Reshma Saujani’s words carry a profound truth. If we truly aim to build a society free of structural gaps, encouraging vocations is not enough. We must rethink how technology is introduced, taught, and imagined from childhood onward. The way we frame this field determines who feels invited into it — and who quietly concludes that it is not meant for them.

A Historically Masculinized Industry

For decades, the technology sector has been overwhelmingly male-dominated. Careers in science, engineering, and technology were perceived as spaces beyond women’s reach — not because of a lack of ability, but because of limited access, scarce opportunities, and the absence of visible role models or inclusive narratives.

Over time, this perception became embedded in the cultural imagination. Even today, it continues to shape educational pathways and professional decisions.

The lack of diversity in technology has never been a talent problem. It is, fundamentally, a matter of access and representation.

The Women Who Built the Foundations

In 1815, Ada Lovelace unknowingly began dismantling many of these barriers when she designed the first algorithm intended to be executed by a machine. She was followed by other extraordinary women: Grace Hopper, inventor of the compiler; Ida Rhodes, a key architect of early U.S. government programming systems; and more recently, Katie Bouman, who led the development of the algorithm that made the first image of a black hole possible in 2019.

And yet, despite their foundational contributions, their names rarely echo in public consciousness. In contrast, figures such as Alan Turing, Bill Gates, or Steve Jobs are widely recognized.

This reflection does not diminish their achievements. Rather, it highlights a deeper issue: women have historically been underrepresented not only in the industry itself, but in the cultural story we tell about it.

Without Role Models, There Is No Mirror

Within educational settings, these female pioneers are often mentioned only in passing — if at all. As a result, many girls grow up without examples that allow them to envision themselves in technological spaces. And when you cannot see yourself reflected somewhere, it becomes far more difficult to imagine that you belong there.

According to the European Commission, only 33% of STEM graduates today are women, and in ICT fields that number drops to just 20%. While progress has been made, these figures still reveal a significant gap. Behind the statistics lie deeper forces: access, confidence, and the fundamental sense of belonging.

Technology Is More Than Code

One of the most persistent misconceptions is the reduction of technology to programming alone. In reality, the field encompasses a vast ecosystem of equally essential roles: product design, user research, data analysis, systems architecture, project leadership, strategy, customer experience, and more.

Technology is not built by code alone. It is built by understanding people.

Digital products serve a diverse global population with varied needs, contexts, and lived experiences. When teams are homogeneous, the solutions they create tend to reflect that homogeneity. When perspectives are diverse, the outcomes are more robust, more empathetic, and more inclusive.

Rewriting the Narrative

Overcoming the fear or alienation many feel toward the tech sector is a critical step forward. That fear can only be dismantled through visibility, education, and the normalization of diversity within the industry itself.

Women and girls must understand that technology is not an exclusive domain reserved for a select few. It is a space enriched by multiple perspectives, disciplines, and ways of thinking. The future demands diverse teams, varied roles, and cultures where every individual feels empowered to contribute — and to lead change.

Only then will we continue advancing and designing solutions that genuinely reflect the complexity and needs of our society.

The post Technology Is Gender-Neutral — The Narrative Isn’t appeared first on Capitole.

While the first wave of Web 3.0 discussion focused on decentralization, ownership, and individual empowerment, its real test lies in enterprise adoption. Corporations and large organizations are now exploring how Web 3.0 technologies (blockchain, smart contracts, tokens, and decentralized identity) can be integrated into existing business models to improve efficiency, transparency, and trust.

At the same time, the convergence of this technology with Virtual Reality (VR), Augmented Reality (AR), and spatial computing is opening new possibilities for how businesses visualize data, train employees, interact with customers, and manage digital assets. This article examines how Web 3.0 is being applied in enterprise contexts, highlighting both successful implementations and current challenges.

Web 3.0 in Corporate and Enterprise Environments

Blockchain as Enterprise Infrastructure

In corporate settings, blockchain is increasingly adopted as a shared ledger rather than a purely public or permissionless network. Enterprises often use private blockchains to coordinate data across departments, suppliers, and partners.

Typical use cases include:

• Supply chain traceability

• Secure data sharing between organizations

• Automated compliance and auditing

• Cross-border payments and settlement

By reducing reconciliation costs and manual verification, blockchain enables organizations to operate with higher transparency and lower operational friction between groups or teams.

Smart Contracts and Process Automation

Smart contracts are increasingly used to automate business logic that traditionally requires legal oversight, intermediaries, or manual validation. In enterprise environments, they are applied to areas such as licensing, royalty distribution or service-level agreements.

For example, a smart contract can automatically release payment once delivery conditions are verified, reducing disputes and delays. However, enterprises must carefully design these contracts, as errors in code can have immediate and irreversible consequences.

Smart contracts work best when processes are clearly defined, rule-based, and auditable.

Web 3.0 and Corporate Identity Management

Decentralized Identity in Organizations

Traditional enterprise identity systems rely on centralized directories and credential providers. Web 3.0 introduces decentralized identity (DID) models, allowing employees, partners, and customers to control verifiable credentials without exposing unnecessary personal data.

In corporate environments, this enables:

• Secure access management across platforms

• Reduced identity fraud

• Compliance with data protection regulations

• Cross-company authentication without shared databases

Although adoption is still limited, decentralized identity is particularly promising in regulated industries such as finance, healthcare, and logistics.

Integration with Virtual Reality, Augmented Reality, the Spatial Web and use Of AI

Integration with Virtual Reality, Augmented Reality, and the Spatial Web

The integration of Web 3.0 with VR and AR transforms how enterprises present information and interact with digital environments. Rather than relying on flat dashboards or static reports, organizations can visualize data spatially and contextually.

