This project is the most awaited project in open source community where every user who belongs to Stock Trading always wanted to develop its own software. This project has been developed specifically for Indian Market Stock Trading. It encompasses end to end trading cycle for intraday trading but the design would be such that it can be easily extended for delivery trading. During the lifecycle of this project we will be using most advance technologies but the base code will always be C/C++. Development Methodology: ======================== We use "Incremental Life Cycle Model" along with Cross-Platform Development (Portable). Project Priorities and Assumptions: =================================== 1) Low Latency, High Performance all the time. 2) Wherever choice has to be made between memory and execution speed, we give preference to speed. 3) Every module devloped will be exhaustively tested. How the work Proceed: ===================== Before the beginning of any new project, we should know the "PROBLEM STATEMENT", so here it is "Problem Statement" ------------------- To Build a high performance, low latency, end to end Trading Platform for Indian Stock Market but not limited to which home users should be able use for trading which guarantees (99% of the times) the profit but does not guarantees maximized profit for intraday trading. First Step: ----------- To provide the optimal solution to any problem is "UNDERSTAING THE PROBLEM". To understand the above problem statement you need to really extract the explicit and implcit requirements from the statement. Here is the List of requirements: Explicit: --------- 1) High Performance 2) Low-Latency 3) End-to-End Trading Platform 4) Focus on Indian Stock Market but not limited to it. 5) Guarantees (99% of the times) the profit but does not guarantees maximized profit. 6) Only for Intraday Trading. Implicit: --------- 1) Book Keeping of the order and trade (Order Management System). 2) Availability of Market Data to End-Users on Demand for identifying the stock and placing the order. 3) User Account Management. Might be I missed something please suggest and after reveiw we add it here. Second Step: ------------ To understand the above Explicit/Implicit requirements, you should have the "KNOWLEDGE OF VARIOUS TECHNOLOGIES" and indepth undertstanding of the "PROBLEM DOMAIN" i.e. Stock Market. Once this is achieved we need to architect the solution in terms of Software and Hardware nodes and their integration. Third Step: ----------- To solve the problem statement, the above requirements should be "DECOMPOSED IN MODULES" and map to them with technolgoies/software/hardware used. Below is the list of modules we are able to identify: Modules Included: ================= Core Modules: -------------- 1) Core Libraries 2) Manual Order Entry System 3) Auto Order Entry System 4) Artificial Exchange 5) Algorithmic Trading Platform 6) Smart Order Router 7) Direct Trading Platform (Ooptional) Utility Modules: ---------------- 8) Logger Server 9) HeartBeat Server Technologies Used: ================= Software: --------- We always use freeware, Open Source Softwares or APIs which are the part of GPL, LGPL.xx licence. Any special requirement for building/using the modules will be detailed in specific module. For development, we generally use: ---------------------------------- Windows-7 for Operating System but any other OS ca be used. Our Code is Platform Indepandant. Visual Studio 2013 in built compiler for build or Intel@ Compilers which can be easily integrated with Visual Studio IDE. For real time, we generally use: -------------------------------- Linux-susse 10 or above with real time extensions. gcc 4.4.1 for build. vi editor Hardware: --------- No special requirement for development purpose. For real time use, it depands how much Stock you are interested in and the various configuration of modules. We prefer generally the below configuration for any number of Stock Trading: 256 GB RAM 16 core processor 1 TB of HDD/SDD Programming Languages and other Technologies: --------------------------------------------- C, C++99/c++11, Lua, ZeroMq, nanodbc, Lock-Free Data Structures, Intel TBB, Boost, Google Protobuf, MySql, Python. Fourth Step: ------------ Dcompose each module till it becomes entity to provide the useful functionality. We are going to explain this in each module detailed section. Fifth Step: ------------ We do design/develop/benchmark/unit test/integration testing of the above modules. Sixth Step: ------------ We deploy the delivered software on various hardware nodes as per the deployment architecture and integrate them. Seventh Step: ------------ Observe the behaviour of deployed software on live traffic and cut two branches at this level : 1st branch continue to do incremental development and 2nd branch fix the issues reported which can be later merged with 1st branch for another release. Any suggestions for improvement are most welcome.

