semvec/pypi-packages huggingface dataset:
pycounts-liannahovh 0.1.0
Calculate word ccounts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. 
Please note that this project is released with a Code of Conduct. 
By contributing to this project, you agree to abide by its terms.

## License

`pycounts` was created by Tomas Beuzen. It is licensed under the terms
of the MIT license.

## Credits

`pycounts` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-jlee 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_jlee

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_jlee
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_jlee` was created by John Lee. It is licensed under the terms of the MIT license.

## Credits

`pycounts_jlee` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-s 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_s

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_s
```

## Usage

`pycounts_s` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_s` was created by Qingqing Song. It is licensed under the terms of the MIT license.

## Credits

`pycounts_s` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-khalidca 0.1.0
A simple toy project to demonstrate how to create python packages
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_khalidca

A simple toy project to demonstrate how to create python packages

## Installation

```bash
$ pip install pycounts_khalidca
```

## Usage

`pycounts_khalidca` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_khalidca.pycounts import count_words
from pycounts_khalidca.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_khalidca` was created by Khalid Abdilahi. It is licensed under the terms of the MIT license.

## Credits

`pycounts_khalidca` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-luming 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_luming

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_luming
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_luming.pycounts_luming import count_words
from pycounts_luming.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_luming` was created by Luming Yang. It is licensed under the terms of the MIT license.

## Credits

`pycounts_luming` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-son 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. 
Please note that this project is released with a Code of Conduct. 
By contributing to this project, you agree to abide by its terms.

## License

`pycounts` was created by Tomas Beuzen. It is licensed under the terms
of the MIT license.

## Credits

`pycounts` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycount-thayehas1 0.1.0
A package that counts occurenece of words in a text
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_thayehas1

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_thayehas1
```

## Usage

`pycounts_thayehas1` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_thayehas1.pycounts_thayehas1 import count_words
from pycounts_thayehas1.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. 
Please note that this project is released with a Code of Conduct. 
By contributing to this project, you agree to abide by its terms.

## License

`pycounts_thayehas1` was created by Taiwo Owoseni. It is licensed under the terms
of the MIT license.

## Credits

`pycounts_thayehas1` was created with 
[`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and 
the `py-pkgs-cookiecutter` 
[template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
skifts 0.1.0
Search for the most relevant documents containing words from a query
License: MIT
Requires Python: >=3.6
Keywords: information-retrieval,text-mining,numpy,tf-idf,cosine-similarity

[![Generic badge](https://img.shields.io/badge/Python-3.6+-blue.svg)](#)
[![Generic badge](https://img.shields.io/badge/OS-Linux%20|%20macOS%20|%20Windows-blue.svg)](#)

# [skifts](https://github.com/rtmigo/skifts_py#readme)

Search for the most relevant documents containing words from the query.

```python3
query = ['A', 'B']

documents = [
    ['N', 'A', 'M'],  # matching features: 'A'
    ['C', 'B', 'A'],  # matching features: 'A', 'B'  
    ['X', 'Y']  # no matching features
]
```

The search with return `['C', 'B', 'A']` and `['N', 'A', 'M']` in that
particular order.

It's not necessarily about text. Words are just any `str` instances. Documents
are unordered collections of these `str`. We search for documents considering
frequency, rarity and match accuracy.

## Install

```bash
pip3 install git+https://github.com/rtmigo/skifts_py#egg=skifts
```

## Use for full-text search

Finding documents that contain words from the query.

```python3
from skifts import SkiFts

# three documents, one per row
documents = [
    ["wait", "mister", "postman"],
    ["please", "mister", "postman", "look", "and", "see"],
    ["oh", "yes", "wait", "a", "minute", "mister", "postman"]
]

fts = SkiFts(documents)

# find and print the most relevant documents:
for doc_index in fts.search(['postman', 'wait']):
    print(documents[doc_index])
```

Words inside the `documents` list are considered ready-made feature identifiers.
If your text needs preprocessing or stemming, this should be done separately.

The ranking takes into account the frequency of words in the document and the
rarity of words in the corpus. The word order in the document and the distance
between words do not matter.

## Implementation details

The search uses the [scikit-learn](https://scikit-learn.org) library, which
ranks documents using [tf-idf](https://en.wikipedia.org/wiki/Tf%E2%80%93idf) and
[cosine similarity](https://en.wikipedia.org/wiki/Cosine_similarity).