Key applications include:

• Immersive employee training and simulations

• Virtual collaboration spaces for remote teams

• AR-assisted maintenance and industrial operations

• Spatial visualization of supply chains, factories, or digital twins

Blockchain ensures that digital assets, permissions, and identities within these environments are secure, verifiable, and transferable.

The Role of Artificial Intelligence in Immersive Web 3.0 Environments

Artificial Intelligence plays a critical role in making VR and AR applications usable, scalable, and truly client-centric within Web 3.0 enterprise environments. While blockchain provides trust, ownership, and verifiability, AI acts as the interpretation and orchestration layer that transforms complex data into meaningful experiences.

In immersive environments, AI enables real-time analysis of user behavior, context, and intent. This allows virtual and augmented interfaces to adapt dynamically: highlighting relevant information, filtering unnecessary data, and guiding users through complex systems based on their role, expertise, or objectives. For example, an AI-driven AR interface can prioritize operational data for a technician, strategic insights for a manager, or product features for a customer, all within the same spatial environment.

AI is also essential for managing the cognitive load inherent in immersive systems. By summarizing blockchain data, automating pattern recognition, and generating contextual explanations, AI ensures that users interact with insight rather than raw information. This combination of AI, Web 3.0, and immersive technologies transforms VR and AR from visual tools into intelligent decision-support systems, making them viable for real enterprise use rather than experimental showcases.

Benefits and Trade-Offs in Enterprise Adoption

Enterprise adoption of Web 3.0 has been somewhat sluggish, primarily because large-scale organizational change can be daunting. Nevertheless, early adopters have spent the past few years gathering data to weigh the potential benefits against the risks and drawbacks outlined below

Benefits

• Increased transparency and auditability

• Reduced dependency on intermediaries

• Improved data integrity and trust

• New business models and revenue streams

Counterparts and Risks

• Technical complexity and skills gap

• Legal and regulatory uncertainty

• Scalability and performance limitations

• Cultural resistance within organizations

Conclusion: A Strategic Tool, not a Universal Solution

Web 3.0 offers powerful tools for enterprises, particularly when combined with immersive technologies such as VR and AR. Its true value lies not in replacing existing systems as a whole but in strategically enhancing them where decentralization, transparency, and digital ownership provide measurable benefits.

As corporate adoption continues, successful organizations will be those that approach Web 3.0 pragmatically (experimenting, learning, and integrating gradually) while keeping user experience, compliance, and long-term scalability at the center of their strategy.

Key Takeaways

1. Web 3.0 as Enterprise Infrastructure

Blockchain and smart contracts provide reliable, transparent foundations for cross- organizational collaboration and automation.

2. Immersive Technologies Multiply Value

The integration of Web 3.0 with VR and AR enables spatial visualization, training, and collaboration beyond traditional interfaces.

3. Client-Centric Information is a Competitive Advantage

Decentralized identity and AI-driven personalization allow enterprises to follow information securely and contextually.

4. Success Requires Strategy, Not Hype

Projects succeed when Web 3.0 is adopted incrementally with clear business objectives, not as a full system replacement.

5. Risks Remain Real

Scalability, regulation, and usability continue to challenge enterprise adoption and require careful planning.

If you missed part one of this article, read it here:

Bibliography

https://ethereum.org/es/web3

https://ethereum.org/en/decentralized-identity

https://ethereum.org/en/developers/docs/smart-contracts

https://www.kraken.com/es/learn/what-is-web3

https://www.bitpanda.com/es/academy/que-es-la-web3

https://www.pictet.com/is/en/insights/web-3-0-more-than-just-the-internet

https://www.britannica.com/money/what-is-blockchain

https://www.telefonica.com/en/communication-room/blog/5-web-3-0-applications-and-examples-you-should-know-about/

https://thehyperstack.com/blog/how-web-3-0-will-change-the-way-we-use-the-internet

https://www.researchgate.net/publication/395529812_Web_30_The_Next_Evolution_of_the_Internet

The post Enterprise Web 3.0: From Infrastructure to Immersive Apps appeared first on Capitole.

The internet is constantly evolving, and today’s digital world generates unprecedented volumes of content. However, users have historically lacked ownership over their data and creations. Web 3.0 emerges as a response to this imbalance, proposing a decentralized, user- centric internet in which individuals regain control over their digital identities, assets, and interactions.

The evolution of Internet: Web 1.0 to Web 3.0

Web 1.0: Read-only Internet

Web 1.0, created during the 80s, consisted of static, centralized websites with minimal interaction (usually used by investigators). Users consumed information but had no meaningful way to participate or influence content. Websites functioned as digital brochures, offering limited functionality and no personalization.

Web 2.0: Read-Write, Platform-Owned

The emergence of Web 2.0 in the mid-2000s transformed the internet into a participatory space. Social media platforms, blogs, wikis, and content-sharing services enabled users to create, share, and interact with content on a scale. This change fueled innovation, collaboration, and global connectivity. However, this participation came at a cost. Although users generated most of the content and data, ownership remained centralized. Large platforms stored user data in proprietary databases, monetizing attention, behavior, and personal information through advertising and analytics. The economic value created by users was largely captured by platform owners, reinforcing asymmetrical power structures and raising concerns about privacy, data exploitation, and digital dependency.

Web 3.0: Read-Write-Own

Web 3.0 introduces a new paradigm by embedding ownership directly into the internet’s architecture. Through decentralized networks and blockchain technology, users can hold, transfer, and manage digital assets without relying on centralized authorities. Identities, data, and value are no longer controlled by platforms but by cryptographic mechanisms secured by distributed networks.

This shift enables peer-to-peer interactions governed by transparent rules encoded in software. Users become stakeholders rather than products, and participation is increasingly aligned with ownership and governance rights.

