semvec/pypi-packages huggingface dataset:
glade-api-python 1.0.0
Glade API Python Package
Requires Python: >=3.8

## About

To Learn more, visit https://developer.gladefinance.co/docs

## Getting Started 
You need a Merchant ID and Key to authenticate against the API, please contact support@gladefinance.co to setup a demo account.

## Installation
You include the class in your project or you can add the repo in your files as in the example below:



## Set environment

```` 
from src.glade_functions import Glade

merchantId = "YOUR_MERCHANT_ID"
merchantKey = "YOUR_MERCHANT_KEY"
````

For Production environment
```` 
api = Glade(merchantId, merchantKey, True)
````

For Sandbox environment
```` 
api = Glade(merchantId, merchantKey, False)
````

## Methods
BVN Verification
```` 
api.bvnValidation(bvnNumber); 
````


Get Chargeable Banks
```` 
api.supportedChargeableBanks(); 
````

Get Bank List
```` 
api.bankList(); 
````

Verify Account Name
```` 
api.verifyAccountName(accountNumber, bankCode, bankName); 
````

Get Personalized Account Info
```` 
api.personalizedAccount( accountName, accountEmail, accountBvn, reference, channel = "providus"); 
````

Create Customer
```` 
api.createCustomer(name, email, phoneNumber, address); 
````

Get All Customers
```` 
api.getCustomers(); 
````

Get A Single Customer's Details
```` 
api.getCustomerDetail(customerId); 
````

Get All Bill Categories
```` 
api.getBillCategory(category = None); 
````

Get Bill ID
```` 
api.getBillById(billId); 
````

Resolve Bill
```` 
api.resolveBill(payCode, reference); 
````

Purchase Bill
```` 
api.purchaseBill(payCode, amount, reference, orderReference = None); 
````

Verify Bill Purchase
```` 
api.verifyBillPurchase(transactionReference); 
````

Make A Single Transfer
```` 
api.transfer(amount, receiverAccountNumber, receiverBankCode, senderName, reference, narration);
````

Verify Single Transfer
```` 
api.verifySingleTransfer(reference); 
````

Make Bulk Transfer
```` 
api.bulkTransfer(transferObjects); 
````

Create Payment Link
````
 api.createPaymentLink(title, description, amount, type, payerBearsFees, acceptNumber, notificationEmail, customLink = None, redirectUrl = None, customMessage = None, frequency = None); 
 ````

Create Ticket
````  
api.createTicket(title, description, amount, type, payerBearsFees, acceptNumber, notificationEmail, ticketData, customLink = None,  redirectUrl = None, customMessage = None, frequency = None); 
````

Create Invoice
```` 
api.invoice(customerId, chargeUser, shipping, vat, dueDate, allowedDiscount, invoiceItems, note, discountType = None, invoiceId = None); 
````


## Return Values
All methods return an array.
Topsis-Amit-102003053 1.0.0
Topsis package for MCDM problems
Requires Python: >=3.6

# Topsis-Amit-102003053
For : Assignment(UCS654)<br>
Submitted by: Amit Kumar<br>
Roll no:102003053
Group:3COE3
## Description
This is a python package used to implement TOPSIS(Technique of Order Preference Similarity to the Ideal Solution) for MCDA(Multiple criteria decision analysis)

<br>

## How to use this package:

## Installation

pip install Topsis-Amit-102003053

## Example:

## Sample dataset
Fund Name | P1 | P2 | P3 | P4 | P5
------------ | ------------- | ------------ | ------------- | ------------ | ------------
M1 | 0.78 | 0.61 | 5.5 | 34.7 | 10.4
M2 | 0.88 | 0.77 | 5 | 58.4 | 16.26
M3 | 0.61 | 0.37 | 5.9 | 39.9 | 11.7
M4 | 0.76 | 0.58 | 4.2 | 57.7 | 15.81
M5 | 0.84 | 0.71 | 3.2 | 48 | 13.19
M6 | 0.76 | 0.58 | 4 | 68.8 | 18.54
M7 | 0.81 | 0.66 | 6.5 | 38.2 | 11.54
M8 | 0.81 | 0.66 | 3.2 | 32.8 | 9.37