## See also

The [gifts](https://github.com/rtmigo/gifts_py#readme) package implements the
same search, but in pure Python with no binary dependencies.
pycounts-ms 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_ms

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_ms
```

## Usage


`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_ms.pycounts_ms import count_words
from pycounts_ms.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```


## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_ms` was created by Mahsa Sarafrazi. It is licensed under the terms of the MIT license.

## Credits

`pycounts_ms` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
spatgen 0.1.6
Pattern generating DSL for spaCy
License: MIT
Requires Python: >=3.6

# Spatgen: Pattern generator for spaCy

Spatgen is a concise and readable DSL and parser which produces patterns for [spaCy](https://github.com/explosion/spaCy)
which you can use in the [Matcher](https://spacy.io/api/matcher) class.

We think [Matcher](https://spacy.io/api/matcher) is fantastic but writing patterns can become tedious especially if there are several combinations with the same prefix or suffix and if the rules don't fall into any of the `OP` operations provided. This package simplifies the creation of large lists of patterns.

## Example

Here's an example showing how to match some syntax with optional and either-or patterns (you can combine these too):

```python
from spatgen import parser

patterns = r"""
name = example
anchors = [study survey report research datum article review]

++match++
lemma(anchors) aux? adv? verb adp? <det? noun | date> [adp det? <org | gpe>]
"""

parser.parse_str(str(patterns))
```

This will produce a `Sections` object which contains a list of patterns (suitable for `Matcher`) for each heading found in the input. It also has a `get_meta` method which allows you to retrieve extra information about the pattern such as its line number and the raw source that led to its creation.

## Syntax

### Variables

Names can contain lowercase alphabetic characters and underscores only. Values are interpreted as either strings or
arrays of strings and quotation marks are not required.

### Sections

Sections are demarcated by surrounding an identifier with `++` on either side.

### Patterns

Patterns loosely follow command-line syntax format.

* `[a ...]` means whatever inside is optional. A pattern will be generated for combinations with and without this
  option.
* `<a | b | ...>` means either a or b (or more). Patterns are generated for every combination.
* `action(param)` interprets `action` to be one of spaCy's token operators (`LEMMA`, `LOWER`, etc).
    * If `param` is a string surrounded by quotes then the pattern is compared directly (e.g. `{"LEMMA": "say"}`).
    * If `param` is an identifier and is specified as a variable then the pattern is an `IN` pattern (
      e.g. `{"LEMMA": {"IN": var}}`).
* Other terms are interpreted as either POS tags or entity types. These are matched on context so the spaCy pattern will
  have the correct type.
    * E.g. `verb` will produce `{"POS": "VERB"}` but `org` will produce `{"ENT_TYPE": "ORG"}`.
* Every match supports modifiers and will produce the corresponding `OP` entry:
    * `?` will match zero or one
    * `*` will match zero or more
    * `+` will match one or more
    * `!` will ensure that none match
pycountsvt 0.1.0
calculates word count in a text file
License: MIT
Requires Python: >=3.9,<4.0

# pycountsvt

calculates word count in a text file

## Installation

```bash
$ pip install pycountsvt
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```


## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycountsvt` was created by Vadim Taskaev. It is licensed under the terms of the MIT license.

## Credits

`pycountsvt` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
emmental 0.1.1
A framework for building multi-modal multi-task learning systems.
License: MIT
Requires Python: >=3.6
Keywords: emmental,multi task learning,deep learing

|Emmental|
==========

|CI-CD| |CodeClimate| |Codecov| |ReadTheDocs| |PyPI| |PyPIVersion| |GitHubStars| |License| |CodeStyle|

Emmental is a framework for building multimodal multi-task learning systems.

Note that Emmental is still *actively under development*, so feedback and
contributions are welcome. Submit bugs in the Issues_ section or feel free to
submit your contributions as a pull request.

Getting Started
---------------

Check out our `Getting Started Guide`_ to get up and running with Emmental.

Learning how to use Emmental
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The `Emmental tutorials`_ cover the Emmental workflow, showing how to build
multimodal multi-task learning systems.

Reference
---------

`Emmental: A framework for building multimodal multi-task learning systems`::

    @misc{wu2019emmental,
      title={Emmental: A framework for building multimodal multi-task learning systems},
      author={Wu, Sen},
      year={2019},
    }


.. |Emmental| image:: docs/static/img/emmental-logo.png
   :target: https://github.com/SenWu/emmental
.. |CodeClimate| image:: https://img.shields.io/codeclimate/maintainability/SenWu/emmental.svg
   :alt: Code Climate
   :target: https://codeclimate.com/github/SenWu/emmental
.. |CI-CD| image:: https://img.shields.io/github/workflow/status/SenWu/emmental/ci.svg
    :target: https://github.com/SenWu/emmental/actions
.. |Codecov| image:: https://codecov.io/gh/SenWu/emmental/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/SenWu/emmental
.. |ReadTheDocs| image:: https://img.shields.io/readthedocs/emmental.svg
   :target: https://emmental.readthedocs.io/
.. |PyPI| image:: https://img.shields.io/pypi/v/emmental.svg
   :target: https://pypi.org/project/emmental/
.. |PyPIVersion| image:: https://img.shields.io/pypi/pyversions/emmental.svg
   :target: https://pypi.org/project/emmental/
.. |GitHubStars| image:: https://img.shields.io/github/stars/SenWu/emmental.svg
   :target: https://github.com/SenWu/emmental/stargazers
.. |License| image:: https://img.shields.io/github/license/SenWu/emmental.svg
   :target: https://github.com/SenWu/emmental/blob/master/LICENSE
.. |CodeStyle| image:: https://img.shields.io/badge/code%20style-black-000000.svg
   :target: https://github.com/ambv/black