The Infrastructure of Web 3.0

Blockchain as a Trust Layer

At the heart of Web 3.0 lies blockchain technology, which functions as a decentralized trust layer. Instead of relying on databases or institutions, blockchains distribute data across networks of independent nodes. Each transaction or data update is cryptographically verified and recorded in an immutable ledger, ensuring transparency and resistance to manipulation.

This architecture enables trustless systems, where participants do not need to know or trust each other personally. Trust is shifted from institutions to code and consensus mechanisms. As a result, value can be exchanged globally with reduced friction, fewer intermediaries, and greater resilience against censorship or single points of failure.

Smart Contracts and dApps

Smart contracts are self-executing programs stored on the blockchain that automatically enforce agreements when predefined conditions are met. They eliminate the need for manual intervention, reducing costs, delays, and the risk of human error.

Decentralized applications (dApps) build on smart contracts to offer services ranging from finance and gaming to identity management and content distribution. Unlike traditional applications, dApps do not rely on centralized servers. Their logic is transparent, their data is distributed, and their governance can be shared among users.

This model promotes openness and accountability while enabling new forms of collaboration and economic organization.

Decentralized Storage and Edge Computing

Web 3.0 also rethinks how data is stored and accessed. Decentralized storage solutions such as IPFS (Interplanetary File System) distribute encrypted data across multiple nodes rather than concentrating it in centralized data centers. This approach enhances security, reduces vulnerability to outages, and improves data sovereignty.

When combined with edge computing and high-speed networks, decentralized storage supports data-intensive applications such as immersive virtual environments, gaming ecosystems, and AI-driven platforms. Processing data closer to the user reduces latency and enhances performance, making decentralized systems increasingly viable at scale.

Tokens, NFTs and Digital Ownership

Tokens and Value Creation

Tokens are the foundational units of value in Web 3.0 ecosystems. Created through smart contracts, they can represent a wide range of rights and functions, including access to services, participation in governance or claims on real-world assets.

Utility tokens grant access to specific features within a platform, while governance tokens enable holders to vote on protocol upgrades, economic parameters, or strategic decisions.

In some cases, tokens represent tokenized real-world assets, such as art, real estate, or intellectual property, bridging digital and physical economies.

NFTs and Digital Property Rights

Non-fungible tokens (NFTs) take a long-standing challenge of the digital era: proving ownership of unique digital items. Unlike traditional digital files (which can be copied endlessly) NFTs are unique, indivisible and verifiable on the blockchain.

NFTs allow creators to monetize digital art, music, collectibles, and virtual goods while retaining origin and rights. Beyond art, NFTs are increasingly used in gaming, digital identity, licensing and access control, demonstrating that ownership in Web 3.0 extends far beyond speculative markets.

Importantly, NFTs do not store the content itself but rather a verifiable record of ownership and authenticity, reinforcing the distinction between possession and authorship.

Challenges and Open Questions

Despite its promise, Web 3.0 faces significant challenges. Scalability remains a technical problem, as decentralized networks must handle growing volumes of transactions without sacrificing security or decentralization. User experience is another barrier, as wallets, private keys, and cryptographic concepts can be difficult for non-technical users.

Legal and regulatory frameworks are still catching up, particularly regarding digital assets, taxation, and consumer protection. Security risks, including smart contract vulnerabilities and fraud, also highlight the need for better standards and education.

These challenges underscore that Web 3.0 is not a finished product but an evolving ecosystem that will change the world in near future if adoption keeps growing.

Conclusion: Ownership as a WIP (Work in Progress)

Web 3.0 represents a structural redefinition of the internet. By combining blockchain, tokens, NFTs, and decentralized governance, it introduces the technical foundations for verifiable digital ownership and peer-to-peer coordination at a global scale. Rather than eliminating platforms, it rebalances power by embedding ownership and control at the protocol level.

For this reason, organizations should not approach Web 3.0 as an immediate, full replacement of existing architecture. Instead, a progressive and strategic adoption is recommended. This involves gradually integrating selected Web 3.0 components into existing web platforms, prioritizing those areas where the organization has a clear vision ofvalue creation, user evolution, and long-term scalability.

Finally, information becomes as important as how it is owned or secured. Augmented Reality and the Spatial Web represent the next step in this evolution, enabling digital content to be displayed in immersive, three-dimensional environments that adapt dynamically to each user. When combined with decentralized identity, blockchain-based permissions, and AI- driven personalization, these technologies allow information to be structured around the specific context, role and needs of the individual interacting with the platform. The next article will explore how client-centric information architectures, spatial interfaces, and augmented reality redefine user interaction, transforming static web experiences into adaptive, intelligent, and immersive digital spaces. Stay tuned.

Key Takeaways

• Blockchain enables trustless ownership and secure peer-to-peer transactions

• Tokens and NFTs redefine digital property and creator monetization

• Governance shifts from centralized authorities toward community-driven models

• Web 3.0 offers a paradigm shift that currently needs greater adoption.

• Any system developed on the blockchain offers freedom, suitability, and trustless endpoints

Read part 2 of this article here:

Bibliography

• https://ethereum.org/es/web3/

• https://www.kraken.com/es/learn/what-is-web3

• https://www.pictet.com/is/en/insights/web-3-0-more-than-just-the-internet

• https://www.bitpanda.com/es/academy/que-es-la-web3

• https://www.researchgate.net/publication/395529812_Web_30_The_Next_Evolution_of_the_Internet

• https://thehyperstack.com/blog/how-web-3-0-will-change-the-way-we-use-the-internet/

• https://www.britannica.com/money/what-is-blockchain

• https://www.telefonica.com/en/communication-room/blog/5-web-3-0-applications-and-examples-you-should-know-about/

The post Web 3.0: A New Era of Internet Property appeared first on Capitole.