BUILD YOUR OWN BLOCKCHAIN: A PYTHON TUTORIAL Download the full Jupyter/iPython notebook from Github here Build Your Own Blockchain – The Basics¶ This tutorial will walk you through the basics of how to build a blockchain from scratch. Focusing on the details of a concrete example will provide a deeper understanding of the strengths and limitations of blockchains. For a higher-level overview, I’d recommend this excellent article from BitsOnBlocks. Transactions, Validation, and updating system state¶ At its core, a blockchain is a distributed database with a set of rules for verifying new additions to the database. We’ll start off by tracking the accounts of two imaginary people: Alice and Bob, who will trade virtual money with each other. We’ll need to create a transaction pool of incoming transactions, validate those transactions, and make them into a block. We’ll be using a hash function to create a ‘fingerprint’ for each of our transactions- this hash function links each of our blocks to each other. To make this easier to use, we’ll define a helper function to wrap the python hash function that we’re using. In [1]: import hashlib, json, sys def hashMe(msg=""): # For convenience, this is a helper function that wraps our hashing algorithm if type(msg)!=str: msg = json.dumps(msg,sort_keys=True) # If we don't sort keys, we can't guarantee repeatability! if sys.version_info.major == 2: return unicode(hashlib.sha256(msg).hexdigest(),'utf-8') else: return hashlib.sha256(str(msg).encode('utf-8')).hexdigest() Next, we want to create a function to generate exchanges between Alice and Bob. We’ll indicate withdrawals with negative numbers, and deposits with positive numbers. We’ll construct our transactions to always be between the two users of our system, and make sure that the deposit is the same magnitude as the withdrawal- i.e. that we’re neither creating nor destroying money. In [2]: import random random.seed(0) def makeTransaction(maxValue=3): # This will create valid transactions in the range of (1,maxValue) sign = int(random.getrandbits(1))*2 - 1 # This will randomly choose -1 or 1 amount = random.randint(1,maxValue) alicePays = sign * amount bobPays = -1 * alicePays # By construction, this will always return transactions that respect the conservation of tokens. # However, note that we have not done anything to check whether these overdraft an account return {u'Alice':alicePays,u'Bob':bobPays} Now let’s create a large set of transactions, then chunk them into blocks. In [3]: txnBuffer = [makeTransaction() for i in range(30)] Next step: making our very own blocks! We’ll take the first k transactions from the transaction buffer, and turn them into a block. Before we do that, we need to define a method for checking the valididty of the transactions we’ve pulled into the block. For bitcoin, the validation function checks that the input values are valid unspent transaction outputs (UTXOs), that the outputs of the transaction are no greater than the input, and that the keys used for the signatures are valid. In Ethereum, the validation function checks that the smart contracts were faithfully executed and respect gas limits. No worries, though- we don’t have to build a system that complicated. We’ll define our own, very simple set of rules which make sense for a basic token system: The sum of deposits and withdrawals must be 0 (tokens are neither created nor destroyed) A user’s account must have sufficient funds to cover any withdrawals If either of these conditions are violated, we’ll reject the transaction. In [4]: def updateState(txn, state): # Inputs: txn, state: dictionaries keyed with account names, holding numeric values for transfer amount (txn) or account balance (state) # Returns: Updated state, with additional users added to state if necessary # NOTE: This does not not validate the transaction- just updates the state! # If the transaction is valid, then update the state state = state.copy() # As dictionaries are mutable, let's avoid any confusion by creating a working copy of the data. for key in txn: if key in state.keys(): state[key] += txn[key] else: state[key] = txn[key] return state In [5]: def isValidTxn(txn,state): # Assume that the transaction is a dictionary keyed by account names # Check that the sum of the deposits and withdrawals is 0 if sum(txn.values()) is not 0: return