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Buy And Sell Bitcoin

Buy And Sell Bitcoin

Prerequisites: Local development environment If you are building a bitcoin application, chances are, you want your users tohave some bitcoin to be able to use your app. You can use Coinbase APIto help your users buy bitcoin. In this short guide youll learnhow to buy and sell bitcoin programmatically. We will set upvery simple price thresholds to buy or sell bitcoin automatically. First, you need to make sure you have a verified payment method associatedwith your Coinbase account. require 'coinbase/wallet'client = Coinbase::Wallet::Client.new(api_key: , api_secret: , CB_VERSION: 'YYYY-MM-DD')payment_methods = client.payment_methodsputs payment_methods from coinbase.wallet.client import Clientclient = Client(, , api_version='YYYY-MM-DD')payment_methods = client.get_payment_methods() var Client = require('coinbase').Client;var client = new Client({ 'apiKey': 'API KEY', 'apiSecret': 'API SECRET', 'version':'YYYY-MM-DD'});client.getPaymentMethods(function(err, paymentMethods) { console.log(paymentMethods);}); Now that youve confirmed that you can buy and sell bitcoin, lets go ahead and set upsimple price checks that will trigger either a buy or a sell when the price of bitcoincrosses the corresponding threshold: account = client.primary_accountpayment_method = client.payment_methods.firstbuy_price_threshold = 200sell_price_threshold = 500buy_price = client.buy_price({currency: 'USD'})sell_price = client.sell_price({currency: 'USD'})if sell_price.amount.to_f <= sell_price_threshold sell = account.sell({"amount" => "1", "currency" => "BTC", "payment_method" => payment_method.id})endif buy_price.amount.to_f <= buy_price_threshold buy = account.buy({"amount" => "1", "currency" => "BTC", "payment_method" => payment_method.id})end account = client.get_primary_account()payment_met Continue reading >>

Get Latest Bitcoin And Other Crypto-currencies Rates Using Python Django -

Get Latest Bitcoin And Other Crypto-currencies Rates Using Python Django -

Get latest Bitcoin and other crypto-currencies rates using python Django James Howells is trying to dig a landfill site to get 7500 bitcoins that were dumped there in 2013. To be a good investor, it is necessary that you keep track of ups and downs in the market. ' There are multiple platforms where you can track the price of bitcoin. But for a python programmer that is no fun. Being a python programmer we will develop our own project where we can get latest bitcoin and other crypto-currency prices. It is always recommended to use virtual environment for all your python and Django projects. Create a virtual environment using python3 using below command. Install the latest Django version and other required libraries. For now only requests package is required. We will add other packages later if required. This will install Django 2.0 and requests package along with some other package. You can verify the same by running commandpip freeze. (crypto) [email protected]: crypto$ pip freezecertifi==2017.11.5chardet==3.0.4Django==2.0idna==2.6pytz==2017.3requests==2.18.4urllib3==1.22 Once virtual environment has been setup and activated, create a new django project. Go to crypto project directory and list the files. Since we are working on Django 2.0 , we need to take care of few things which we will highlight as we progress. Add this app to the list of installed apps in settings.py file. from django.urls import pathfrom . import viewsapp_name = 'bitcoin'urlpatterns = [ path('', views.index, name="index"),] Django 2.0 Note: Adding app_name in urls.py is require now, otherwise you will get the below error. 'Specifying a namespace in include() without providing an app_name 'django.core.exceptions.ImproperlyConfigured: Specifying a namespace in include() without providing an app_name is n Continue reading >>