Among the various ERPs on the market, SAP stands out as one of the best options, addressing three key areas directly and effectively:

Business Process Automation

Automating business processes enhances efficiency by eliminating human error and allowing resources to focus on higher-value tasks. In SAP, processes that can be reviewed and automated include the following areas: Finance, Logistics, Human Resources, Production, Procurement, and Sales.

Main advantages of process automation:

• Scalability without a significant cost increase: Organizations can handle a higher transaction volume without adding headcount.

• Traceability and regulatory compliance: Every transaction is recorded in real time, simplifying audits and the generation of regulatory reports.

Quantitative example:

A manufacturing company implemented S/4HANA Cloud with the FI-GL (Financial Accounting – General Ledger) and CO (Controlling) modules, cutting its monthly financial close from two weeks to one—a roughly 50% time reduction.

Intelligent Workflows

SAP’s ERP not only executes processes but continuously improves workflows by applying automation, artificial intelligence, and machine learning to anticipate issues and enhance decision-making. Key modules and services include:

• SAP AI Core
• Smart Business Service
• SAP Predictive Analytics
• SAP Conversational AI

Notable funcionalities:

• Inventory Management: SAP Predictive Analytics analyzes sales history and external variables to forecast demand. Basic intelligent replenishment flow:
• Daily collection of sales and stock data in SAP S/4HANA Public Cloud.
• Predictive model calculates next-period demand.
• If forecast exceeds minimum stock, Smart Business Service issues an alert.
• Automatic creation of a purchase order in SAP MM (Materials Management) sent to the supplier.
• Automatic receipt and registration of goods in SAP WM (Warehouse Management).
• Real-time stock updates.
• Accounts Payable: SAP AI Core detects unusual patterns to suggest automatic invoice reviews.
• Human Resources: SAP Conversational AI implements internal chatbots for payroll, absence, and training inquiries and Smart Business Service applies AI to analyze employee turnover patterns and suggest retention plans.

Real-Time Integration

A cornerstone of SAP ERP implementations is full real-time data availability, offering:

• Complete, transparent visibility: Instant access to KPIs across all areas.
• Efficient cross-department coordination: All departments share the same data and terminology.
• Connection with auxiliary systems (CRM, IoT, external platforms, e-commerce, etc.):
• Integration of supplier and customer data in procurement and sales.
• Synchronization of sensor and production-line data.
• Immediate stock updates.

Furthermore, SAP Business Technology Platform (SAP BTP) serves as an integration and innovation layer, enabling:

• Development of custom business functionalities without altering the core system.
• Connectivity with third-party solutions via APIs or event streams.
• Use of advanced services such as SAP Data Intelligence, SAP Analytics Cloud, and SAP HANA Cloud.

Deployment Options for SAP S/4HANA:

• S/4HANA Public Cloud: Ideal for companies seeking rapid time-to-value and minimal infrastructure management.
• S/4HANA Private Cloud: Recommended for mid-sized companies balancing flexibility with IT control.
• S/4HANA On-Premise: Designed for large enterprises with strict data regulations and internal infrastructure policies.

In all cases, SAP BTP underpins these services as the integration and innovation layer.

Scalability and Total Cost of Ownership (TCO)

Although SAP S/4HANA’s implementation cost may be higher upfront, a 5–7-year TCO analysis shows ROI through productivity gains and operational savings. Key TCO components include:

A comparative table highlights basic features of SAP S/4HANA versus Oracle NetSuite, Microsoft Dynamics 365, and Odoo.

• Licensing:
• SaaS (Public/Private Cloud): Periodic per-user or per-module fees, including basic support and automatic updates.
• On-Premise: Annual fixed licensing fees (per user or module) plus maintenance (around 20% of licensing cost).
• Implementation:
• Consulting services for system configuration, unit testing, data migration, and user training.
• Variable costs based on complexity (number of countries, integrations, legal requirements, etc.).
• Infrastructure
• Public Cloud: Managed by SAP or a cloud provider.
• Private Cloud/On-Premise: On-premises hardware, database licenses, power, and cooling, with renewal every 4–5 years.
• Maintenance and Support:
• SaaS: Included support and automatic updates.
• On-Premise/Private Cloud: Internal IT or partners handle updates under additional contracts.
• Training and Change Management:
• Planning and administering initial and ongoing user training.
• Change-management programs to drive user adoption.
• Savings and Payback:
• Improved operational efficiency.
• Reduced errors and labor costs.
• Enhanced decision-making visibility.

Comparison with competing ERPs

Conclusion

SAP S/4HANA Cloud (in any deployment mode) is more than just a data repository. It enables companies to:

• Slash financial-close times by up to 47% and cut accounting errors by 25%.
• Enhance customer service levels.
• Reduce average inventory by 25% and transportation costs by 20%.
• Anticipate demand and automate replenishment with predictive models.
• Achieve 100% regulatory compliance and avoid penalties.

In short, SAP S/4HANA, together with SAP BTP and a hybrid-cloud strategy, represents one of the most comprehensive, scalable, and future-proof solutions, delivering quantifiable, sustainable long-term ROI.

The post SAP S/4HANA ERP: Scalable Business Solutions for the Future appeared first on Capitole.

As you know, in Capitole we have presence in many different industries. Many of us are in data processing projects, in Data Science / Development /Devops positions and work both on physical servers and on cloud machines in AWS, Azure or other cloud services. For us it is very important to work efficiently and follow good practices in development, leaving a good image of our company wherever we go. This allows us to perform our job the best we can and makes things easier for the end customers of the developed product.

In this article, we share some of the thoughts that we have acquired over time, that are meant to help as tips to organize the code. They are simple tricks that can save a lot of time and misunderstandings in the day-to-day work of the team of developers.

Inline Tests

I know you test your code; otherwise, how do you know it works? But here’s the question: do you keep track of the tests you do? If not, how can others trust your code?

