Nandu Singh

Nandu Singh

1596378553

Learn how to build your own Cryptocurrency Trading Bot with Python

If you’ve been in the cryptocurrency market for more than a few days, you probably know the feeling of the market dropping and you feel hopeless in cashing out your portfolio into a stablecoin or Bitcoin.

Instead of panicking, take control of your portfolio by learning how to write powerful scripts which can instantly execute the trades you need to move in and out of positions.

By the end of this tutorial, you will be equipped with tools which allow you to fully automate and control your portfolio without ever logging into your exchange accounts.

This video series will walk you through the process of building each aspect of your own cryptocurrency trading bot.

The Shrimpy Developer APIs are the premier crypto trading APIs in the market. Collect data across 17+ exchanges, thousands of markets, and more. Access historical tick-by-tick trade data, OHLCV candlesticks, and orderbook snapshots.

Execute trades in real-time or use our smart order routing endpoints. Everything is at the tip of your fingers for immediate integration into your products or services.

Installation

pip install shrimpy-python

Quick Start

All requests are synchronous. For a comprehensive API usage guide, please see https://developers.shrimpy.io/docs.

If you would like to use the async/await style similar to our Node.js library, consider using the asyncio python library to wrap the synchronous requests provided here.

import shrimpy

public_key = 'bea8edb348af226...'
secret_key = 'df84c39fb49026dcad9d99...'
client = shrimpy.ShrimpyApiClient(public_key, secret_key)
ticker = client.get_ticker('bittrex')

Public Endpoints

The clients for both the public and authenticated endpoints are identical. Please note that if you attempt to use the authenticated endpoints without keys, it will fail.

supported_exchanges = client.get_supported_exchanges()
exchange_assets = client.get_exchange_assets('bittrex')
trading_pairs = client.get_trading_pairs('bittrex')

Market Data Methods

ticker = client.get_ticker('bittrex')
orderbooks = client.get_orderbooks(
    'bittrex',  # exchange
    'XLM',      # base_symbol
    'BTC',      # quote_symbol
    10          # limit
)
candles = client.get_candles(
    'bittrex',  # exchange
    'XLM',      # base_trading_symbol
    'BTC',      # quote_trading_symbol
    '15m'       # interval
)

Authenticated Endpoints

As mentioned above, please use the provided Shrimpy API keys to access the authenticated endpoints. Endpoints such as user management require the master api key, while endpoints such as trading will work with either a master api key or a user api key.

User Management Methods

users = client.list_users()
user = client.get_user(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8' # user_id
)
create_user_response = client.create_user(
    'mycustomname' # (optional) name
)
user_id = create_user_response['id']
client.name_user(
    'mycustomname' # name
)

User API Keys Methods

public_user_keys = client.get_api_keys(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8' # user_id
)
user_api_keys = client.create_api_keys(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8' # user_id
)
client.delete_api_keys(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',                            # user_id
    '51ac18b7d208f59b3c88acbb1ecefe6ba6be6ea4edc07e7a2450307ddc27ab80' # public_key
)
permissions = client.get_api_key_permissions(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',                            # user_id
    '51ac18b7d208f59b3c88acbb1ecefe6ba6be6ea4edc07e7a2450307ddc27ab80' # public_key
)
client.set_api_key_permissions(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',                             # user_id
    '51ac18b7d208f59b3c88acbb1ecefe6ba6be6ea4edc07e7a2450307ddc27ab80', # public_key
    True,                                                               # enable account methods
    False                                                               # enable trading methods
)

Account Methods

accounts = client.list_accounts(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8' # user_id
)
account = client.get_account(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # exchange_account_id
)
link_account_response = client.link_account(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',                             # user_id
    'binance',                                                          # exchange
    'GOelL5FT6TklPxAzICIQK25aqct52T2lHoKvtcwsFla5sbVXmeePqVJaoXmXI6Qd', # public_key (a.k.a. apiKey)
    'SelUuFq1sF2zGd97Lmfbb4ghITeziKo9IvM5NltjEdffatRN1N5vfHXIU6dsqRQw',  # private_key (a.k.a. secretKey
    'mypassphrase'                                                       # (optional)passphrase - required for exchanges with passphrases like CoinbasePro
)
account_id = link_account_response['id']
client.unlink_account(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    456                                     # account_id
)
ip_addresses = client.get_ip_whitelist_addresses(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8' # user_id
)

Trading Methods

create_trade_response = client.create_trade(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # account_id
    'BTC',                                  # from_symbol
    'ETH',                                  # to_symbol
    '0.01'                                  # amount of from_symbol
)
trade_id = create_trade_response['id']
trade = client.get_trade_status(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # exchange_account_id
    '72dff099-54c0-4a32-b046-5c19d4f55758'  # trade_id
)
active_trades = client.list_active_trades(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # exchange_account_id
)

Balance Methods

balance = client.get_balance(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)
total_balance_history = client.get_total_balance_history(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)