.. _Getting Started Guide: https://emmental.readthedocs.io/en/latest/user/getting_started.html
.. _Emmental tutorials: https://github.com/SenWu/emmental-tutorials
.. _Issues: https://github.com/SenWu/emmental/issues/
url-into-images 0.1.2
provide image download link through csv file and it will download all the images. also you can chose different extension.
License: MIT

[![Build Status](https://travis-ci.org/sujitmandal/url-into-images.svg?branch=master)](https://travis-ci.org/sujitmandal/url-into-images) [![GitHub license](https://img.shields.io/github/license/sujitmandal/url-into-images)](https://github.com/sujitmandal/url-into-images/blob/master/LICENSE) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/url-into-images) ![PyPI - Wheel](https://img.shields.io/pypi/wheel/url-into-images) ![PyPI](https://img.shields.io/pypi/v/url-into-images)

[![Downloads](https://pepy.tech/badge/url-into-images)](https://pepy.tech/project/url-into-images)

Automatically  Download Multiple Images.

## Package Installation : 
```
pip install url-into-images
```
## Url Into Images :
provide image download link through csv file and it will download all the images. also you can chose different extension.
```
 • jpg

 • jpeg

 • png

 • bmp

 • gif
```
## How to import the module:
```python
URL_PATH = ('') # csv file where image URL contain

IMAGE_PATH = ('') # Download image path
```
## Download JPG
```python
from url_into_images.url_into_images import url_jpg

url_jpg(URL_PATH, IMAGE_PATH)
```
## Download JPEG
```python
from url_into_images.url_into_images import url_jpeg

url_jpeg(URL_PATH, IMAGE_PATH)
```
## Download PNG
```python
from url_into_images.url_into_images import url_png

url_png(URL_PATH, IMAGE_PATH)
```
## Download BMP
```python
from url_into_images.url_into_images import url_bmp

url_bmp(URL_PATH, IMAGE_PATH)
```
## Download GIF
```python
from url_into_images.url_into_images import url_gif

url_gif(URL_PATH, IMAGE_PATH)
```

## Required package’s:
```
• pip install pandas
```
## License:
MIT Licensed

## Author:
Sujit Mandal

[GitHub](https://github.com/sujitmandal)

[PyPi](https://pypi.org/user/sujitmandal/)

[LinkedIn](https://www.linkedin.com/in/sujit-mandal-91215013a/)
pprofiler 0.1.2
Python Decorator for Profiling Function or Method
License: MIT
Requires Python: >=3.8,<4.0

# pprofiler

Simple Python Decorator to Profiling Function or Method

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install pprofiler.

```bash
pip install pprofiler
```

## Usage


```
Python 3.8.10 (default, Jun 23 2021, 11:56:21)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.24.1 -- An enhanced Interactive Python. Type '?' for help.

In [1]: from pprofiler import pprof

In [2]: @pprof(sort_by=["cumulative", "ncalls"])
   ...: def test():
   ...:     arr = []
   ...:     for i in range(0, 100_000):
   ...:         arr.append(i)
   ...:

In [3]: test()
         100002 function calls in 0.018 seconds

   Ordered by: cumulative time, call count

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.012    0.012    0.018    0.018 <ipython-input-4-87325251511f>:1(test)
   100000    0.005    0.000    0.005    0.000 {method 'append' of 'list' objects}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
```


# pprofiler 0.1.2 Release Notes
## January 12, 2022

## Changelog

* Add `line_to_print` parameter - to reduce output for large profiler output
* Add `strip_dirs` parameter - to reduce output for large profiler output
* `sort_by` parameter now accept `tuple` or `list`


## License
[MIT](https://choosealicense.com/licenses/mit/)
pycounts-jacqann 0.2.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_jacqann

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_jacqann
```

## Usage

`pycounts_jacqann` can be used to count words in a text file and plot the results as follows:

```bash
from pycounts_jacqann.pycounts import count_words
from pycounts_jacqann.plotting import plot_words
import mathplotlib.pyplot as plt

file_path = "test.txt"
counts = count_words(file_path)
fig = plot_words(counts, n=10_
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_jacqann` was created by Jacqueline Chong. It is licensed under the terms of the MIT license.

## Credits

`pycounts_jacqann` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts-wangtw 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9,<4.0

# pycounts_wangtw

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_wangtw
```

## Usage

`pycounts_wangtw` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_wangtw.pycounts_wangtw import count_words
from pycounts_wangtw.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_wangtw` was created by Tianwei Wang. It is licensed under the terms of the MIT license.

## Credits

`pycounts_wangtw` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).