False # Check that the transaction does not cause an overdraft for key in txn.keys(): if key in state.keys(): acctBalance = state[key] else: acctBalance = 0 if (acctBalance + txn[key]) < 0: return False return True Here are a set of sample transactions, some of which are fraudulent- but we can now check their validity! In [6]: state = {u'Alice':5,u'Bob':5} print(isValidTxn({u'Alice': -3, u'Bob': 3},state)) # Basic transaction- this works great! print(isValidTxn({u'Alice': -4, u'Bob': 3},state)) # But we can't create or destroy tokens! print(isValidTxn({u'Alice': -6, u'Bob': 6},state)) # We also can't overdraft our account. print(isValidTxn({u'Alice': -4, u'Bob': 2,'Lisa':2},state)) # Creating new users is valid print(isValidTxn({u'Alice': -4, u'Bob': 3,'Lisa':2},state)) # But the same rules still apply! True False False True False Each block contains a batch of transactions, a reference to the hash of the previous block (if block number is greater than 1), and a hash of its contents and the header Building the Blockchain: From Transactions to Blocks¶ We’re ready to start making our blockchain! Right now, there’s nothing on the blockchain, but we can get things started by defining the ‘genesis block’ (the first block in the system). Because the genesis block isn’t linked to any prior block, it gets treated a bit differently, and we can arbitrarily set the system state. In our case, we’ll create accounts for our two users (Alice and Bob) and give them 50 coins each. In [7]: state = {u'Alice':50, u'Bob':50} # Define the initial state genesisBlockTxns = [state] genesisBlockContents = {u'blockNumber':0,u'parentHash':None,u'txnCount':1,u'txns':genesisBlockTxns} genesisHash = hashMe( genesisBlockContents ) genesisBlock = {u'hash':genesisHash,u'contents':genesisBlockContents} genesisBlockStr = json.dumps(genesisBlock, sort_keys=True) Great! This becomes the first element from which everything else will be linked. In [8]: chain = [genesisBlock] For each block, we want to collect a set of transactions, create a header, hash it, and add it to the chain In [9]: def makeBlock(txns,chain): parentBlock = chain[-1] parentHash = parentBlock[u'hash'] blockNumber = parentBlock[u'contents'][u'blockNumber'] + 1 txnCount = len(txns) blockContents = {u'blockNumber':blockNumber,u'parentHash':parentHash, u'txnCount':len(txns),'txns':txns} blockHash = hashMe( blockContents ) block = {u'hash':blockHash,u'contents':blockContents} return block Let’s use this to process our transaction buffer into a set of blocks: In [10]: blockSizeLimit = 5 # Arbitrary number of transactions per block- # this is chosen by the block miner, and can vary between blocks! while len(txnBuffer) > 0: bufferStartSize = len(txnBuffer) ## Gather a set of valid transactions for inclusion txnList = [] while (len(txnBuffer) > 0) & (len(txnList) < blockSizeLimit): newTxn = txnBuffer.pop() validTxn = isValidTxn(newTxn,state) # This will return False if txn is invalid if validTxn: # If we got a valid state, not 'False' txnList.append(newTxn) state = updateState(newTxn,state) else: print("ignored transaction") sys.stdout.flush() continue # This was an invalid transaction; ignore it and move on ## Make a block myBlock = makeBlock(txnList,chain) chain.append(myBlock) In [11]: chain[0] Out[11]: {'contents': {'blockNumber': 0, 'parentHash': None, 'txnCount': 1, 'txns': [{'Alice': 50, 'Bob': 50}]}, 'hash': '7c88a4312054f89a2b73b04989cd9b9e1ae437e1048f89fbb4e18a08479de507'} In [12]: chain[1] Out[12]: {'contents': {'blockNumber': 1, 'parentHash': '7c88a4312054f89a2b73b04989cd9b9e1ae437e1048f89fbb4e18a08479de507', 'txnCount': 5, 'txns': [{'Alice': 3, 'Bob': -3}, {'Alice': -1, 'Bob': 1}, {'Alice': 3, 'Bob': -3}, {'Alice': -2, 'Bob': 2}, {'Alice': 3, 'Bob': -3}]}, 'hash': '7a91fc8206c5351293fd11200b33b7192e87fad6545504068a51aba868bc6f72'} As expected, the genesis block includes an invalid transaction which initiates account balances (creating tokens out of thin air). The hash of the parent block is referenced in the child block, which contains a set of new transactions which affect system state. We can now see the state of the system, updated to include the transactions: In [13]: state Out[13]: {'Alice': 72, 'Bob': 28} Checking Chain Validity¶ Now that we know how to create new blocks and link them together into a chain, let’s define functions to check that