Welcome to the amazing world of unit testing. This is one of those things that might not seem fun at the beginning, but once you’ve experienced long hours wasted debugging code, and then hours saved thanks to testing your code, it magically becomes fun and a must.

I would want to teach you about the assert statement, also known as “inline tests”. These tests are useful to check if the input and output of your functions are correct.

Let me show you an example where this comes in handy. Let’s say you are working with a vector of probabilities, and you want to project to 0 or 1 depending on a threshold. This function is implementing this:

def project_to_zero_or_one(probabilities, threshold):

# define empty array

projections = np.empty_like(probabilities)

# project

projections[probabilities < threshold] = 0

projections[probabilities >= threshold] = 1

return projections

But what if there are nans in your input vector? What if one of the entries is <0 or >1? (remember probabilities are not defined outside the range [0,1]) What if the input is a matrix and not a vector?

I would like the code to tell me if anything like that is happening, meaning there’s something wrong somewhere else I need to fix before it’s too late.

def project_to_zero_or_one(probabilities, threshold):

# check input

assert probabilities.ndim == 1, “Input must be a vector!”

assert np.isnan(probabilities).sum() == 0, “Input contains NaN values!”

assert np.sum(probabilities > 1) == 0, f”There are probabilities > 1!”

assert np.sum(probabilities < 0) == 0, f”There are probabilities < 0!”

# define empty array

projections = np.empty_like(probabilities)

# project

projections[probabilities < threshold] = 0

projections[probabilities >= threshold] = 1

return projections

One practice I like to follow is extracting all assert statements out of the main function. This is particularly useful when you have other functions that use the same argument, such as probabilities, allowing you to reuse the code.

def _check_probabilities(probabilities):

assert probabilities.ndim == 1, ‘Input must be a vector!’

assert np.isnan(probabilities).sum() == 0, ‘Input contains NaN values!’

assert np.sum(probabilities > 1) == 0, ‘There are probabilities > 1!’

assert np.sum(probabilities < 0) == 0, ‘There are probabilities < 0!’

Code formatters and Stylers

You may not realize it yet, but you’ll spend most of your career reading code instead of writing it. Whether you work in a team and review your colleagues’ code, or when you are trying to solve a problem by looking for an answer on StackOverflow, or even when you come back to debug code you wrote months ago. In all those situations, you will be reading a lot of code.

For that reason, it is important to write code in a consistent and uniform way. This includes decisions such as maximum line length, empty lines between function definitions, and syntax conventions like vector[:-1] or vector[: -1]. These may seem like small details, but they have a significant impact on code readability for humans. The big question is, can all these small decisions be automated? Yes, indeed.

• A code formatter is a tool that automatically modifies the layout and style of source code to adhere to a specific set of formatting rules or guidelines. I highly recommend Black.

• On the other hand, a code styler is a tool that assists developers in applying a specific coding style or set of guidelines to their code. While similar to code formatters, code stylers are more flexible and suggest changes to the code instead of modifying it directly. For example, they may suggest renaming variables or removing unused libraries. I highly recommend flake8.

Structuring code as a package

Are you having trouble importing your own Python modules? Does the error ModuleNotFoundError: No module named ‘my_python_file’ look familiar? Have you already experienced the insecurity of knowing if you have installed your modules, where they are located or if you are using the correct path? It might be time to improve your code structure.

Whenever starting a new project, structure your code something like this:

my_project/

├── src/

│ ├── __init__.py

│ ├── my_module.py

│ └── my_folder/

│ ├── __init__.py

│ └── my_other_module.py

├── data/

│ ├── raw/

├── scripts/

│ ├── my_script.py

├── setup.py

└── README.md

A few things to note:

•  When Python imports a package, it looks for the __init__.py file in the package directory and executes any code inside it.
• setup.py is a Python script that is used to define the metadata and dependencies of a Python package. The simplest it can be is:

from setuptools import setup, find_packages

setup(

name=’my_package’,

packages=find_packages(),

)

You can also specify dependencies, authors, versions, etc:

from setuptools import setup, find_packages

setup(

name=’my_package’,

version=’0.1′,

author=’John Doe’,

author_email=’john.doe@example.com’,

description=’A simple Python package’,

packages=find_packages(),

install_requires=[

‘numpy>=1.16.0’,

‘pandas>=0.23.4’,

],

)

Once your folders look like this (and you are in your virtual environment) type pip install -e path/to/my_project/. This will install your package in editable mode. This means that as you change your code your installed package is automatically updated, and you won’t need to reinstall anything.             

Conclusion

In summary, good coding structure and practices not only improve development efficiency, but also facilitate collaboration and long-term code maintenance.

• The practice of testing (in an ordered and consistent manner) is essential to ensure in a reliable and controlled way that the code complies with the defined functionalities correctly.
• The use of code stylizers and formatters are essential habits to homogenize criteria in any development team. The key is to write code that is easily understandable, replicable, and adaptable, which will benefit both you and your teammates and customers.
• Structuring your own code as a package is a good practice that will make it easier to share and publish the code in the future and installing it in editable mode saves a lot of time, as it updates automatically.

Efficiency in code is ultimately efficiency in results.

The post Code Development Tips: Unit tests, code formatters and stylers and structuring code as a package. appeared first on Capitole.

If you have experienced any of these problems, this article is for you.

At Capitole we have presence in many different industries. Many of us are in data processing projects, in Data Science/Development/Devops positions and work both on physical servers and on cloud machines in AWS, Azure or other cloud services. For us it is very important to work efficiently and follow good practices in development, leaving a good image of our company wherever we go. This allows us to perform our job the best we can and makes things easier for the end customers of the developed product.

In this article, we share some of the reflections that we have acquired over time, as tips to organise the code.

