This article continues on the series we started the last time: Solidity smart contract examples, which implement a simplified real-world process.

Here, we’re walking through an example of a simple open auction.

Original Source Code: Solidity Docs

We’ll first lay out the entire smart contract example without the comments for readability and development purposes.

Then we’ll dissect it part by part, analyze it and explain it.

Following this path, we’ll get a hands-on experience with smart contracts, as well as good practices in coding, understanding, and debugging smart contracts.

Smart contract – Simple Open Auction

// SPDX-License-Identifier: GPL-3.0

pragma solidity ^0.8.4; contract SimpleAuction { address payable public beneficiary; uint public auctionEndTime; address public highestBidder; uint public highestBid; mapping(address => uint) pendingReturns; bool ended; event HighestBidIncreased(address bidder, uint amount); event AuctionEnded(address winner, uint amount); error AuctionAlreadyEnded(); error BidNotHighEnough(uint highestBid); error AuctionNotYetEnded(uint timeToAuctionEnd); error AuctionEndAlreadyCalled(); constructor( uint biddingTime, address payable beneficiaryAddress ) { beneficiary = beneficiaryAddress; auctionEndTime = block.timestamp + biddingTime; } function bid() external payable { if (block.timestamp > auctionEndTime) revert AuctionAlreadyEnded(); if (msg.value <= highestBid) revert BidNotHighEnough(highestBid); if (highestBid != 0) { pendingReturns[highestBidder] += highestBid; } highestBidder = msg.sender; highestBid = msg.value; emit HighestBidIncreased(msg.sender, msg.value); } function withdraw() external returns (bool) { uint amount = pendingReturns[msg.sender]; if (amount > 0) { pendingReturns[msg.sender] = 0; if (!payable(msg.sender).send(amount)) { pendingReturns[msg.sender] = amount; return false; } } return true; } function auctionEnd() external { if (block.timestamp < auctionEndTime) revert AuctionNotYetEnded(auctionEndTime - block.timestamp); if (ended) revert AuctionEndAlreadyCalled(); ended = true; emit AuctionEnded(highestBidder, highestBid); beneficiary.transfer(highestBid); }

}

Code breakdown and analysis

// SPDX-License-Identifier: GPL-3.0

Compiles only with Solidity compiler version 0.8.4 and later, but before version 0.9.

Learn More: Layout of a Solidity File

pragma solidity ^0.8.4; contract SimpleAuction {

Parameters of the auction are variables beneficiary and auctionEndTime which we’ll initialize with contract creation arguments while the contract gets created, i.e. in the contract constructor.

Data type for time variables is unsigned integer uint, so that we can represent either absolute Unix timestamps (seconds since 1970-01-01) or time periods in seconds (seconds lapsed from the reference moment we chose).

 address payable public beneficiary; uint public auctionEndTime;

The current state of the auction is reflected in two variables, highestBidder and highestBid.

 address public highestBidder; uint public highestBid;

Previous bids can be withdrawn, that’s why we have mapping data structure to record pendingReturns.

 mapping(address => uint) pendingReturns;

Indicator flag variable for the auction end. By default, the flag is initialized to false; we’ll prevent changing it once it switches to true.

 bool ended;

When changes occur, we want our smart contract to emit the corresponding change events.

 event HighestBidIncreased(address bidder, uint amount); event AuctionEnded(address winner, uint amount);

We’re defining four errors to describe relevant failures. Along with these errors, we’ll also introduce “triple-slash” comments, commonly known as natspec comments. They enable users to see comments when an error is displayed or when users are asked to confirm the transaction.

Learn More: Natspec comments are formally defined in Ethereum Natural Language Specification Format.

 /// The auction has already ended. error AuctionAlreadyEnded(); /// There is already a higher or equal bid. error BidNotHighEnough(uint highestBid); /// The auction has not ended yet, the remaining seconds are displayed. error AuctionNotYetEnded(uint timeToAuctionEnd); /// The function auctionEnd has already been called. error AuctionEndAlreadyCalled();

Initialization of the contract with the contract creation arguments biddingTime and beneficiaryAddress.

