Python crypto trading bot
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In Grid 3, add a Basic Operation element to execute the evaluation logic. Here is the code of that element: The element outputs a 1 if you should buy or a -1 if you should sell. An output of 0 means there's nothing to do right now. Use a Branch element to control the execution path. Due to the fact that both 0 and -1 are processed the same way, you need an additional Branch element on the right-most execution path to decide whether or not you should sell.
Grid 3 should now look like this: Execute orders Since you cannot buy twice, you must keep a persistent variable between the cycles that indicates whether you have already bought. You can do this with a Stack element. The Stack element is, as the name suggests, a representation of a file-based stack that can be filled with any Python data type. You need to define that the stack contains only one Boolean element, which determines if you bought True or not False.
As a consequence, you have to preset the stack with one False. You can set this up, for example, in Grid 4 by simply passing a False to the stack. The Stack instances after the branch tree can be configured as follows: Image by: Configuring the Stack element In the Stack element configuration, set Do this with input to Nothing. Otherwise, the Boolean value will be overwritten by a 1 or 0. This configuration ensures that only one value is ever saved in the stack True or False , and only one value can ever be read for clarity.
Right after the Stack element, you need an additional Branch element to evaluate the stack value before you place the Binance Order elements. Image by: Evaluating the variable from the stack Append the Binance Order element to the True path of the Branch element. For the purposes of this tutorial, I am demonstrating the overall process by using a Market Order.
Because of that, I recommend using at least a Limit order. The subsequent element is not triggered if the order was not executed properly e. Therefore, you can assume that if the subsequent element is triggered, the order was placed. Here is an example of output from a successful sell order for XMRBTC: Image by: Successful sell order This behavior makes subsequent steps more comfortable: You can always assume that as long the output is proper, the order was placed.
Therefore, you can append a Basic Operation element that simply writes the output to True and writes this value on the stack to indicate whether the order was placed or not. If something went wrong, you can find the details in the logging message if logging is enabled. Image by: Logging output from Binance Order element Schedule and sync For regular scheduling and synchronization, prepend the entire workflow in Grid 1 with the Binance Scheduler element.
Image by: Binance Scheduler at position 1A, grid 1 The Binance Scheduler element executes only once, so split the execution path on the end of Grid 1 and force it to re-synchronize itself by passing the output back to the Binance Scheduler element. If you want to take advantage of these low-cost clouds, you can use PythonicDaemon, which runs completely inside the terminal.
Image by: PythonicDaemon console PythonicDaemon is part of the basic installation. To use it, save your complete workflow, transfer it to the remote running system e. When it comes to letting your bot trade with your money, you will definitely think thrice about the code you program.
Setup Before we can begin, we must set up our environment. Sign up for an account. If you have not yet enabled 2FA for your account, you will first need to go through the process of setting up 2FA. Enter your 6-digit verification code and account password. Once you have verified your account, Shrimpy will send you an email that will require you to confirm the creation of the API key. Confirm your email by clicking on the link in the verification email.
After confirming the creation of the API key in your email, you can then see a card that represents your developer API key. The public key will be displayed by default. This can only be done one time, so securely store the secret key once it has been shown. The private key will not be shown by default and can only be viewed ONE time. That means after you view your private key, Shrimpy will never show you the key again.
Copy both the public and private secret keys to secure locations. Do not ever share this API key with anyone. We will use all of the settings for this tutorial guide, however, you can reconfigure your setup once you are ready to deploy your production version of your trading bot. Note: You can create multiple API keys. We don't need to buy any credits to test Shrimpy, but you can purchase credits at any time on the "Payment" tab. This will look something like the screenshot below.
Purchase credits when ready. Before credits can be purchased, we first require you to link a payment method. After linking a payment method, you can enter the value of the credits you wish to purchase. Setting Up Our Python Environment There are a few things we will need to set up for our Python environment before we can start coding.
First, start by installing the Shrimpy Python Library. These libraries are Pandas and Plotly. If you are using Python2, please update your version of Python. That is the exchange API keys. These API keys are retrieved from the exchange that you want to use for trading.
With the Shrimpy personal plan, you can connect to 20 different exchange accounts at one time, but for these examples, we will only connect to one. Log into your exchange account and follow the appropriate tutorial in our list of exchange specific articles here.
These articles will help you get access to your API key and copy them into a secure location. Once the API keys have been copied, you can close out of the article. You do not need to paste them into the Shrimpy portfolio management application since we will only use them for our scripts throughout these example tutorials.
The following examples will include blanks where you will need to input your public and secret API keys for both Shrimpy and the exchange. When you see: Input the exchange specific API keys you generated in previous steps. Collecting Pricing Data One of the most important pieces of information for a bot to decide when to execute a trade is pricing data. Exchange specific pricing data should be used to calculate the optimal trade times, as well as the exact placement of the orders.
Generally, order book data is used to make the specific decisions on where to place an order and trade data can be used to determine when an order should be executed. Simple Price Ticker The simple price ticker is a way to access the latest prices for each asset on an exchange. This value is updated on a 1-minute interval. The purpose of this endpoint is for display purposes only. This endpoint is not designed for order execution or arbitrage.
We provide other endpoints for those purposes. That means there is no delay between the time the trade is executed on the exchange and this price ticker updates. This endpoint is more complex, however, as it will require a websocket connection. As the order book is updated live, you can access a snapshot of this live data to either execute trades, provide information for decision making, or even just analyze the market.
That way your local copy of the order book is never outdated. We only need to connect an exchange account one time. Without this information, we would be guessing at the quantity of funds we have available for each asset. Use this script to access the balances for any exchange account that has been linked to your Shrimpy Developer APIs.
It is important to remember that trading is complex. The examples provided here will be a great starting point, but they are not the finish line.
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