They are simple tricks that can save a lot of time and misunderstandings in the day-to-day work of the team of developers.

From Jupyter/Databricks notebooks to scripts

Many of us begin coding in Jupyter notebooks, and I get it—it’s simple, allows you to quickly test new code, experiment with syntax, and easily visualize plots. However, as you become more proficient in Python, it’s important to transition to writing scripts.

Why make the switch? There are many good reasons, but the most important one is that it encourages better code structure. In a script, there are no cells—everything runs sequentially. If you need additional functions, you can write separate scripts and use them as modules (a module is simply a .py file that contains functions and classes for reuse).

So, what is a script?

A script is simply a .py  file designed to execute a specific task or set of tasks. Let me show you the basic structure of a script with an example: analyze.py.

* In short, if __name__ == “__main__”: allows you to execute code when the file runs as a script, but not when it’s imported as a module. To run it as a script simply type python analyze.py in your terminal. To use it as a module, in a new .py file, write import analyze, and you’ll have access to the 3 functions defined without running the code inside the if statement.

Readable Code

Imagine I start writing the following: “goodcodingpractices ARE oneofTHEmost imp

ortant skillssssss      you Will develop                                                                                             as a DataScientist.”

You probably understood what I meant, but you had to do an effort to do so. Bad coding practices are the equivalent of what I just showed in the previous sentence for code, but even worse. I remember at the beginning of my career writing code, so poorly I couldn’t understand it myself. In this section you’ll learn how to write code properly. The main idea here is that your code should be easy to read by anybody (other people and your future self). In my experience, this trait is what differences a beginner from a pro.

Variable Names

“There are only two hard things in Computer Science: cache invalidation and naming things.”

– Phil Karlton

Check the following video to learn how to name variables properly. (These tips also apply to function names).

Functions

I assume you know what a function is and its syntax in Python. The important thing here is how to use them effectively and name them correctly. Functions should be used to structure your code correctly. If your functions are more than 100 lines long, there is probably something wrong. Break them into smaller functions that make sense.

Tips for naming your functions:

1. Descriptive names: The name should describe what the function does in a clear and concise way.
2. Action verbs: Function names should use verbs to indicate what the function does.
3. Use the snake_case naming convention.
4. Avoid abbreviations: Abbreviations can make function names difficult to understand.

Indentation

If you need more than 3 levels of indentation, you should fix your program. You can read the preferred Linux kernel coding style and take it as a reference. This video shows the importance of this point.

Comments

In an ideal world, you wouldn’t need comments. If your variable and function names are concise and self-explanatory, and your program is designed in a way that breaks down into logical functions that are easy to follow, your code should be easily readable, and no comments would be needed.

However, we live in an imperfect world where the best decisions are not always obvious, and where we sometimes have to sacrifice readability for performance. For these reasons, I recommend writing comments. I suggest breaking functions (or code) into small chunks, each accompanied by a comment at the top explaining what you are doing and why.

Virtual Environments

If you’ve been involved in several projects simultaneously without using virtual environments, you know the struggle. Every time you need a library, you simply type pip install <new_library>, and if you now run pip list, you’ll see a huge list of libraries that you don’t even remember installing. The pain is even greater if you work in a team where nobody uses virtual environments or if you are involved in several projects simultaneously: encountering code crashes for no apparent reason, difficulty running code for new team members, and so on.

The solution to these problems is a virtual environment. For Python, I recommend virtualenv. It creates an environment in which you can install libraries completely independent of the rest of your system. To install it, simply run pip install virtualenv, and to learn how to use it, type tldr virtualenv. To remove a virtual environment, simply delete the folder you initially created. Note that the process of activating a virtual environment is slightly different for Windows and Linux.

Remember that you can have as many virtual environments as you want. Don’t be afraid to create and delete environments as needed.

I usually create two for each project: one for development and one for production.

Conclusion

In summary, good coding structure and practices not only improve development efficiency, but also facilitate collaboration and long-term code maintenance. Migrating from notebooks to well-organised scripts, writing clear and concise functions, using descriptive names, and taking advantage of tools such as virtual environments are essential habits for any development team. The key is to write code that is easily understandable, reproducible, and adaptable, which will benefit you, your teammates, and your customers. Efficiency in code is ultimately efficiency in results.

The post Structure, Readability and Efficiency in Code Development appeared first on Capitole.

Security is a fundamental aspect of application development, especially in the context of the imminent European Cyber Resilience Act (CRA). This law will require companies to take security measures throughout the software development lifecycle. Therefore, at Capitole we believe that it is extremely important to adopt measures to protect our applications from the threats that may arise from these third-party dependencies.

This is where Software Composition Analysis (SCA) comes in.

What is SCA?

SCA is a process of identifying and evaluating the security risks associated with software dependencies in our projects. Its goal is to help us obtain an inventory of all third-party components used in our projects. Thanks to this inventory, we can determine which dependencies could be affected by known vulnerabilities, such as those identified in the Common Vulnerabilities Enumeration (CVE) system.

As we mentioned earlier, using third-party components can present several risks, including:

Obsolete components: Not updating our project dependencies can lead to vulnerabilities that have been patched in newer versions.

Known vulnerabilities: Even recent versions may have vulnerabilities that have either not been discovered or have not been patched yet, so it is important to be aware of them to mitigate them.

High-risk components: These are components that have access to sensitive data and are critical to our application’s security. SCA helps us identify these components and take additional security measures to protect them adequately.

Therefore, it is important that we integrate mechanisms into our development cycle that allow us to audit these components that we do not develop ourselves.

How to implement SCA?

To implement Software Composition Analysis (SCA) in our projects, we will rely on the tools provided by OWASP (Open Web Application Security Project). This process consists of three fundamental steps:

Step 1: Analysis

All software dependencies are identified using the previously mentioned inventory or bill of materials (BOM).

