semvec/pypi-packages huggingface dataset:
Fermat-FasterCoding 1.0.1
Example code for the Fermats-Little-Theorem modular inverse algorithm

# Fermats Little Theorem

This repository contains an example
of the Fermats Little Theorem algorithm
for C++ and one for Python3.

## C++

To run the example for C++
change into the `c++` folder
and run the following bash script in Linux.

```bash
mkdir build && \
cd build && \
cmake .. -G "Unix Makefiles" && \
make
```

The program should be build and 
you can see an executable called `modinverse`.

You can test it with `./modinverse arg1 arg2`.

For example:

```bash
./modinverse 3 5
modular inverse of 3 mod 5 is 2
```

```bash
./modinverse 2 4
There is no modular inverse!
```

```bash
./modinverse 2  
Not enough input arguments!
```

## Python3

You can run this example from source or 
install it with pip and include it in your project.

### Source

**Requirement**
- virtualenv

To run this example from source,
run the following bash script in Linux.

```bash
python3 -m virtualenv . && \
source ./bin/activate && \
pip3 install -r requirements.txt
```

This will generate a virual environment and
install the requirement.

After that you can run the programm with

`python3 Fermat/fermat.py arg1 arg2`

For example:

```bash
python3 Fermat/fermat.py 2 5
The mod inverse of 2 mod 5 is 3
```

```bash
python3 Fermat/fermat.py 2 4
There is no modular inverse!
```

```bash
python3 Fermat/fermat.py 2  
Not enough input arguments!
```

### Pip

To install this example with pip, simply run:

`pip3 install Fermat-FasterCoding`

Then you can use it as import like this:

```python
import Fermat.fermat as fermat

inverse = fermat.modInverse(3, 5) # This will return 2
```
AX3003P 0.1
Package for controlling AX-3003P Programmable DC Power Supply

# AX3003P Programmable DC Power Supply Control Library
[![Documentation Status](https://readthedocs.org/projects/ax3003p/badge/?version=latest)](https://ax3003p.readthedocs.io/en/latest/?badge=latest)

Python package that provides an API for controlling AX3003P programmable power supply.
It works on Linux, OSX, Windows and BSD.

## Features
 - Enabling/disabling the output.
 - OVP and OCP control.
 - Voltage and current control.
 - Output voltage, current and power measurements.

## Requirements
 - Python 2.7 or Python 3 and newer
 - pySerial

## Installing

#### From PyPI
AX3003P can be installed from PyPI::
```
pip3 install AX3003P
```

Or in case of using Python 2.7::
```
pip install AX3003P
```

#### From source
```
python3 setup.py install
```

Or in case of using Python 2.7
```
python setup.py install
```

## Documentation
Available on readthedocs.org : https://ax3003p.readthedocs.io/en/latest
ipython-namespaces 0.1.3
Extension for IPython/Jupyter Notebooks that adds namespaces that you can enter and re-enter
Requires Python: >=3.6,<4.0

# IPython Namespaces

Extension for IPython/Jupyter Notebooks that adds namespaces that you can enter and re-enter.

(Because: “Namespaces are one honking great idea – let’s do more of those!”)

## Usage (in a Jupyter Notebook)

Install and load the extension:

```
!pip install -U ipython-namespaces
%load_ext ipython_namespaces
```

Use the `space` cell magic:

```
foo = 23
```

```
%%space dustin

bar = 42
foo, bar
```

Output: `(23, 42)`

```
foo, bar
```

Output: `NameError: name 'bar' is not defined`

```
%%space dustin

foo, bar
```

Output: `(23, 42)`

```
from ipython_namespaces import Namespaces

Namespaces.dustin['bar']
```

Output: `42`

## Features

1. Separate namespaces within one Jupyter Notebook
2. Access to other namespaces via the `Namespaces` class
3. Unchanged behavior of `display` – the value of the last line in a cell is displayed
4. Unchanged behavior of tracebacks – the problematic line in one’s own code is highlighted

## Acknowledgements

Thanks to Davide Sarra and the Jupyter Spaces extension for the inspiration!
azoo 1.3.1
Downloads apks from androzoo repository https://androzoo.uni.lu/

[![Build Status](https://travis-ci.com/ArtemKushnerov/az.svg?branch=master)](https://travis-ci.com/ArtemKushnerov/az)

Downloads specified number of **randomly chosen** apks satisfying specified criteria from androzoo repository.  
Saves specified metadata to *metadata.csv*. dexdate, apksize and vtdetection require specifying lower and upper bounds in format lower:upper, both inclusive.  
One of the bounds can be omitted (i.e. you can write :upper or lower:)  
pkgname, markets, metadata, sha256, sha1, md5 can be either single values or comma separated lists. 
Key and input file can be specified as options or via local or global config file.
Allows downloading in the multiple threads.

### PREREQUISITES
- Python 3.6

### INSTALLATION

1. `pip install azoo`

2. create *.az* file in your home directory (~ on Linux 
and macOS, C:\Users\%USERNAME% on Windows) or in the directory where you want to invoke `az` from with the following contents:  
```
key=%API_KEY%  
input_file=%PATH_TO_INPUT_FILE%
```
Alternatively, use cli options `-k` and `-i`

Request the api key from androzoo, download and uncompress the input file from here https://androzoo.uni.lu/lists

### CONFIGURATION
You can configure api key and input file either using cli options or *.az* configuration file. The file can be placed locally (in directory where you want to invoke `az` from) or globally (in your home directory).
The precedence for reading config values is as follows: cli -> local-> global.

