semvec/pypi-packages huggingface dataset:
quickvec 0.3.0
QuickVec: Fast and easy loading and querying of word vectors
License: MIT
Requires Python: >=3.6

# QuickVec

[![build](https://github.com/ConstantineLignos/quickvec/actions/workflows/main.yml/badge.svg)](https://github.com/ConstantineLignos/quickvec/actions/workflows/main.yml)

QuickVec is a simple package to make it easy to work with word embeddings.
QuickVec supports instantaneous loading of word embeddings after converting
them to a native SQLite format. QuickVec is designed to do exactly one thing
well: allow you to quickly load word embeddings and look up the vectors for
words.

# Installation

`pip install quickvec` (requires Python 3.6+)

# Design philosophy

QuickVec was created to support [NERPy](https://github.com/ConstantineLignos/nerpy),
a named entity recognition framework that uses word embeddings for feature
generation. NERPy originally used gensim, but the time and memory required to
load a word embedding completely into memory was a large performance
bottleneck. NERPy then turned to Magnitude, but its conversion process is quite
slow, and its installation process caused problems for NERPy users.
The NERPy developers created QuickVec based on the design of Magnitude,
but with the goal of creating a package with minimal features and dependencies.

# FAQ

* _How does QuickVec compare to [gensim](https://pypi.org/project/gensim/)'s
  `KeyedVectors` for loading word embeddings?_
  QuickVec can load word embeddings instantaneously after conversion to its
  native SQLite-based format, and does not load the whole embedding into memory,
  making it more memory efficient. However, QuickVec only supports text-format
  word embeddings files, and in general has far less functionality.
* _How does QuickVec compare to [Magnitude](https://pypi.org/project/pymagnitude/)
  for loading word embeddings?_
  Like Magnitude, QuickVec can instantly load word embeddings after conversion
  to its native SQLite-based format. QuickVec's conversion process is faster
  than Magnitude's. However, QuickVec does not support many of Magnitude's
  features, such as word similarity or generating vectors for out-of-vocabulary
  words, and QuickVec does not provide pre-converted word embeddings and only
  supports loading from text-format embeddings.
dcase-util 0.2.20
A collection of utilities for Detection and Classification of Acoustic Scenes and Events
License: MIT
Keywords: audio sound

DCASE Utilities
===============

A collection of utilities for Detection and Classification of Acoustic
Scenes and Events

|Build Status| |Coverage Status| |PyPI| |License: MIT|

This collection of utilities is for Detection and Classification of
Acoustic Scenes and Events (DCASE). These utilities were originally
created for the DCASE challenge baseline systems
(`2016 <https://github.com/TUT-ARG/DCASE2016-baseline-system-python>`__
& `2017 <https://github.com/TUT-ARG/DCASE2017-baseline-system>`__) and
are bundled into a standalone library to allow their re-usage in other
research projects.

The main goal of the utilities is to streamline the research code, make
it more readable, and easier to maintain. Most of the implemented
utilities are related to audio datasets: handling meta data and various
forms of other structured data, and provide standardized usage API to
audio datasets from various sources.

Documentation
=============

See https://dcase-repo.github.io/dcase_util/ for detailed instruction,
manuals and tutorials.

Installation instructions
=========================

The latest stable release is available on PyPI, and you can install with
pip: ``pip install dcase_util``

License
=======

Code released under the `MIT
license <https://github.com/DCASE-REPO/dcase_util/tree/master/LICENSE>`__.

.. |Build Status| image:: https://travis-ci.org/DCASE-REPO/dcase_util.svg?branch=master
   :target: https://travis-ci.org/DCASE-REPO/dcase_util
.. |Coverage Status| image:: https://coveralls.io/repos/github/DCASE-REPO/dcase_util/badge.svg?branch=master
   :target: https://coveralls.io/github/DCASE-REPO/dcase_util?branch=master
.. |PyPI| image:: https://img.shields.io/pypi/v/dcase_util.svg
   :target: https://pypi.python.org/pypi/dcase_util
.. |License: MIT| image:: https://img.shields.io/badge/license-MIT-blue.svg
   :target: https://opensource.org/licenses/MIT
ast-selector 0.2.0
Query AST elements by using CSS Selector-like syntax
License: MIT
Requires Python: >=3.8,<4.0
Keywords: ast

# AST Selector

<p align="center">
    <img src="https://raw.githubusercontent.com/guilatrova/ast_selector/main/img/logo.png">
</p>

