and MySQL (via the MySQLdb python module).

See manual.txt for full documentation.


## Installing

Install using pip:

    pip install binder

Install from source:

    python setup.py install


## Quick Tour

Define the schema for a table:

    >>> from binder import *
    >>> Trades = Table("trades",
    ...     DateCol("date"), UnicodeCol("trans", 4), UnicodeCol("symbol", 4),
    ...     IntCol("qty"), FloatCol("price")
    ... )

Creating a new database using SQLite and create the table we defined above:

    >>> conn = SqliteConnection("readme.db3")
    >>> conn.create_table(Trades)

Insert a row using a regular Python dictionary:

    >>> from datetime import date
    >>> row = {
    ...     "date":date(2006, 1, 5), "trans":"BUY", "symbol":"RHAT",
    ...     "qty":100, "price":35
    ... }
    >>> conn.insert(Trades, row)
    >>> conn.commit()

Finally, retrieve the data:

    >>> conn.select(Trades)
    [{'date': datetime.date(2006, 1, 5), 'symbol': u'RHAT', 'trans': u'BUY', 'price'
    : 35.0, 'qty': 100}]