A Practical Introduction To Blockchain With Python

A Practical Introduction To Blockchain With Python

Blockchain is arguably one of the most significant and disruptive technologies that came into existence since the inception of the Internet. It's the core technology behind Bitcoin and other crypto-currencies that drew a lot of attention in the last few years. As its core, a blockchain is a distributed database that allows direct transactions between two parties without the need of a central authority. This simple yet powerful concept has great implications for various institutions such as banks, governments and marketplaces, just to name a few. Any business or organization that relies on a centralized database as a core competitive advantage can potentially be disrupted by blockchain technology. Putting aside all the hype around the price of Bitcoin and other cryptocurrencies, the goal of this blog post is to give you a practical introduction to blockchain technology. Sections 1 and 2 cover some core concepts behind blockchain, while section 3 shows how to implement a blockchain using Python. We will also implement 2 web applications to make it easy for end users to interact with our blockchain. Please note that I'm using Bitcoin here as a medium for explaning the more general technology of "Blockchain", and most of the concepts described in this post are applicable to other blockchain use cases and crypto-currencies. Below is an animated gif of the two web apps that we will build in section 3. It all started with a white paper released in 2008 by an unknown person or entity using the name Satoshi Nakamoto. The white paper was titled Bitcoin: A Peer-to-Peer Electronic Cash System and it laid the foundation of what later became known as Blockchain. In the original Bitcoin white paper, Satoshi described how to build a peer-to-peer electronic cash system that allows onli Continue reading >>

Api For Bitcoin Data

Api For Bitcoin Data

This document is a comprehensive guide to using the Quandl API to access our free bitcoin data. If you havent already done so, we recommend reading Quandls general API documentation ; the functionality will be a lot clearer if you do so. Quandl offers free Bitcoin exchange rates for 30+ currencies from a variety of exchanges. Quandls simple API gives access to Bitcoin exchanges and daily Bitcoin values. With numerous software packages, including R and Python, Quandl is the easiest way to find and download historical Bitcoin prices. You can view up to date Bitcoin market data on our Bitcoin Markets page. This page is a tutorial on usage of the API to access Bitcoin data. Accessing Bitcoin data via the API is no different than the mechanism for all data on Quandl. The purpose of this help page is simply to explain the specific nomenclature were using for Bitcoin data. For general help, see API . For packagespecific help, start on the tools page. All Bitcoin codes follow the same format: Australian dollar exchange rate on BTCMarket exchange: Honk Kong dollar exchange rate from MT. Gox: Thai Baht exchange rate from LocalBTC exchange: Additional information is available on our API page . All of Quandls datasets are also available through a number of tools Your email address will not be published. Required fields are marked * Quandl offers a simple API for stock market data downloads. Our daily data feeds deliver end-of-day prices, historical stock fundamental data, harmonized fundamentals, financial ratios, indexes, options and volatility, earnings estimates, analyst ratings, investor sentiment and more. This post describes how our stock market data is organized, and explains how to access it. Data Organization: Time-series vs. Tables Quandl's data products come in many for Continue reading >>

Bitcoin With Python Coinmonks Medium

Bitcoin With Python Coinmonks Medium

In this tutorial, we are going to introduce Bitcoin using Python. We will be using Pythons bitcoin library, conveniently called bitcoin. To get started with Bitcoin using Python, we need, A Computer which can run Python programming environment A basic knowledge of Python or another scripting language Ability to run commands and programs from a command line program Download and install python from Make sure to download the Python 3.x as thats the one we are going to be using in this tutorial. After you finish installing Python, open your command line program and execute below command to install bitcoin python library We will start with a writing a Hello World equivalent of Bitcoin in Python. To write your python, you can need a code or text editor which supports writing in ASCII format. You cannot use MS Word of Wordpad for this. You could use Notepad, but we recommend using Atom Code Editor , a free code editor. Open your favorite editor and type in below code. In this code, we are first importing the bitcoin library. We are then generating a private key using random_key function and we are then displaying the private key on the screen. Save it as a .py file and then open your command line program and run the above program like this. Next we generate a public key. We do this by passing the private key we generated to privtopub function Next, we create a multi-signature bitcoin address. Multi-signature address is an address that is associated with more than one private key. So, we first create 3 public and private keys. We then create a multi-sig by passing the 3 public keys to mk_multisig_script function. Finally, the resulting multi-sig is passed to scriptaddr function to create the multi signature bitcoin address. print(Private Key 1: + my_private_key1) my_public_key Continue reading >>