## Input
### In Command Prompt
Enter filename followed by .csv extension, then enter values of weights separated by commas like "1,1,1,2,2",then enter values of impacts separated by commas like "+,+,-,-,+" without giving space in between comma value, then enter name of file where you want to save output followed by .csv extension
```
topsis data.csv "1,1,1,2,2" "+,+,-,-,+" out.csv
```
## Output
This will be in our Output csv file
Fund Name | P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank
------------ | ------------- | ------------ | ------------- | ------------ | ------------ | ------------ | ------------
M1 | 0.78 | 0.61 | 5.5 | 34.7 | 10.4 | 0.5303740545041122 | 4
M2 | 0.88 | 0.77 | 5 | 58.4 | 16.26 | 0.5372510220778413 | 3
M3 | 0.61 | 0.37 | 5.9 | 39.9 | 11.7 | 0.4715707210914604 | 8
M4 | 0.76 | 0.58 | 4.2 | 57.7 | 15.81 | 0.5099483054760279 | 6
M5 | 0.84 | 0.71 | 3.2 | 48 | 13.19 | 0.57723478293325 | 1
M6 | 0.76 | 0.58 | 4 | 68.8 | 18.54 | 0.49447887833737925 | 7
M7 | 0.81 | 0.66 | 6.5 | 38.2 | 11.54 | 0.5244107252631429 | 5
M8 | 0.81 | 0.66 | 3.2 | 32.8 | 9.37 | 0.5576533672285703 | 2
sql-test-kit 0.4.0
Framework for testing SQL queries
Requires Python: >=3.8,<3.12

# sql-test-kit

This is a framework for testing SQL queries.
It works by directly running the queries against the targeted engine, thus being robust to any change in the
corresponding SQL dialect.
Moreover, it is currently focused on interpolating test data directly inside the SQL queries, making the test much
quicker than if it was creating actual tables.

# Installation

This package is available on Pypi, so you can use your favorite dependency managment tool to install it. For example :
* with pip : 
```shell
pip install sql-test-kit
```
* with poetry : 
```shell
poetry add sql-test-kit
```

# Usage example

`sql-test-kit` is currently available for most SQL engines (Postgres, Redshift, Snowflakes...), and is particularly useful
for those where no framework exists for locally testing SQL queries.

Nevertheless, a specific implementation has been written for BigQuery, in order to facilitate Table object initialization,
as well as null values interpolation in tests.

Here is a simple example of instantiating a Table object and a SQL query for BigQuery :
```python
from sql_test_kit import BigqueryTable, Column


sales_amount_col = "SALES_AMOUNT"
sales_date_col = "SALES_DATE"
sales_table = BigqueryTable(
    project="project",
    dataset="dataset",
    table="table",
    columns=[
        Column(sales_amount_col, "FLOAT64"),
        Column(sales_date_col, "STRING"),
    ],
)
current_year_sales_by_day_query = f"""
    SELECT {sales_date_col}, SUM({sales_amount_col}) AS {sales_amount_col}
    FROM {sales_table}
    WHERE {sales_date_col} >= "2023-01-01"
    GROUP BY {sales_date_col}
    """
```

You can then test it this way :
```python
import pandas as pd
from google.cloud.bigquery import Client

from sql_test_kit import QueryInterpolator


def test_current_year_sales_by_day_query():
    # Given
    sales_data = pd.DataFrame(
        {
            "SALES_ID": [1, 2, 3, 4],
            sales_date_col: ["2022-12-31", "2023-01-01", "2023-01-01", "2023-01-02"],
            sales_amount_col: [10, 20, 30, 40],
        }
    )

    # When
    interpolated_query = QueryInterpolator() \
        .add_input_table(sales_table, sales_data) \
        .interpolate_query(current_year_sales_by_day_query)
    current_year_sales_by_day_data = Client().query(interpolated_query).to_dataframe()

    # Then
    expected_current_year_sales_by_day_data = pd.DataFrame(
        {
            sales_date_col: ["2023-01-01", "2023-01-02"],
            sales_amount_col: [50, 40],
        }
    )

    pd.testing.assert_frame_equal(
        current_year_sales_by_day_data,
        expected_current_year_sales_by_day_data,
        check_dtype=False,
    )
```
showtools 2.0.3
Show storage and network devices in table format on cli

