semvec/pypi-packages huggingface dataset:
sqliteplus 1.1.0
Прога для преобразования данных полученных из БД в словарь, где ключами выступают названия полей.

Прога для преобразования данных полученных из БД в словарь, где ключами выступают названия полей.

Версия 1.1.0

Написана prok0l:    https://github.com/prok0l/

Инструкция: обернуть функцию connect в декоратор sqlite_dict (sqlite) или sql_dict (PostgreSQL, MariaDB, MS SQL)
deale-shared-library 0.0.7
A shared library for Deale microservices

# deale_shared_library

deale_shared_library is a shared library for Deale microservices, providing easy-to-use interfaces to AWS services such as DynamoDB and Cognito.
Installation

You can install deale_shared_library via pip:

``` python
pip install deale_shared_library
```


### Usage

Below are brief overviews and examples of how to use the DynamoDB and Cognito classes provided by this library.

### DynamoDB Class

The DynamoDB class is a wrapper around the AWS Boto3 DynamoDB resource, providing methods to perform operations like scanning a table, querying a table, and putting items into a table.

#### Example


```python
from deale_shared_library import DynamoDB

# Initialize DynamoDB class
ddb = DynamoDB()

# Put an item into a table
ddb.put_item("my_table", {"id": "1", "name": "John Doe", "email": "john@example.com"})

# Scan a table
response = ddb.scan("my_table")
print(response["Items"])

# Query a table
response = ddb.query("my_table", KeyConditionExpression=Key('id').eq('1'))
print(response["Items"])
```


### Cognito Class

The Cognito class provides methods to interact with AWS Cognito, such as fetching user details and user attributes.

#### Example


``` python
from deale_shared_library import Cognito

# Get Cognito user
user = Cognito.get_cognito_user("username")

# Get Cognito user attribute
email = Cognito.get_cognito_user_attribute("username", "email")
```


### Lambda Class

The `Lambda` class provides an interface to interact with AWS Lambda functions.

#### Example

```python
from deale_shared_library import Lambda

# Invoke a Lambda function
response = Lambda.invoke_function(
    "test_function",
    path_parameters={"param1": "value1"},
    query_string_parameters={"param2": "value2"},
    body={"key": "value"},
    cognito={"username": "test_user"}
)
```