<h2 align="center">Query AST elements by using CSS Selector-like syntax</h2>

<p align="center">
  <a href="https://github.com/guilatrova/ast_selector/actions"><img alt="Actions Status" src="https://github.com/guilatrova/ast_selector/workflows/CI/badge.svg"></a>
  <a href="https://pypi.org/project/ast-selector/"><img alt="PyPI" src="https://img.shields.io/pypi/v/ast_selector"/></a>
  <img src="https://badgen.net/pypi/python/ast_selector" />
  <a href="https://github.com/relekang/python-semantic-release"><img alt="Semantic Release" src="https://img.shields.io/badge/%20%20%F0%9F%93%A6%F0%9F%9A%80-semantic--release-e10079.svg"></a>
  <a href="https://github.com/guilatrova/ast_selector/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/guilatrova/ast_selector"/></a>
  <a href="https://pepy.tech/project/ast-selector/"><img alt="Downloads" src="https://static.pepy.tech/personalized-badge/ast_selector?period=total&units=international_system&left_color=grey&right_color=blue&left_text=%F0%9F%A6%96%20Downloads"/></a>
  <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"/></a>
  <a href="https://github.com/guilatrova/tryceratops"><img alt="try/except style: tryceratops" src="https://img.shields.io/badge/try%2Fexcept%20style-tryceratops%20%F0%9F%A6%96%E2%9C%A8-black" /></a>
  <a href="https://twitter.com/intent/user?screen_name=guilatrova"><img alt="Follow guilatrova" src="https://img.shields.io/twitter/follow/guilatrova?style=social"/></a>
</p>

> "Query AST elements 🌲 by using CSS Selector-like 💅 syntax."

## Installation and usage

### Installation

```
pip install ast-selector
```

### Usage

```py
from ast_selector import AstSelector

tree = load_python_code_as_ast_tree()
query = "FunctionDef Raise $FunctionDef"
# Query all functions that raises at least an exception

functions_raising_exceptions = AstSelector(query, tree).all()
```

### Use Cases

#### Functions that return int

```py
from ast_selector import AstSelector

tree = load_python_code_as_ast_tree()
query = "FunctionDef.returns[id=int] $FunctionDef"
# Query all functions that return ints e.g. def sum() -> int

function_element = AstSelector(query, tree).first()
```

## License

MIT

## Credits

It's extremely hard to keep hacking on open source like that while keeping a full-time job. I thank God from the bottom of my heart for both the inspiration and the energy.
none-aware 0.0.2
Package provided none-aware wrapper for none-safety object manipulation.
License: MIT
Requires Python: >=3.6

# Python none-aware

## Install

```commandline
pip install none-aware
```

## Usage

```python
from none_aware import Maybe
obj = dict(foo='bar', baz=dict(foo='foo', bar='bar'))

maybe_obj = Maybe(obj)

assert maybe_obj['foo']() == 'bar'
assert maybe_obj['bar']() is None
assert maybe_obj['baz']['foo']() == 'foo'
assert maybe_obj['bar']['foo']() is None
assert maybe_obj['foo']['bar']() is None
assert maybe_obj.foo() == 'bar'
assert maybe_obj.bar() is None
assert maybe_obj.baz.foo() == 'foo'
assert maybe_obj.bar.foo() is None
assert maybe_obj.foo.bar() is None
assert maybe_obj.foo.upper() == 'BAR'
assert maybe_obj.foo.upper.lower() == 'bar'
assert maybe_obj.bar.foo.other.upper.lower() is None
assert maybe_obj.bar.foo.other.upper.lower.else_('Nothing') == 'Nothing'

maybe_strict = Maybe(obj, strict=True)
assert maybe_strict['foo'].else_('Other') == 'bar'
assert maybe_strict.foo.else_('Other') == 'Other'

maybe_none = Maybe(None)
print(maybe_none.foo.bar)  # None
print(maybe_none.is_none())  # True
print(maybe_none.bar.baz.is_none())  # True
print(maybe_obj.foo.is_none())  # False
print(maybe_obj.foo.bar.is_none())  # True
```
light-sql3 1.0.1
Light cover for sqlite3
License: MIT
Requires Python: >=3.7,<4.0

# Light db
Light db this is easy cover for database sqlite3
## How to use
```py
from light_sql3 import DataBase

example = DataBase(
    name="light_db"
)

# Method insert (return type bool)
example.insert(id="some_id", value="some_value")


# Method get (return value by id)
print(example.get(id="some_id"))


# Method add (return type bool)
example.add(id="some_id", num=100)


# Method remove (return type bool)
example.remove(id="some_id", num=100)


# Method all (return all values from table)
print(example.all())


# Method update (return type bool)
example.update(id="some_id", value=1000)


# Method has (return type bool)
print(example.has(id="some_id"))


# Method delete (return type bool)
example.delete(id="some_id")

# I think the command names make it clear what exactly they do
```
Painless-SQLAlchemy 1.0.3
Simplified filtering and serialization for SQLAlchemy
License: MIT
Keywords: SQLAlchemy,Serialization,Query,Simple,Abstraction,PostGis,Columns


Painless-SQLAlchemy
----------------
Easy serialization and filtering for SQLAlchemy.

Links:
* [github](https://github.com/GetintheLoop/painless-sqlalchemy)