new blocks are valid- and that the whole chain is valid. On a blockchain network, this becomes important in two ways: When we initially set up our node, we will download the full blockchain history. After downloading the chain, we would need to run through the blockchain to compute the state of the system. To protect against somebody inserting invalid transactions in the initial chain, we need to check the validity of the entire chain in this initial download. Once our node is synced with the network (has an up-to-date copy of the blockchain and a representation of system state) it will need to check the validity of new blocks that are broadcast to the network. We will need three functions to facilitate in this: checkBlockHash: A simple helper function that makes sure that the block contents match the hash checkBlockValidity: Checks the validity of a block, given its parent and the current system state. We want this to return the updated state if the block is valid, and raise an error otherwise. checkChain: Check the validity of the entire chain, and compute the system state beginning at the genesis block. This will return the system state if the chain is valid, and raise an error otherwise. In [14]: def checkBlockHash(block): # Raise an exception if the hash does not match the block contents expectedHash = hashMe( block['contents'] ) if block['hash']!=expectedHash: raise Exception('Hash does not match contents of block %s'% block['contents']['blockNumber']) return In [15]: def checkBlockValidity(block,parent,state): # We want to check the following conditions: # - Each of the transactions are valid updates to the system state # - Block hash is valid for the block contents # - Block number increments the parent block number by 1 # - Accurately references the parent block's hash parentNumber = parent['contents']['blockNumber'] parentHash = parent['hash'] blockNumber = block['contents']['blockNumber'] # Check transaction validity; throw an error if an invalid transaction was found. for txn in block['contents']['txns']: if isValidTxn(txn,state): state = updateState(txn,state) else: raise Exception('Invalid transaction in block %s: %s'%(blockNumber,txn)) checkBlockHash(block) # Check hash integrity; raises error if inaccurate if blockNumber!=(parentNumber+1): raise Exception('Hash does not match contents of block %s'%blockNumber) if block['contents']['parentHash'] != parentHash: raise Exception('Parent hash not accurate at block %s'%blockNumber) return state In [16]: def checkChain(chain): # Work through the chain from the genesis block (which gets special treatment), # checking that all transactions are internally valid, # that the transactions do not cause an overdraft, # and that the blocks are linked by their hashes. # This returns the state as a dictionary of accounts and balances, # or returns False if an error was detected ## Data input processing: Make sure that our chain is a list of dicts if type(chain)==str: try: chain = json.loads(chain) assert( type(chain)==list) except: # This is a catch-all, admittedly crude return False elif type(chain)!=list: return False state = {} ## Prime the pump by checking the genesis block # We want to check the following conditions: # - Each of the transactions are valid updates to the system state # - Block hash is valid for the block contents for txn in chain[0]['contents']['txns']: state = updateState(txn,state) checkBlockHash(chain[0]) parent = chain[0] ## Checking subsequent blocks: These additionally need to check # - the reference to the parent block's hash # - the validity of the block number for block in chain[1:]: state = checkBlockValidity(block,parent,state) parent = block return state We can now check the validity of the state: In [17]: checkChain(chain) Out[17]: {'Alice': 72, 'Bob': 28} And even if we are loading the chain from a text file, e.g. from backup or loading it for the first time, we can check the integrity of the chain and create the current state: In [18]: chainAsText = json.dumps(chain,sort_keys=True) checkChain(chainAsText) Out[18]: {'Alice': 72, 'Bob': 28} Putting it together: The final Blockchain Architecture¶ In an actual blockchain network, new nodes would download a copy of the blockchain and verify it (as we just did above), then announce their presence on the peer-to-peer network and start listening for transactions. Bundling