Step 2: Identification and Detection

Known vulnerabilities (CVEs) present in those dependencies are detected.Step 3: Mitigation

The recommendations suggested to mitigate the risk associated with these vulnerabilities and prevent their exploitation are followed.

To carry out this process, we will use three OWASP tools, all of which are open source and free:

• OWASP Dependency Check: This tool scans our project for dependencies, compares them to a database of known vulnerabilities, and generates a detailed report that includes the criticality of the vulnerabilities, their description, and possible solutions. To implement this tool in our project, we will download it from https://owasp.org/www-project-dependency-check and run the command at the root of our project. As a result, we will obtain HTML with the analysis results.
• OWASP Cyclone DX: This tool facilitates the generation of our Bill of Materials (BOM), which is essential for analyzing our dependencies. To do this, we will use its repository and choose the version depending on the project in which we want to run it (Node, Python, Maven) https://github.com/CycloneDX When we run the tool, we will obtain a JSON with the list of materials. WASP Cyclone DX: This tool makes it easy for us to generate our bill of materials (BOM), which is essential for analyzing our dependencies.
• OWASP Dependency Track: Finally, this tool provides us with a control panel where we can organize our projects. It feeds on the Bill of Materials (BOM) generated with Cyclone DX to identify our dependencies and manage them effectively. To use Dependency Track, on the one hand we will need a Bill of Materials (which may have been previously generated with CycloneDX) and deploy the docker that they provide us on their website https://docs.dependencytrack.org/getting-started/deploy-docker

These tools that OWASP provides us with are multiplatform tools so we can run them in all types of projects. In addition to identifying vulnerabilities, as NPM audit could do, it also analyzes the age of the components and the software licenses of them, apart from which they can be integrated with tools such as Jenkins and the results of the reports can be generated in different formats.

Recommendations

By following these recommendations, we will be ensuring the security of our project with respect to third-party dependency management:

Use resources from trusted sources: When selecting libraries and frameworks, we must make sure that they come from trusted and maintainable sources. This involves considering aspects such as update times, reputation on platforms like GitHub, and the effective resolution of reported issues. Opting for trusted sources reduces the risk of introducing vulnerabilities into our project from the start.

Keep components updated: It is recommended to perform periodic updates of our components. In this way, we can ensure that we are up to date with security patches and bug fixes, thus mitigating the risk of exploitation of known vulnerabilities.

Conclusion

In conclusion, effective management of third-party dependencies in software is crucial to ensure the security and integrity of our projects. By integrating SCA into the development cycle of these, we can identify and mitigate the risks associated with the use of external components.

Bibliography:

• https://digital-strategy.ec.europa.eu/en/library/cyber-resilience-act
• https://owasp.org/www-community/Component_Analysis
• https://owasp.org/www-project-cyclonedx/
• https://owasp.org/www-project-dependency-check/
• https://owasp.org/www-project-dependency-track/

Alberto Castillo Molina

Senior Back-end Developer at Capitole

The post The Importance of Third-Party Dependency Management in Software Development appeared first on Capitole.

Unleash Your Business Potential with Low-Code Innovation!

In today’s ever-evolving business world, speed and adaptability are not just advantages – they’re necessities. Imagine a game-changing solution that allows your organization to swiftly adapt and automate processes effortlessly. Enter the world of low-code platforms – a revolutionary approach to Business Process Automation (BPA) that ensures efficiency without the need for extensive coding expertise. Let’s explore how this can transform your business!

The Low-Code Revolution

Low-code platforms are swiftly becoming the go-to solution for businesses aiming to streamline and automate processes. The beauty lies in their ability to empower both IT and non-technical users to collaboratively build applications using a visual development interface, slashing development time significantly.

Accelerated Development Cycles

Traditional software development can be time-consuming, causing delays in implementing crucial business processes. Low-code platforms revolutionize this by offering a visual, drag-and-drop interface. This means your team can create applications with minimal coding, resulting in faster deployment and the ability to adapt swiftly to changing market demands.

Increased Efficiency and Productivity

Unlock enhanced efficiency and productivity by automating repetitive and time-consuming tasks. Low-code platforms free up valuable human resources, allowing your team to focus on strategic, creative, and high-value activities. Say goodbye to errors and hello to dedicated time for critical thinking and innovation.

Democratizing Innovation

Low-code platforms break down barriers to innovation. No longer confined to IT experts, users across departments can contribute to the development process, fostering a culture of innovation throughout your organization. Silos crumble as collaboration takes center stage.

Cost-Efficiency and Scalability

Implementing low-code platforms leads to substantial cost savings. With reduced need for specialized coding expertise and faster development cycles, project costs plummet. Additionally, these platforms offer scalability, allowing your business to adapt and grow without hefty resource investments.

Ensuring Future-Proof Operations

In the dynamic business landscape, adaptability is crucial for long-term success. Low-code platforms provide a future-proof solution, enabling businesses to iterate and update applications rapidly. This agility ensures your organization can keep pace with evolving market trends and technology advancements without massive overhauls.

Realizing the Potential: Use Cases and Examples

Let’s delve into real-world examples of how companies can leverage low-code technology to address specific challenges, promote collaboration, and unlock new opportunities for innovation and growth:

1. Customized CRM Systems: Swiftly enhance customer interactions with a tailored CRM system, collaboratively built by marketing and sales teams using low-code platforms.
2. Supply Chain Optimization: Streamline supply chain processes by automating workflows, allowing logistics and procurement teams to collaborate seamlessly.
3. Employee Onboarding and HR Workflows: Boost HR efficiency by automating onboarding processes. Low-code technology ensures a seamless onboarding experience for new hires.
4. Data Integration and Reporting: Overcome disparate data challenges with integrated dashboards and reporting systems created by cross-functional teams, no extensive coding required.
5. Regulatory Compliance Solutions: Stay compliant effortlessly by adapting systems to new regulations swiftly, courtesy of low-code platforms.
6. E-commerce Platform Enhancement: Stay competitive by enhancing e-commerce platforms collaboratively with marketing, sales, and IT teams using low-code technology.
7. Healthcare Process Automation: Improve operational efficiency in healthcare with rapid development of applications for appointment scheduling, patient records, and billing.
8. Educational Institution Management Systems: Streamline administrative processes in educational institutions with applications for student enrollment, grading systems, and communication channels built using low-code platforms.

