I can give an article on how to accurately calculate the marker price using connecting curves.
Token’s price calculation I need using connecting curves
Connection curves are an essential tool for Solana developers to manage liquidity and ensure their token stability. In this article, we will look at how to accurately calculate the marker prices using the connecting curves.
Introduction to the connection curve
The binding curve is a mathematical function that is input value (eg the current market price) on the output value (eg marker price). The connection curve is designed to ensure a reliable and effective type of liquidity management and avoid price shocks.
Token price calculation using connecting curves
In order to accurately calculate the marker price using a binding curve, you must follow these steps:
1. Step: Search Account Information
First, you need to look for account information from a user who wants to calculate the marker price. You can use the “structure” library to analyze the user’s public key.
`Python
from the construction structure, int64ul
Import solana.rpc
Define the structure of the binding curve
Bondingcurvestruct (Structures) Class:
Def __init __ (itself, symbol, min_price, max_price):
self.symbol = symbol
self.min_price = min_price
self.max_price = max_price
Search Account Information to the user who wants to calculate the marker price
Solaris_key = "your_solarius_key"
replace with your Solana key
user_pubkey = solaris_key.public_Key ()
Bonding_curve = bondingcurvestruct (
Symbol = "Sun",
Define the connecting curve symbol
Min_Price = 1000,
Define the minimum price of the connection curve
Max_Price = 20000
Define the maximum price of the connection curve
)
Account_info = solana.rpc.fetch_account_info (user_pubkey, boxing_curs)
2. Step: Analyze account information
Once you have received your account information, you need to analyze them to obtain the information you need. You can use the “structure” library’s internal analysis features to convert the account account into a structured format.
`Python
Analyze account information in structured format
Account_info_struct = account_info.data
Bonding_curve_info = account_info_struct.account_info
Use the minimum and maximum prices of the connection curves
minimal
Max_price = bonding_curve_info.price.max
Step 3: Calculate the marker price using the connection curve
Now that you have obtained the information you need, you can calculate the marker price using the connection curve. You can use simple linear interpolation or more sophisticated algorithm for accuracy.
`Python
Define the marker symbol and minimum and maximum prices
token_symbol = "Sol"
min_price_token = 1000
Max_price_token = 20000
Calculate the marker price using the connection curve
Bonding_curve_struct = bondingcurstrukt (token_symbol, min_price_token, max_price_token)
Token_price = (min_price - min_price_token) / (max_price - min_price_token) * (Max_price - Max_price_token) + min_price_token
Step 4: Print the result
Finally, you can print the calculated marker price.
`Python
Print the result
Print ("Marker Price:", Token_Price)
Example of case use
Here is an example of how to use this code to calculate the price of a marker for a particular user:
“ Python
Solaris_key = “your_solarius_key”
replace with your Solana key
user_pubkey = solaris_key.public_Key ()
Bonding_curve = bondingcurvestruct (
Symbol = “Sun”,
Define the connecting curve symbol
Min_Price = 1000,
Define the minimum price of the connection curve
Max_Price = 20000
Define the maximum price of the connection curve
)
Account_info = solana.rpc.fetch_account_info (user_pubkey, boxing_curs)
Analyze account information in structured format
Account_info_struct = account_info.