Girls make a million excuses to avoid being with the guy who isn't the one they're interested in at that moment. They keep a bunch of sausages on the backburner most times. This one girl who I liked said her tonsils were out and she couldn't make it after 3 months of love emojis and this kind of thing. Then it was something else. She said she was in a dating relationship. Only, there was no evidence on IG. Women change their minds all the time and they don't like to be forced to meet someone. Maybe they just like talking to you on the DM's for an ego boost. One thing's for sure though; If you try to force them to meet they back out quicker than an alleyway cat before a pile of exploding excrement.
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How to make an AI trading bot
Python has emerged as a powerful tool in the hands of amateur and professional traders alike. There are libraries available for cryptocurrency trading, backtesting, and simulation. In this article, we will be focusing on the creation of a simple trading bot using the Python programming language.
The first step is to install the necessary libraries. We will be using the TensorFlow library for Artificial Intelligence, the NumPy library for scientific computing, and the pandas library for data analysis.
pip install tensorflow numpy pandas
We will also be using the Coinbase API to get real-time pricing data. You will need to create a Coinbase account and register for a Coinbase API key.
Once the libraries are installed, we can start coding the trading bot. Our bot will consist of three components:
The first component is responsible for gathering price data from the Coinbase API.
The second component is responsible for analyzing the data and making buy and sell decisions.
The third component is responsible for sending orders to the Coinbase API.
The first component is a simple function that downloads the latest Bitcoin price data from the Coinbase API.
def get_price(btc_pair):
url = "https://api.coinbase.com/v2/prices/"
request = urllib.request.Request(url)
response = urllib.request.urlopen(request)
data = response.read()
return data
The second component is a bit more complicated. It consists of two functions: one for buying and one for selling.
The buy function will analyze the price data and make a buy decision if the price is below the moving average. It will also check the volume to make sure there is enough liquidity.
def buy(btc_pair, volume):
ma = moving_average(btc_pair, period=10)
if ma < price:
buy_volume = volume
else:
buy_volume = 0
return buy_volume
The sell function is similar, except it will sell if the price is above the moving average.
def sell(btc_pair, volume):
ma = moving_average(btc_pair, period=10)
if ma > price:
sell_volume = volume
After reading this article, you should be able to use python to make a trading bot. Trading bots can help you make more efficient and profitable trades by automatically executing trades for you.
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