transactions into a block, they then pass their proposed block on to other nodes. We’ve seen how to verify a copy of the blockchain, and how to bundle transactions into a block. If we recieve a block from somewhere else, verifying it and adding it to our blockchain is easy. Let’s say that the following code runs on Node A, which mines the block: In [19]: import copy nodeBchain = copy.copy(chain) nodeBtxns = [makeTransaction() for i in range(5)] newBlock = makeBlock(nodeBtxns,nodeBchain) Now assume that the newBlock is transmitted to our node, and we want to check it and update our state if it is a valid block: In [20]: print("Blockchain on Node A is currently %s blocks long"%len(chain)) try: print("New Block Received; checking validity...") state = checkBlockValidity(newBlock,chain[-1],state) # Update the state- this will throw an error if the block is invalid! chain.append(newBlock) except: print("Invalid block; ignoring and waiting for the next block...") print("Blockchain on Node A is now %s blocks long"%len(chain)) Blockchain on Node A is currently 7 blocks long New Block Received; checking validity... Blockchain on Node A is now 8 blocks long

Maps are everywhere around us: in our cars, on our phones, and driving public health initiatives. Geospatial skills and knowledge are increasingly sought after in industry, and will continue to prove vital to Data Science. You will learn how to create maps and analyze spatial data using Python and SQL, how spatial data are applied in a variety of domains, and have hands-on experiences with real data. Together, we will answer questions such as: (1) what are maps, (2) how can we create maps from data, (3) and how do we quantify and analyze maps. Applied geospatial projects will include: autonomous vehicles, public health, supply chain, and more.

David Aplin Group, one of Canada's Best Managed Companies, has partnered with our client to recruit Junior Software Developers. New graduates or soon-to-graduate students are encouraged to apply! Our client is looking for Junior Software Developers to join their growing team. This position is responsible for the development, evaluation, implementation, and maintenance of new software solutions, including maintenance and development of existing applications. Applications involve data collection, data storage, machine learning, and data visualization. The Role: Designing, coding, and debugging software applications using front-end frameworks and enterprise applications - front-end, back-end, and full-stack development. Performing software analysis, code analysis, requirements analysis, software reviews, identification of code metrics, system risk analysis, software reliability analysis. Providing assistance with installations, system configuration, and third-party system integrations. Providing team members and clients with support and guidance. The Ideal Candidate: A Bachelor's degree or Diploma in Computer Science, Computer Engineering, Information Technology, or a similar field. Experience working with coding languages C#, JavaScript, Angular, React, Python, PHP jQuery, JSON, and Ajax. Solid understanding of web design and development principles. Good planning, analytical, and decision-making skills. A portfolio of web design, applications, and projects you have worked on including projects published on GitHub. Critical-thinking skills. In-depth knowledge of software prototyping and UX design tools. High personal code/development standards (peer testing, unit testing, documentation, etc). Team spirit and a sense of humour are always great. Goal-orientated and deadline-driven. COVID-19 considerations: All employees are currently working from home. Any equipment or materials required for work will be provided by the company via shipment to the employee's home. Company policy will continue to evolve through the COVID-19 pandemic and implement alternative working arrangements to ensure that all our people stay safe. If you are interested in this position and meet the above criteria, please send your resume in confidence directly to Jim Juacalla or Ron Cantiveros at Aplin Information Technology, A Division of David Aplin Group. We thank all applicants; however, only those selected for an interview will be contacted. Apply: https://jobs.aplin.com/job/409253/Junior-Software-Developers-New-Graduates