Ccxt Pypi

Ccxt Pypi

The list above is updated frequently, new crypto markets, altcoin exchanges, bug fixes, API endpoints are introduced and added on a regular basis. See the Manual for details. If you dont find a cryptocurrency exchange market in the list above and/or want another exchange to be added, post or send us a link to it by opening an issue here on GitHub or via email. The library is under MIT license , that means its absolutely free for any developer to build commercial and opensource software on top of it, but use it at your own risk with no warranties, as is. This library is shipped as an all-in-one module implementation with minimalistic dependencies and requirements: `js/ < >`__ in JavaScript `python/ < >`__ in Python (generated from JS) `php/ < >`__ in PHP (generated from JS) You can also clone it into your project directory from ccxt GitHub repository : git clone An alternative way of installing this library into your code is to copy a single file manually into your working directory with language extension appropriate for your environment. JavaScript version of CCXT works both in Node and web browsers. Requires ES6 and async/await syntax support (Node 7.6.0+). When compiling with Webpack and Babel, make sure it is not excluded in your babel-loader config. This library implements full public and private REST APIs for all exchanges. WebSocket and FIX implementations in JavaScript, PHP, Python and other languages coming soon. The ccxt library supports both camelcase notation (preferred in JavaScript) and underscore notation (preferred in Python and PHP), therefore all methods can be called in either notation or coding style in any language. // both of these notations work in JavaScript/Python/PHPexchange.methodName () // camelcase pseudocodeexchange.method_name () // under Continue reading >>

Anyex Pypi

Anyex Pypi

The list above is updated frequently, new crypto markets, altcoin exchanges, bug fixes, API endpoints are introduced and added on a regular basis. See the Manual for details. If you dont find a cryptocurrency exchange market in the list above and/or want another exchange to be added, post or send us a link to it by opening an issue here on GitHub or via email. The library is under MIT license , that means its absolutely free for any developer to build commercial and opensource software on top of it, but use it at your own risk with no warranties, as is. This library is shipped as an all-in-one module implementation with minimalistic dependencies and requirements: `js/ < >`__ in JavaScript `python/ < >`__ in Python (generated from JS) `php/ < >`__ in PHP (generated from JS) You can also clone it into your project directory from anyex GitHub repository : git clone An alternative way of installing this library into your code is to copy a single file manually into your working directory with language extension appropriate for your environment. JavaScript version of anyex works both in Node and web browsers. Requires ES6 and async/await syntax support (Node 7.6.0+). When compiling with Webpack and Babel, make sure it is not excluded in your babel-loader config. This library implements full public and private REST APIs for all exchanges. WebSocket and FIX implementations in JavaScript, PHP, Python and other languages coming soon. The anyex library supports both camelcase notation (preferred in JavaScript) and underscore notation (preferred in Python and PHP), therefore all methods can be called in either notation or coding style in any language. // both of these notations work in JavaScript/Python/PHPexchange.methodName () // camelcase pseudocodeexchange.method_name () // un Continue reading >>

Ccxt Pypi

Ccxt Pypi

The list above is updated frequently, new crypto markets, altcoin exchanges, bug fixes, API endpoints are introduced and added on regular basis. See the Manual for details. If you dont find a cryptocurrency exchange market in the list above and/or want another market to be added, post or send us a link to it by opening an issue here on GitHub or via email. The library is under MIT license, that means its absolutely free for any developer to build commercial and opensource software on top of it, but use it at your own risk with no warranties, as is. Developer team is open to collaboration and available for hiring and outsourcing. If youre interested in integrating this software into an existing project or in developing new opensource and commercial projects we welcome you to read our Public Offer. This library is shipped as a single-file (all-in-one module) implementation with minimalistic dependencies and requirements. The ccxt library can also be used in web browser client-side JavaScript for various purposes. git clone The client-side JavaScript version also requires CryptoJS. Download and unpack CryptoJS into your working directory or clone CryptoJS from GitHub . git clone Finally, add links to CryptoJS components and ccxt to your HTML page code: // print all available markets document.addEventListener ('DOMContentLoaded', () => console.log (ccxt)) The ccxt library consists of a public part and a private part. Anyone can use the public part out-of-the-box immediately after installation. Public APIs open access to public information from all exchange markets without registering user accounts and without having API keys. This library implements full public and private REST APIs for all exchanges. WebSocket and FIX implementations in JavaScript, PHP, Python and other l Continue reading >>