Asset Management Methods

client.rebalance(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)
rebalance_period_hours = client.get_rebalance_period(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)
client.set_rebalance_period(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # account_id
    24                                      # rebalance_period in hours
)
strategy = client.get_strategy(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)
client.set_strategy(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',   # user_id
    123,                                      # account_id
    {
        'isDynamic': False,
        'allocations': [
            { 'symbol': 'BTC', 'percent': '50' },
            { 'symbol': 'ETH', 'percent': '50' }
        ]
    }                                         # strategy
)
client.clear_strategy(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',   # user_id
    123                                       # account_id
)
client.allocate(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8',    # user_id
    123,                                       # account_id
    {
        'isDynamic': False,
        'allocations': [
            { 'symbol': 'USDT', 'percent': '100' }
        ]
    }                                          # strategy
)

Limit Order Methods

place_limit_order_response = client.place_limit_order(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # account_id
    'BTC',                                  # base_symbol
    'ETH',                                  # quote_symbol
    '0.01',                                 # quantity of base_symbol
    '0.026',                                # price
    'SELL',                                 # side
    'IOC',                                  # time_in_force
)
limit_order_id = place_limit_order_response['id']
order = client.get_limit_order_status(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # account_id
    '8c2a9401-eb5b-48eb-9ae2-e9e02c174058'  # order_id
)
orders = client.list_open_orders(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123                                     # account_id
)
order = client.cancel_limit_order(
    '701e0d16-1e9e-42c9-b6a1-4cada1f395b8', # user_id
    123,                                    # account_id
    '8c2a9401-eb5b-48eb-9ae2-e9e02c174058'  # order_id
)

Analytics Methods

backtest_assets = client.get_backtest_assets(
    'kucoin' # exchange
)
backtest_results = client.run_backtest(
    'binance',                                       # exchange
    10,                                              # rebalance_period in hours
    '0.1',                                           # fee in percent
    '2018-05-19T00:00:00.000Z',                      # start_time
    '2018-11-02T00:00:00.000Z',                      # end_time
    '5000',                                          # initial_value in USD
    [
        { 'symbol': "BTC", 'percent': '50' },
        { 'symbol': "ETH", 'percent': '50' }
    ]                                                # allocations
)

Insight Methods

asset_dominance = client.get_asset_dominance()
asset_popularity = client.get_asset_popularity()

Historical Methods

count = client.get_historical_count(
    'trade',
    'Bittrex',
    'LTC',
    'BTC',
    '2019-05-19T01:00:00.000Z',
    '2019-05-20T02:00:00.000Z'
)
instruments = client.get_historical_instruments()
bittrex_instruments = client.get_historical_instruments('Bittrex')
trades = client.get_historical_trades(
    'Bittrex',
    'LTC',
    'BTC',
    '2019-05-19T00:00:00.000Z',
    '2019-05-20T00:00:00.000Z',
    100
)
orderbooks = client.get_historical_orderbooks(
    'Bittrex',
    'LTC',
    'BTC',
    '2019-05-19T00:00:00.000Z',
    '2019-05-20T00:00:00.000Z',
    100
)
candles = client.get_historical_candles(
    'Bittrex',
    'LTC',
    'BTC',
    '2019-05-19T00:00:00.000Z',
    '2019-05-20T00:00:00.000Z',
    100,
    '1m'
)

Management Methods

status = client.get_status()
usage = client.get_usage()

Websocket

Users can access the Shrimpy websocket feed using the ShrimpyWsClient class. A handler must be
passed in on subscription that is responsible for processing incoming messages from the websocket
stream. It is recommended that you simply send the message to another processing thread from your custom
handler to prevent blocking the incoming message stream.

The client handles pings to the Shrimpy server based on the API Documentation

import shrimpy


public_key = '6d73c2464a71b94a81aa7b13d...'
private_key = 'e6238b0de3cdf19c7861f8e8f5d137ce7113ac1e884b191a14bbb2...'

# This is a sample handler, it simply prints the incoming message to the console
def error_handler(err):
    print(err)


# This is a sample handler, it simply prints the incoming message to the console
def handler(msg):
    print(msg)


api_client = shrimpy.ShrimpyApiClient(public_key, private_key)
raw_token = api_client.get_token()
client = shrimpy.ShrimpyWsClient(error_handler, raw_token['token'])

subscribe_data = {
    "type": "subscribe",
    "exchange": "coinbasepro",
    "pair": "ltc-btc",
    "channel": "orderbook"
}

# Start processing the Shrimpy websocket stream!
client.connect()
client.subscribe(subscribe_data, handler)

# Once complete, stop the client
client.disconnect()

Exchange: Binance.com
Github: https://github.com/shrimpy-dev/shrimpy-python
Docs: https://developers.shrimpy.io/docs

#cryptocurrency #bitcoin #blockchain #python

What is GEEK

Buddha Community

Learn how to build your own Cryptocurrency Trading Bot with Python
Sival Alethea

Sival Alethea

1624410000

Create A Twitter Bot With Python

Create a Twitter bot with Python that tweets images or status updates at a set interval. The Python script also scrapes the web for data.

📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=8u-zJVVVhT4&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=14
🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency - For Beginner
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #a twitter bot #a twitter bot with python #bot #bot with python #create a twitter bot with python

Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Sival Alethea

Sival Alethea

1624291780

Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency - For Beginner
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #learn python #learn python for beginners #learn python - full course for beginners [tutorial] #python programmer #concepts in python

Shardul Bhatt

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development