semvec/pypi-packages huggingface dataset:
goated 0.0.7
Python library for interacting with the Goated Exchange API.
License: MIT
Requires Python: >=3.9
Keywords: goated,betting,trading,sports,sportsbetting,exchange,bet,prediction,market

# Goated Python Library

A handy library to interacting with, sourcing information from and trading on the Goated Exchange.

## Creating an authenticated Client to interact with the API using email and password

```
from goated.client import TradingClient

# Create a Goated Client Object to interact with the API
client = TradingClient.create_with_login(
    url = "https://api.goated.com",
    email = "YOUR_GOATED_EMAIL",
    password = "YOUR_GOATED_PASSWORD"
)

```

## Or using API Key and Secret (available from account tab)

```
from goated.client import TradingClient

# Create a Goated Client Object to interact with the API
client = TradingClient.create_with_api_key(
    url = "https://api.goated.com",
    api_key = "YOUR_GOATED_API_KEY",
    api_secret = "YOUR_GOATED_API_SECRET"
)

```

## Creating a State container, sourcing and loading some user information into the container

```
# Create a State Container object to hold relational state
state = Container()

# Get balances response from API
balances_response = client.get_balances()
# Add/update it within the state container
state.update_balances(balances_response)

# Get positions response from API
positions_response = client.get_positions() # Without any filters
# Add/update it within the state container
state.update_positions(positions_response)

# Get orders response from API
orders_response = client.get_orders() # Without any filters
# Add/update it within the state container
state.update_orders(orders_response)

print(state.__dict__)

```

## Sourcing information from the API 

```
# Get all categories
categories = client.get_categories()  # Without any filters

print('Categories:')
print(categories)

# Get subcategory record for first category
category_id = categories[0].get('id')
subcategories = client.get_subcategories(
    category_ids=[category_id]
) if category_id != None else []
print('Subcategories:')
print(subcategories)

# Get events in the first subcategory
subcategory_id = subcategories[0].get('id') if len(subcategories) > 0 else None
events = client.get_events(
    subcategory_ids=[subcategory_id]
) if subcategory_id != None else []
print('Events:')
print(events)

# Get all markets in the first event
event_id = events[0].get('id') if len(events) > 0 else None
markets = client.get_markets(
    event_id=[event_id]
) if event_id != None else []
print('Markets:')
print(markets)


```
Flask-Boilerplate-Creator 0.0.4
Create boilerplate structure of flask web application
License: MIT
Requires Python: >=3.8
Keywords: fbc,flask-boilerplate-creator,flask boilerplate creator

# Flask Boilerplate Creator
Create boilerplate for flask web application

Install using pip

```cmd
> pip install Flask-Boilerplate-Creator
```

run the Flask-Boilerplate-Creator

```cmd
> python -m fbc
```

After running above command it will ask for other modules to be installed, if not leave it blank

```
Select modules to install
[0] flask-sqlalchemy
[1] flask-migrate
[2] flask-admin
[3] flask-wtf
[4] flask-session
Enter module index numbers separated by comma to add:
```

Enter pip command if default command is not working, in some os value for it may be `python3 -m pip install`

```
Enter pip command (default is 'python -m pip install'):
```

All ok, it will install the module now
After installing all modules it will create files and folders on your system
This operation will remove any file content or delete folder if exists

```
Installing modules: flask
using command python -m pip install
*Installing flask

##:- pip install output will be here

*Structure created successfully.
If you get error like module not found, run `python -m pip install -r requirements.txt` command.
```

Done - structure is created.