# showtools
This tool displays information about disks or network cards in a nice
ASCII table format on the command line. 

- All network interfaces and some of their properties
- All storage devices (hdd/sdd) and some of their properties (SMART)

Examples:

Show information about network interfaces:

![network][netw]

[netw]: http://louwrentius.com/static/images/showtools/shownet.png

Show SMART information about disks:

- PS = Pending Sector
- RS = Reallocated Sector
- RSE = Reallocated Sector Event

![showdisk01][1]

[1]: http://louwrentius.com/static/images/showtools/showdisk01.png

This is the output for a 24-drive NAS. You can zoom in by clicking on the image.

![showdisk02][2]

[2]: http://louwrentius.com/static/images/showtools/showdisk02.png

### Installation

Showtools is available through pypi.
Just enter: 

    pip install showtools

Manual install:

1. clone this repository with git clone https://github.com/louwrentius/showtools
2. cd showtools
3. python3 setup.py install
4. install hdparm, smartmontools and ethtool

    apt install hdparm smartmontools ethtool

### Usage:
```
usage: show [-h] [-E] [-g] [-a] [-m] [-k] [-S] [-D] [-e] [-s] [-z] [-f] [-c] [-p] [-w] [-o] [-t] [-H] [-P] [-r] [-R] [-C] [-u] [-n] [-l] [-4] [-6] [-M] [-T] [-d] [-F] {disk,net}

Show detailed disk|net device information in ASCII table format

positional arguments:
  {disk,net}            Show disk information

optional arguments:
  -h, --help            show this help message and exit

generic_settings:
  Options that apply for all device types.

  -E, --transparent     Disable table formatting (no lines)
  -g, --noheader        Disable table header (in transparent mode)
  -a, --all-opts        show all information

storage:
  Generic options for storage devices

  -m, --model           device model
  -k, --type            device type (HDD/SDD)
  -S, --serial          device serial number
  -D, --state           drive power status (active/standby)
  -e, --apm             Advanced Power Mode
  -s, --size            device size in Gigabytes
  -z, --speed           SATA Link in Gbps
  -f, --firmware        device firmware version
  -c, --controller      controller to which device is connected
  -p, --pcipath         /dev/disk/by-path/ ID of the device
  -w, --wwn             device World Wide Name
  -o, --scsi            /dev/by-id/scsi
  -t, --temp            temperature in Celcius
  -H, --hours           power on hours
  -P, --pending         pending sector count
  -r, --reallocated     reallocated sector count
  -R, --reallocatedevent
                        reallocated sector event count
  -C, --crc             CRC error
  -u, --startstop       spin up/down
  -n, --park            head parking

network:
  Available options for network devices

  -l, --link            network card link status
  -4, --ipv4            IPv4 address
  -6, --ipv6            IPv6 address
  -M, --mac             hardware / MAC address
  -T, --show-type       network card type
  -d, --driver          driver module
  -F, --firmware-version
                        firmware version
```
florest 0.0.1
Библиотека создана Флорестом, тут дохрена хороших функций. Пользуемся!

Пример использования:
```import florest
url = input(f'Введите ссылку на вебхук.')
message = input(f'Введите, сообщение, которое вы хотите ввести.)
a = florest.Response.write_webhook_message
print(a)```
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: kirillborisenko985@gmail.com
License: UNKNOWN
Description: UNKNOWN
Platform: UNKNOWN