 /// Create a simple auction with `biddingTime` /// seconds bidding time on behalf of the /// beneficiary address `beneficiaryAddress`. constructor( uint biddingTime, address payable beneficiaryAddress ) { beneficiary = beneficiaryAddress; auctionEndTime = block.timestamp + biddingTime; }

A bidder bids by sending the currency (paying) to the smart contract representing the beneficiary, hence the bid() function is defined as payable.

Learn More: What is payable in Solidity?

 /// Bid on the auction with the value sent /// together with this transaction. /// The value will only be refunded if the /// auction is not won. function bid() external payable {

The function call reverts if the bidding period ended.

 if (block.timestamp > auctionEndTime) revert AuctionAlreadyEnded();

The function rolls back the transaction to the bidder if the bid does not exceed the highest one.

 if (msg.value <= highestBid) revert BidNotHighEnough(highestBid);

The previous highest bidder was outbid and his bid is added to his previous bids reserved for a refund.

A direct refund is considered a security risk due to the possibility of executing an untrusted contract.

Instead, the bidders (recipients) will withdraw their bids themselves by using withdraw() function below.

 if (highestBid != 0) { pendingReturns[highestBidder] += highestBid; }

The new highest bidder and his bid are recorded; the event HighestBidIncreased is emitted carrying this information pair.

 highestBidder = msg.sender; highestBid = msg.value; emit HighestBidIncreased(msg.sender, msg.value); }

Bidders call the withdraw() function to retrieve the amount they bid.

 /// Withdraw a bid that was overbid. function withdraw() external returns (bool) { uint amount = pendingReturns[msg.sender]; if (amount > 0) {

It is possible to call the withdraw() function again before the send() function returns. That’s the reason why we need to disable multiple sequential withdrawals from the same sender by setting the pending returns for a sender to 0.

 pendingReturns[msg.sender] = 0;

Variable type of msg.sender is not address payable, therefore we need to convert it explicitly by using function payable() as a wrapping function.

If the send() function ends with an error, we’ll just reset the pending amount and return false.

 if (!payable(msg.sender).send(amount)) { // No need to call throw here, just reset the amount owing pendingReturns[msg.sender] = amount; return false; } } return true; }

The auctionEnd() function ends the auction and sends the highest bid to the beneficiary.

The official Solidity documentation recommends dividing the interacting functions into three functional parts:

• checking the conditions,
• performing the actions, and
• interacting with other contracts.

Otherwise, by combining these parts rather than keeping them separated, more than one calling contract could try and modify the state of the called contract and change the called contract’s state.

 /// End the auction and send the highest bid /// to the beneficiary. function auctionEnd() external {

Checking the conditions…

 if (block.timestamp < auctionEndTime) revert AuctionNotYetEnded(auctionEndTime - block.timestamp); if (ended) revert AuctionEndAlreadyCalled();

…performing the actions…

 ended = true; emit AuctionEnded(highestBidder, highestBid);

…and interacting with other contracts.

 beneficiary.transfer(highestBid); }

}

Our smart contract example is a simple, but a powerful one, enabling us to bid an amount of currency to the beneficiary.

When the contract instantiates via its constructor, it sets the auction end time and its beneficiary, i.e. beneficiary address.

The contract has three simple features, implemented via dedicated functions: bidding, withdrawing the bids and ending the auction.

A new bid is accepted only if its amount is strictly larger than the current highest bid. A new bid acceptance means that the current highest bid is added to the bidder’s balance for later withdrawal. The new highest bidder becomes the current highest bidder and the new highest bid becomes the current highest bid.

Bid withdrawing returns all summed previous bids to each bidder (mapping pendingReturns).