How To Generate Your Very Own Bitcoin Private Key

How To Generate Your Very Own Bitcoin Private Key

How to generate your very own Bitcoin private key How to generate your very own Bitcoin private key In cryptocurrencies, a private key allows a user to gain access to their wallet. The person who holds the private key fully controls the coins in that wallet. For this reason, you should keep it secret. And if you really want to generate the key yourself, it makes sense to generate it in a secure way. Here, I will provide an introduction to private keys and show you how you can generate your own key using various cryptographic functions. I will provide a description of the algorithm and the code in Python. Most of the time you dont. For example, if you use a web wallet like Coinbase or Blockchain.info, they create and manage the private key for you. Its the same for exchanges. Mobile and desktop wallets usually also generate a private key for you, although they might have the option to create a wallet from your own private key. So why generate it anyway? Here are the reasons that I have: You want to make sure that no one knows the key You just want to learn more about cryptography and random number generation (RNG) Formally, a private key for Bitcoin (and many other cryptocurrencies) is a series of 32 bytes. Now, there are many ways to record these bytes. It can be a string of 256 ones and zeros (32 * 8 = 256) or 100 dice rolls. It can be a binary string, Base64 string, a WIF key , mnemonic phrase , or finally, a hex string. For our purposes, we will use a 64 character long hex string. The same private key, written in different formats. Why exactly 32 bytes? Great question! You see, to create a public key from a private one, Bitcoin uses the ECDSA, or Elliptic Curve Digital Signature Algorithm. More specifically, it uses one particular curve called secp256k1. Now, this c Continue reading >>

Analyzing Cryptocurrency Markets Using Python | Hacker News

Analyzing Cryptocurrency Markets Using Python | Hacker News

I think it helps to "step out" with correlation/regression to understand why something may be spurious or why you get the high correlation values that you do. In some cases, there is no logical connection between variables which leads to spurious regression. However, in this case, if you "step out", the reason for the correlation is pretty obvious. There has been a lot of money pouring into crypto recently because most people are speculating on the space as a whole. Bitcoin's price is too high for smaller investors to make a significant amount of money on, but when a big Bitcoin move makes the news, those investors want a piece. They then pour money into the smaller coins, hoping to get a larger return on their investment. All of this is to say that I think this is the opposite of spurious correlation. However, that doesn't make the correlation meaningful in any way. When ETH or BTC jumps and makes the news, the other coins tend to follow because the whole space is speculative right now. This would be more appropriately titled "downloading, cleaning, and plotting cryptocurrency price data using pandas and plotly in a Jupyter notebook." TL DR the analysis is just a couple of time series correlation coefficient heatmaps. That being said this is a great tutorial for people just starting out with data handling and analysis in pandas. It's great how readily available financial data is with cryptocurrencies! As a complement to this post, I've been recently working with Jupyter notebooks to analyze high-frequency trading activity in Bitcoin markets [1]. I've been listening to the GDAX socket since end July, so I have almost a month's worth of tick data (~ 7GB+ gzip compressed JSON data, it surely explodes to ~100 GB after extracting). If somebody is interested to carry out fu Continue reading >>