Embrace the Low-Code Revolution with Capitole Consulting

At Capitole Consulting, we are at the forefront of this technological revolution. Our team of knowledgeable experts is dedicated to helping companies build the fundamentals, preparing your organization to adapt and transform seamlessly. Are you ready to unleash the full potential of your business through low-code platforms? Join the revolution with Capitole Consulting and propel your organization into a new era of efficiency, innovation, and growth. Let’s shape the future together!

Referencias:

• ¿Sabes lo que es ser un Citizen Developer? – Software Testing Bureau

• Microsoft is a Leader in the 2021 Gartner® Magic Quadrant™ for Enterprise Low-Code Application Platforms | Microsoft Power Apps

• Low-code innovation using Power Platform – Microsoft Power Platform Blog

• Describe the business value of the Microsoft Power Platform – Training | Microsoft Learn

• App Building Software for Everyone | Microsoft Power Apps

By Nohelya Dos Santos

The post Low Code Dev Business Potential appeared first on Capitole.

In the realm of software application development, QA analysts are akin to sentinels of success. When it comes to launching an app, the imperative is clear: it must operate with seamless perfection. In the crucible of app development, the art of streamlining user experiences becomes paramount. This involves a rigorous evaluation conducted by UI/UX experts and beta testers, identifying and resolving glitches at an early stage. By doing so, we ensure the birth of a successful, seamlessly functioning application, primed to make its mark in a competitive landscape.

Now, let’s turn our attention to the manifold benefits that software quality assurance brings to the table. Not only does it serve as a financial steward by nipping issues in the bud, minimizing overhead costs, and fostering an efficient development process, but it also takes on the mantle of enhancing the user experience. With eagle-eyed scrutiny, QA ensures that the app remains free of defects and operates in harmony with its intended design. This augmentation results in robust applications that adhere to stringent quality standards, minimizing the risk of system crashes, data breaches, or data corruption. Additionally, QA’s vigilance extends to the realm of security, where it detects and eliminates vulnerabilities, safeguarding sensitive user data and fostering trust among clients. Furthermore, QA adapts to the ever-evolving landscape of software development, aligning itself with the shifting sands of methodologies such as agile and DevOps.

It encompasses various types of testing, including functional, usability, performance, and security testing, with each type serving as a building block for overall software quality. Automation in QA accelerates the process and ensures consistent testing, although it comes with its own set of challenges. The human element in QA is pivotal, as skilled analysts not only detect bugs but also bring a critical perspective, offer valuable feedback, and contribute to overall product quality. By prioritizing quality assurance, we not only fulfill our clients’ expectations but also cultivate trust and loyalty. The judicious use of advanced tools and automation serves as the crowning touch, empowering us to optimize efficiency, curtail costs, and deliver consistently high-quality projects.

By Kevin Redlich

The post The Crucial Role of Quality Assurance in Software Development appeared first on Capitole.

Introduction

Playwright, an open-source library by Microsoft, stands out in E2E testing for its compatibility with multiple browsers and programming languages, offering fast and efficient automation.

Why Playwright?

Playwright is an open-source library developed by Microsoft that has gained significant popularity in the world of E2E testing. One of the primary reasons for discussing Playwright is its versatility and efficiency. Playwright allows for E2E testing in multiple browsers, including Chrome, Firefox, Edge, and Safari. Furthermore, it is compatible with various programming languages, making it accessible to a wide range of developers. Its user-friendly nature and integration with popular testing frameworks like Jest make it an attractive choice.

Playwright offers several key advantages:

Playwright is versatile, supporting tests in Chrome, Firefox, Edge, and Safari. Its integration with frameworks like Jest makes it appealing. It offers multi-browser support, compatibility with several languages, and an intuitive API for rapid automation.

Comparison with Some Existing Frameworks

Special Features of Playwright

Playwright also offers a set of advanced features that set it apart:

Resilience: Tests in Playwright are resilient to instability. The tool eliminates the need for artificial wait times, which are a major cause of unstable tests. Assertions are automatically retried until the necessary conditions are met, ensuring consistent results.

Tracing: Playwright allows for the configuration of retry strategies and captures execution traces, videos, and screenshots to eliminate instability issues, facilitating problem debugging.

No Limitations: Playwright leverages the modern architecture of browsers and runs tests outside the browser process, eliminating typical limitations of in-process test runners. This enables the execution of scenarios spanning multiple tabs, multiple origins, and multiple users in a single test.

Reliable events: Playwright employs a reliable event system that allows interaction with dynamic elements and the emulation of real user events.

Complete isolation: Each test in Playwright runs in an isolated browser context, ensuring complete separation and zero interference between tests. It also allows for the preservation of authentication state for reuse across all tests, avoiding repetitive login operations.

In summary, Playwright offers advanced features that ensure resilience, the elimination of unstable tests, the ability to execute complex scenarios, and a high degree of isolation, resulting in fast and efficient execution of E2E tests. These features make it a solid choice for projects requiring high-quality and reliable testing.

The world of software is constantly changing and advancing, and at Capitole, we are always at the forefront of these trends to provide our clients with the most innovative and effective solutions.

Jose Alberto Lorenzo

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