Contract Test Scenario

Open auction duration (in seconds): 240

Beneficiary: 0x5B38Da6a701c568545dCfcB03FcB875f56beddC4

Testing/demonstration steps:

1. Account 0xAb8483F64d9C6d1EcF9b849Ae677dD3315835cb2 bids 10 Wei;
2. Account 0x4B20993Bc481177ec7E8f571ceCaE8A9e22C02db bids 25 Wei;
3. Account 0x78731D3Ca6b7E34aC0F824c42a7cC18A495cabaB bids 25 Wei (rejected);
4. Account 0x617F2E2fD72FD9D5503197092aC168c91465E7f2 bids 35 Wei;
5. Account 0xAb8483F64d9C6d1EcF9b849Ae677dD3315835cb2 bids 40 Wei + initiates premature auction end;
6. Account 0xAb8483F64d9C6d1EcF9b849Ae677dD3315835cb2 withdraws his bids;
7. Account 0x4B20993Bc481177ec7E8f571ceCaE8A9e22C02db withdraws his bids;
8. Account 0x78731D3Ca6b7E34aC0F824c42a7cC18A495cabaB withdraws his bids;
9. Account 0x78731D3Ca6b7E34aC0F824c42a7cC18A495cabaB initiates timely auction end;
10. Account 0x617F2E2fD72FD9D5503197092aC168c91465E7f2 withdraws his bids;

Appendix – The Contract Arguments

In this section is additional information for running the contract. We should expect that our example accounts may change with each refresh/reload of Remix.

Our contract creation arguments are the open auction duration (in seconds) and the beneficiary address (copy this line when deploying the example):

300, 0x5B38Da6a701c568545dCfcB03FcB875f56beddC4

Info: we could’ve used any amount of time, but I went with 300 seconds to timely simulate both a rejected attempt of ending the auction and the successful ending of the auction.

Conclusion

We continued our smart contract example series with this article that implements a simple open auction.

First, we laid out clean source code (without any comments) for readability purposes. Omitting the comments is not recommended, but we love living on the edge – and trying to be funny!

Second, we dissected the code, analyzed it, and explained each possibly non-trivial segment. Just because we’re terrific, safe players who never risk it and do everything by the book

Programmer Humor – Blockchain

PHP has a core function session_destroy() to clear all the session values. It is a simple no-argument function that returns a boolean true or false.

The PHP session ID is stored in a cookie by default. Generally that session cookie file is name PHPSESSID. The session_destroy function will not unset the session id in the cookie.

To destroy the session ‘completely’, the session ID must also be unset.

This quick example uses session_destroy() to destroy the session. It uses the set_cookie() method to kill the entirety by expiring the PHP session ID.

<?php

// Always remember to initialize the session,

// even before attempting to destroy it. // Destroy all the session variables.

$_SESSION = array(); // delete the session cookie also to destroy the session

if (ini_get("session.use_cookies")) { $cookieParam = session_get_cookie_params(); setcookie(session_name(), '', time() - 42000, $cookieParam["path"], $cookieParam["domain"], $cookieParam["secure"], $cookieParam["httponly"]);

} // as a last step, destroy the session.

session_destroy();

Note:

1. Use session_start() to reinitiate the session after the PHP session destroy.
2. Use PHP $_SESSION to unset a particular session variable. For an older PHP version, use session_unset().

About this login session_destroy() example

Let’s create a login example code to use PHP session, session_destroy and all. It allows users to login and logout from the current session. Use this code if you are looking for a complete user registration and login in PHP script.

This example provides an automatic login session expiry feature.

Landing page with a login form

This form posts the username and the password entered by the user. It verifies the login credentials in PHP.

On successful login, it stores the logged-in state into a PHP session. It sets the expiry time to 30 minutes from the last login time.

It stores the last login time and the expiry time into the PHP session. These two session variables are used to expire the session automatically.

login.php

<?php

session_start();

$expirtyMinutes = 1;

?>

<html>

<head>

<title>PHP Session Destroy after 30 Minutes</title>

<link rel='stylesheet' href='style.css' type='text/css' />

<link rel='stylesheet' href='form.css' type='text/css' />

</head>

<body> <div class="phppot-container"> <h1>Login</h1> <form name="login-form" method="post"> <table> <tr> <td>Username</td> <td><input type="text" name="username"></td> </tr> <tr> <td>Password</td> <td><input type="password" name="password"></td> </tr> <tr> <td><input type="submit" value="Sign in" name="submit"></td> </tr> </table> </form>

