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
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
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
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
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
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