Ccxt Pypi

Ccxt Pypi

The list above is updated frequently, new crypto markets, altcoin exchanges, bug fixes, API endpoints are introduced and added on regular basis. See the Manual for details. If you dont find a cryptocurrency exchange market in the list above and/or want another exchange to be added, post or send us a link to it by opening an issue here on GitHub or via email. The library is under MIT license , that means its absolutely free for any developer to build commercial and opensource software on top of it, but use it at your own risk with no warranties, as is. Developer team is open to collaboration and available for hiring and outsourcing. If youre interested in integrating this software into an existing project or in developing new opensource and commercial projects we welcome you to read our Public Offer. This library implements full public and private REST APIs for all exchanges. WebSocket and FIX implementations in JavaScript, PHP, Python and other languages coming soon. The ccxt library supports both camelcase notation (preferred in JavaScript) and underscore notation (preferred in Python and PHP), therefore all methods can be called in either notation or coding style in any language. // both of these notations work in JavaScript/Python/PHPexchange.methodName () // camelcase pseudocodeexchange.method_name () // underscore pseudocode 'use strict';var ccxt = require ('ccxt');(() => async function () { let kraken = new ccxt.kraken () let bitfinex = new ccxt.bitfinex ({ verbose: true }) let huobi = new ccxt.huobi () let okcoinusd = new ccxt.okcoinusd ({ apiKey: 'YOUR_PUBLIC_API_KEY', secret: 'YOUR_SECRET_PRIVATE_KEY', }) let krakenMarkets = await kraken.loadMarkets () console.log (kraken.id, krakenMarkets) console.log (bitfinex.id, await bitfinex.loadMarkets ()) console.log ( Continue reading >>

Osint Investigation Based On Gao Report About Firearm Sales In Dark Web + Bitcoin Tracking Withpython

Osint Investigation Based On Gao Report About Firearm Sales In Dark Web + Bitcoin Tracking Withpython

In November, last year, GAO (Government Accountability Office) and ATF (The Bureau of Alcohol, Tobacco, Firearms and Explosives) released report about firearm sales in Internet. Investigation has consisted of covered attempts to purchase a weapon on Surface Web and Dark Web. 2 of 7 attempts on Dark Web were successful. Based on different OSINT techniques, I was trying to find in which marketplace agents bought guns and track the transaction if possible. Spoiler alert I think its not possible. I really encourge you to read whole report, Ive learned a lot of interesting things reading it. If you want to see how real trade in Dark Web looks like, read this article from Sam Biddle. All of 72 tries on Surface Web have ended with agents empty hands. Because of different law obligations, no vendor agreed to sell illegally firearms to covered agents. Lets look what can we gather about Dark Web investigation, which can be helpful in further targeting. ATF Enforcement Efforts and Outcomes of GAO Covert Testing page3 Report states as above, but doesnt point how much time was allocate for each task Surface Web and Dark Web. ATF Enforcement Efforts and Outcomes of GAO Covert Testing page19 First weapon was semi automatic AR-15 and description mentions obliterated serial number and method of shipping. ATF Enforcement Efforts and Outcomes of GAO Covert Testing page20 In this case, we can learn that purchased weapon was Israeli-made and was wrongly advertised. No words about serial number this time. ATF Enforcement Efforts and Outcomes of GAO Covert Testing page19 Of course, there are no names of the markets. Only marketplaces and online auctions are mentioned by word. Having this information, we are sure that agents didnt try to buy firearms on some forums or chans. Also second sente Continue reading >>

Github - Ofek/bit: Bitcoin Made Easy.

Github - Ofek/bit: Bitcoin Made Easy.