<?php

if (isset($_POST['submit'])) { $usernameRef = "admin"; $passwordRef = "test"; $username = $_POST['username']; $password = $_POST['password']; // here in this example code focus is session destroy / expiry only // refer for registration and login code https://phppot.com/php/user-registration...-download/ if ($usernameRef == $username && $passwordRef == $password) { $_SESSION['login-user'] = $username; // login time is stored as reference $_SESSION['ref-time'] = time(); // Storing the logged in time. // Expiring session in 30 minutes from the login time. // See this is 30 minutes from login time. It is not 'last active time'. // If you want to expire after last active time, then this time needs // to be updated after every use of the system. // you can adjust $expirtyMinutes as per your need // for testing this code, change it to 1, so that the session // will expire in one minute // set the expiry time and $_SESSION['expiry-time'] = time() + ($expirtyMinutes * 60); // redirect to home // do not include home page, it should be a redirect header('Location: home.php'); } else { echo "Wrong username or password. Try again!"; }

}

?>

</div>

</body>

</html>

Dashboard validates PHP login session and displays login, and logout links

This is the target page redirected after login. It shows the logout link if the logged-in session exists.

Once timeout, it calls the destroy-session.php code to destroy all the sessions.

If the 30 minutes expiry time is reached or the session is empty, it asks the user to log in.

home.php

<?php

session_start();

?>

<html>

<head>

<title>PHP Session Destroy after 30 Minutes</title>

<link rel='stylesheet' href='style.css' type='text/css' />

<link rel='stylesheet' href='form.css' type='text/css' />

</head>

<body> <div class="phppot-container">

<?php

if (! isset($_SESSION['login-user'])) { echo "Login again!<br><br>"; echo "<a href='login.php'>Login</a>";

} else { $currentTime = time(); if ($currentTime > $_SESSION['expiry-time']) { require_once __DIR__ . '/destroy-session.php'; echo "Session expired!<br><br><a href='login.php'>Login</a>"; } else { ?> <h1>Welcome <?php echo $_SESSION['login-user'];?>!</h1> <a href='logout.php'>Log out</a>

<?php }

}

?>

</div>

</body>

</html>

This PHP code is used for users who want to log out before the session expiry time.

It destroys the session by requiring the destroy-session.php code. Then, it redirects the user to the login page.

logout.php

<?php

session_start();

require_once __DIR__ . '/destroy-session.php';

header('Location: login.php');

?>

I hope this example helps to understand how to destroy PHP sessions. And also, this is a perfect scenario that is suitable for explaining the need of destroying the session.
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Problem Formulation and Solution Overview

This article will show you how to find the most common element in a Pandas Column.

To make it more interesting, we have the following running scenario:

You have been provided with a downloadable CSV file containing crime statistics for the San Diego area, including their respective NCIC Crime Codes.

Question: How would you determine the most common NCIC Crime Code that occurs in San Diego’s jurisdiction?

We can accomplish this task by one of the following options:

• Method 1: Use Pandas mode()
• Method 2: Use Pandas value_counts()
• Method 3: Use value_counts() and idxmax()
• Method 4: Use value_counts() and keys()
• Method 5: Use Pandas groupby()

Preparation

Before moving forward, please ensure the Pandas library is installed. Click here if you require instructions.

Then, add the following code to the top of each script. This snippet will allow the code in this article to run error-free.

import pandas as pd

After importing the Pandas library, this library is referenced by calling the shortcode (pd).

Method 1: Use Pandas mode()

This example uses the mode() method to determine the single most common crime committed in San Diego on a given day.

df = pd.read_csv('crimes.csv', usecols=['crimedescr'])

max_crime = df['crimedescr'].mode()

print(max_crime)

The above code reads in the crimedescr column from the crimes.csv file downloaded earlier. This saves to the DataFrame df.

Next, the crimedescr column is then accessed, and the mode() method is appended. This method returns a value or set of values that appear most often along a selected axis. The results save to max_crime.

These results are output to the terminal.

So, out of 7,854 rows of crimes committed on a given day for San Diego, the above offense was committed the highest number of times.