### SAMPLE USAGE  

  `az -n 10 -d 2015-12-11: -s :3000000  -m play.google.com,appchina`

This means: download 10 apks with the dexdate starting from the
2015-12-11 (inclusive), size up to 3000000 bytes (inclusive) and present on either play.google.com or appchina

##### Options:  
```
  -n, --number INTEGER     Number of apks to download.
  -d, --dexdate TEXT       The date on a dex file, format %Y-%m-%d, e.g.  2015-10-03.
  -s, --apksize TEXT       Apk size, in bytes.
  -vt, --vtdetection TEXT  Virus total rating, integer.
  -pn, --pkgname TEXT      Package names.
  -m, --markets TEXT       Markets, e.g. play.google.com. Possible values (can differ, since repository is updating): 1mobile,angeeks,anzhi,apk_bang,appchina,fdroid,freewarelovers,genome,hiapk,markets,mi.com,play.google.com,proandroid,slideme,torrents.
  --sha256 TEXT            SHA256 hashes.
  --sha1 TEXT              SHA1 hashes of apks to download.
  --md5 TEXT               MD5 hashes of apks to download.
  -md, --metadata TEXT     Metadata. This is a subset of latest.csv column names to keep in metadata.csv. By default sha256,pkg_name,apk_size,dex_date,markets.  
  -o, --out TEXT           Output folder name. By default current directory.
  -sd, --seed INTEGER      Seed for a random algorithm.
  -k, --key TEXT           Androzoo api key.
  -i, --input-file TEXT    Path to input csv.
  -t, --threads INTEGER    Number of threads for concurrent download. 4 by default.
  --version                Show the version and exit.
  --help                   Show this message and exit.  
```
building-energy-forecastor 0.0.3
Pour l'instant fait pas grand chose

# Forecastor for Buildings' Consumption

Go check ce lien pour rÃ©diger le README: 
[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)

### Installation
Command line:
*pip install building_energy_forecastor*

### Features' list for preprocessing data from *src/building_preprocess*
* **day_of_week(date_serie)**: Takes a pandas.Series of dates and returns a pandas.Series of corresponding week days
(['Monday', 'Tuesday', ...]).
* **set_time_index(df, timeindex='Timestamp')**: Set the time column as index of the dataframe df. By default the column's
label is 'Timestamp'.
* **time_to_cycle(df, timeindex='Timestamp')**: From the 3rd competitor of the [Forecast challenge](https://www.drivendata.org/competitions/51/electricity-prediction-machine-learning/)
by Schneider Electric. Add column to a copy of df containing cosinus and sinus functions of the time of the day, the month of the year and the day of the year.
* **add_weather(df, weather, timeindex='Timestamp', freq_temp='D')**: From the 3rd competitor of the [Forecast challenge](https://www.drivendata.org/competitions/51/electricity-prediction-machine-learning/) by Schneider Electric.
Adds the weather data to the training dataset (*df* here) merging the two dataframes on the 'Timestamp' and rouding the time
value in weather to the precised freq_temp ('D' by default).
* **fill_temperature(df, tempindex='Temperature')**: fill the NaN values in the tempindex column by computing the mean on the
two closest framing values.

### Model functions from *src/building_model*
* **building_regressor()**: Returns a linear regressor from Scikit-learn.
* **building_train(reg, X, y)**: Trains the regressor with X the data and Y the targeted values.
* **building_prediction(reg, X)**: Returns a pandas.DataFrame showing the prediction of the regressor *reg* given the data *X*.
aws-lambda-context 1.1.0
AWS Lambda Context class for type checking and testing
Requires Python: >= 3.6

Python Lambda Context
=====================

A micro library that provides the AWS Lambda Context class for type checking and testing.

Installing
----------

.. code-block::

    pip install aws-lambda-context

Usage
-----

Import the LambdaContext on your handler file and type hint the lambda function with it:

.. code-block:: python

    from aws_lambda_context import LambdaContext

    def my_lambda_handler(event: Any, context: LambdaContext) -> None:
        ...

The type hint should enables type checking with mypy_ and editor auto-completion

The class is also useful as a mock during tests:

.. code-block:: python

    from aws_lambda_context import (
        LambdaClientContext,
        LambdaClientContextMobileClient,
        LambdaCognitoIdentity,
        LambdaContext
    )

    def test_handler():
        lambda_cognito_identity = LambdaCognitoIdentity()
        lambda_cognito_identity.cognito_identity_id = 'cognito_identity_id'
        lambda_cognito_identity.cognito_identity_pool_id = 'cognito_identity_pool_id'

        lambda_client_context_mobile_client = LambdaClientContextMobileClient()
        lambda_client_context_mobile_client.installation_id = 'installation_id'
        lambda_client_context_mobile_client.app_title = 'app_title'
        lambda_client_context_mobile_client.app_version_name = 'app_version_name'
        lambda_client_context_mobile_client.app_version_code = 'app_version_code'
        lambda_client_context_mobile_client.app_package_name = 'app_package_name'

        lambda_client_context = LambdaClientContext()
        lambda_client_context.client = lambda_client_context_mobile_client
        lambda_client_context.custom = {'custom': True}
        lambda_client_context.env = {'env': 'test'}

        lambda_context = LambdaContext()
        lambda_context.function_name = 'function_name'
        lambda_context.function_version = 'function_version'
        lambda_context.invoked_function_arn = 'invoked_function_arn'
        lambda_context.memory_limit_in_mb = 'memory_limit_in_mb'
        lambda_context.aws_request_id = 'aws_request_id'
        lambda_context.log_group_name = 'log_group_name'
        lambda_context.log_stream_name = 'log_stream_name'
        lambda_context.identity = lambda_cognito_identity
        lambda_context.client_context = lambda_client_context

        assert handler({}, lambda_context) == 'something'

References
----------

- https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html

.. _mypy: http://mypy-lang.org/