Bit is Python's fastest Bitcoin library and was designed from the beginning to feel intuitive, beeffortless to use, and have readable source code. It is heavily inspired by Requests and Keras . Bit is so easy to use, in fact, you can do this: >>> from bit import Key>>>>>> my_key = Key(...)>>> my_key.get_balance('usd')'12.51'>>>>>> # Let's donate!>>> outputs = [>>> # Wikileaks>>> ('1HB5XMLmzFVj8ALj6mfBsbifRoD4miY36v', 0.0035, 'btc'),>>> # Internet Archive>>> ('1Archive1n2C579dMsAu3iC6tWzuQJz8dN', 190, 'jpy'),>>> # The Pirate Bay>>> ('129TQVAroeehD9fZpzK51NdZGQT4TqifbG', 3, 'eur'),>>> # xkcd>>> ('14Tr4HaKkKuC1Lmpr2YMAuYVZRWqAdRTcr', 2.5, 'cad')>>> ]>>>>>> my_key.send(outputs)'9f59f5c6757ec46fdc7440acbeb3920e614c8d1d247ac174eb6781b832710c1c' Here is the transaction . Python's fastest available implementation (100x faster than closest library) Seamless integration with existing server setups First class support for storing data in the blockchain Access to the blockchain (and testnet chain) through multiple APIs for redundancy Optimal transaction fee API, with optional caching Multiple representations of private keys; WIF, PEM, DER, etc. Continue reading >>

Follow The Bitcoin With Python, Blockexplorer And Webhose.io

Follow The Bitcoin With Python, Blockexplorer And Webhose.io

Open source intelligence techniques & commentary Follow the Bitcoin With Python, BlockExplorer and Webhose.io More and more investigations are being conducted on Tor and many of them can also include investigating Bitcoin transactions. The nature of Bitcoin is such that the transactions themselves are designed to be anonymous but there are many other factors that can dictate whether the owner of a Bitcoin wallet is protecting their identity correctly. By performing secondary searches for Bitcoin addresses you can typically find relationships or interesting trails of information that you can follow. In this blog post we are going to develop a tool where we can target a particular Bitcoin address, visualize the transactions flowing in and out of it and then perform secondary dark web searches using Webhose.io to see if we can find hidden services where the bitcoin wallets have been mentioned. We will of course visualize all of this so that we can explore the data when we are finished. First make sure you have Python installed, and then install the requests library: pip install requests. If you are unsure of how to do this then check out the videos on this page under the Setup section. Next head to Webhose.io and request an API access key . You will also require a few Python libraries to be installed. So do the following: Crack open a new Python script, name it bitcoindarkweb.py (you can download the full source here ) and start hammering out the following code: import argparseimport requestsimport networkxwebhose_access_token = "WEBHOSE API TOKEN"blacklist = ["4a6kzlzytb4ksafk.onion","blockchainbdgpzk.onion"]webhose_base_url = "= "/darkFilter?token=%s&format=json&q=" % webhose_access_tokenblock_explorer_url = "= argparse.ArgumentParser(description='Collect and visualize Continue reading >>

Track Bitcoin Prices On A Live Graph With Python

Track Bitcoin Prices On A Live Graph With Python

Track Bitcoin prices on a live graph with Python You will need Python 3+ installed on your machine. Basic knowledge of Python, Flask and JavaScript will be helpful. Graphs and charts are great for representing information in a clear and concise way. They can be used in various apps to show data to users when needed. Quickly changing data can be better represented using realtime graphs and charts as users can quickly see both current and historical data easily. In this tutorial, we will be making use of Pusher Channels , Plotly and Flask to build a simple app for displaying the price of a Bitcoin in a realtime graph and bar chart. Here is what the final app will look like: To follow along properly, basic knowledge of Python, Flask and JavaScript (ES6 syntax) is needed. You will also need to install Python and virtualenv locally. Virtualenv is a tool that helps us create isolated Python environments. This makes it possible for us to install dependencies (like Flask) in an isolated environment, and not pollute our global packages directory. To install virtualenv: As stated earlier, we will be developing using Flask, a web framework for Python. In this step, we will activate a virtual Python environment and install Flask for use in our project. mkdir realtime-graph cd realtime-graph virtualenv .venv source .venv/bin/activate Note: To activate the virtual environment on a Windows machine, you would need to enter the path to the activate file (in .venv/Scripts) in Powershell / command prompt. You can find more info here . We will also need the Requests library. Let us install it now: Pusher is a service that makes it easy for us to supercharge our web and mobile applications with realtime updates. We will be using it primarily for powering the realtime updates to our graphs. Continue reading >>

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