The above code only provides us with the name of the most common crime; what if we need the crime name and the respective count?

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code'])

max_crime = df['crimedescr'].mode()

max_count = df['ucr_ncic_code'].mode() print(max_crime)

print(max_count)

The above code is output to the terminal and displays the following.

Now, you are equipped to return to your boss and tell them that 7,000 offenses of 10851 (A) VC TAKE VEH W/O OWNER occurred on a given day in San Diego.

Method 2: Use value_counts()

This example uses the value_counts() function to determine the top 5 most common crimes committed in San Diego on a given day.

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code'])

top5_names = df['crimedescr'].value_counts()[:5].index.tolist()

print(top5_names)

The above code reads in the crimedescr and ucr_ncic_code columns from the crimes.csv file downloaded earlier. This saves to the DataFrame df.

Then, the crimedescr column is accessed, and the value_counts() function is appended. This function returns a series containing the counts of unique values.

However, since slicing is also appended ([:5]), only the top five (5) common crimes are retrieved and then converted to a List. The results save to top5_names.

The above code only provides us with the names of the top 5 most common crimes; what if we need the names and their respective counts?

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code'])

top5 = df['crimedescr'].value_counts()[:5].sort_values(ascending=False)

print(top5)

The above output is sent to the terminal.

A cleaner way to achieve the same results is to use the following code.

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code'])

top5 = df['crimedescr'].value_counts().nlargest(5)

print(top5)

The above code calls the nlargest() method to determine and retrieve the top five (5) common crimes. The output is identical to the above.

A much cleaner and more precise output to send to the boss!

Method 3: Use value_counts() and idxmax()

This example uses value_counts() and idxmax() to determine the single most common crime committed in San Diego on a given day.

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code'])

max_crime = df['crimedescr'].value_counts().idxmax()

print(max_crime)

The above code reads in the crimedescr and ucr_ncic_code columns from the crimes.csv file downloaded earlier. This saves to the DataFrame df.

Then, the crimedescr column is accessed, and the value_counts() function is appended. This function returns a series containing the count of unique values.

Next, idxmax() is appended. This method returns the index of the first occurrence of the maximum index(es) over a selected axis.

The results save to max_crime and are output to the terminal.

Method 4: Use value_counts() and keys()

This example uses value_counts() and keys() to determine the top 5 most common crimes committed in unique grid areas of San Diego on a given day.

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'grid', 'ucr_ncic_code'])

top5_grids = df['grid'].value_counts().keys()[:5]

print(top5_grids)

The above code reads in the crimedescr, grid, and the ucr_ncic_code columns from the crimes.csv file downloaded earlier. This saves to the DataFrame df.

Let’s break the highlighted line down.

If df['grid'].value_counts() was output to the terminal, the following would display (snippet). However, we have added a heading row to make it more understandable, and only five (5) rows are displayed.

Next, the code keys()[:5] is appended. The final output displays as follows.

Method 5: Use groupby()

This examples uses groupby() to group our data on the Crime Code and displays the totals in descending order.

df = pd.read_csv('crimes.csv', usecols=['crimedescr', 'ucr_ncic_code']) res = (df.groupby(['ucr_ncic_code','crimedescr']).size() .sort_values(ascending=False) .reset_index(name='count'))

print(res)

The above code reads in the crimedescr and the ucr_ncic_code columns from the crimes.csv file downloaded earlier. This saves to the DataFrame df.

Next, the groupby() function is called and passed the first argument: df.groupby(['ucr_ncic_code','crimedescr']).size(). If this was output to the terminal at this point, the following would display (snippet).

print(df.groupby(['ucr_ncic_code','crimedescr']).size())

As you can see, the other arguments need to be added to turn this into something usable. Sorting the data in descending order and adding a count column will provide the results we are looking for.

If the original Method 5 code example was output to the terminal, the following would display.

Summary

This article has provided five (5) ways to find the most common element in a Panda Column. These examples should provide you with enough information to select the one that best meets your coding requirements.

Good Luck & Happy Coding!

Programming Humor – Python