semvec/pypi-packages huggingface dataset:
BasicCalculatorBySAK 0.0.1
A very basic calculator.
License: MIT
Keywords: calculator

Simple Calculator to perfrom four tasks. 
1. Add two numbers
2. Substract two numbers
3. Multiply two numbers
4. Devision of two numbers

Change Log
++++++++++++++++++++++++++++++++++++++++++++


0.0.1 (04/06/2021) [DD/MM/YYYY]
--------------------------------------------
- First Release
prsaw 0.4.0
PRSAW, an acronym for `Python Random Stuff API Wrapper`, is a wrapper for the Random Stuff API.
License: MIT
Keywords: random stuff,api,wrapper

# PRSAW 0.4.0
[![Downloads](https://static.pepy.tech/personalized-badge/prsaw?period=total&units=international_system&left_color=green&right_color=orange&left_text=Downloads)](https://pepy.tech/project/prsaw)

PRSAW, an acronym for `Python Random Stuff API Wrapper`, is a wrapper for the [Random Stuff API](https://api.pgamerx.com/).
PyPI: https://pypi.org/project/prsaw/ 

## Installation

You can install released versions of prsaw from the Python Package Index with pip or a similar tool:

**Stable Release:** `pip install prsaw`<br>
**Working Version:** `pip install git+https://github.com/CodeWithSwastik/prsaw.git`

## Example Usage (No API KEY)
```python
# import the module
from prsaw import RandomStuff

# initiate the object
rs = RandomStuffV2() 

# get a response from an endpoint
response = rs.get_ai_response("How are you?")
print(response)

# close the object once done (recommended)
rs.close()
```

## Example async usage (With an API key)
```python
# import the module
from prsaw import RandomStuff

# initiate the object with async mode
api_key = "Your API Key"
rs = RandomStuff(async_mode = True, api_key = api_key)

# get a joke
joke = await rs.get_joke()
print(joke)

# close the session
await rs.aclose()
```

## Plans
If you've purchased a premium plan you can pass that as a paramater to RandomStuffV3 or RandomStuffV4
```python
plan = "Can be pro/biz/mega/ultra"
rs = RandomStuffV4(api_key = api_key, plan=plan)
```


## Server (V4)
You can specify the server in RandomStuffV4 if you want
```python
server = "Can be primary/backup/unstable"
rs = RandomStuffV4(api_key = api_key, server=server)
```
## Misc
You can also pass `dev_name`, `bot_name` and `ai_language` as paramaters to RandomStuffV3 or RandomStuffV4.

## Functions available

The current list of asynchronous functions available are:

```python
# endpoints
await get_joke(_type)  # Refer to https://api.pgamerx.com/endpoints
await get_image(_type) # for all the endpoints
await get_ai_response(msg)

# others
await aclose() # closes the object
 ```
 
 ## Important Links
 * Register API key - [Click Here](https://api.pgamerx.com/register)           
 * Documentation/Endpoints - [Click Here](https://api.pgamerx.com/endpoints/)
noice 0.1.6
Data Engineering tools.
License: MIT
Requires Python: >=3.9,<4.0

# noice

noice is a collection of [noice](https://www.merriam-webster.com/words-at-play/what-does-noice-mean) data tools for noice [data people](https://www.reddit.com/r/dataengineering/comments/nc6ptk/tell_us_youre_a_data_engineer_without_telling_us/).

![noice](https://media.giphy.com/media/4KF85OSbyjVOfyjksJ/giphy.gif)

## pypi

[noice](https://pypi.org/project/noice/)

---
Made with ❤️ by the team at [Mashey](http://mashey.com)
oasis 0.1.3
Optimal Asymptotic Sequential Importance Sampling
License: MIT
Keywords: F-measure active sampling evaluation classification recall precision

=====
OASIS
=====

.. image:: https://travis-ci.org/ngmarchant/oasis.svg?branch=master
    :target: https://travis-ci.org/ngmarchant/oasis
.. image:: https://img.shields.io/badge/License-MIT-yellow.svg
    :target: https://opensource.org/licenses/MIT
.. image:: https://badge.fury.io/py/oasis.svg
    :target: https://pypi.python.org/pypi/oasis

OASIS is a tool for evaluating binary classifiers when ground truth class
labels are not immediately available, but can be obtained at some cost (e.g.
by asking humans). The tool takes an unlabelled test set as input and
intelligently selects items to label so as to provide a *precise* estimate of
the classifier's performance, whilst *minimising* the amount of labelling
required. The underlying strategy for selecting the items to label is based on
a technique called *adaptive importance sampling*, which is optimised for the
classifier performance measure of interest. Currently, OASIS supports
estimation of the weighted F-measure, which includes the F1-score, precision
and recall.

Important links
===============
Documentation: https://ngmarchant.github.io/oasis

Source: https://www.github.com/ngmarchant/oasis

Technical paper: https://arxiv.org/pdf/1703.00617.pdf

Example
=======
See the Jupyter notebook under ``docs/tutorial/tutorial.ipynb``::

    >>> import oasis
    >>> data = oasis.Data()
    >>> data.read_h5('Amazon-GoogleProducts-test.h5')
    >>> def oracle(idx):
    >>>     return data.labels[idx]
    >>> smplr = oasis.OASISSampler(alpha, data.preds, data.scores, oracle)
    >>> smplr.sample_distinct(5000) #: query labels for 5000 distinct items
    >>> print("Current estimate is {}.".format(smplr.estimate_[smplr.t_ - 1]))


License and disclaimer
======================
The code is released under the MIT license. Please see the LICENSE file for
details.
pgcr-log 1.0.3
用来记录日志的极简库，支持控制台彩色字体输出
License: MIT
Requires Python: >=3.7,<4.0

# pgcr_log
用来记录日志的极简库，支持控制台彩色字体输出

## 快速入门
### 简单使用
```python
from pgcr_log import log

log.info("info.............")
log.debug("debug.............")
log.success("success.............")
log.error(f"error.............{[11, 22, 33, 44, 55]}")
```

### 设置日志文件大小和最大日志文件数量
```python
from pgcr_log import Log

log = Log()
log.set_level("success")
log.log_to_file(limit=1, max_file_count=10)
log = log.logger
for i in range(10000):
    log.debug("This message was debug")
    log.success("This message was successful")
    log.info("Hello world")
    log.warning("This is a warning")
    log.error("This is an error")
    log.critical("This is  a critical error")
```