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@faun shared a link, 2 years, 4 months ago
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CLI tools hidden in the Python standard library

The Python gzip module can be used as a CLI tool by running "python -m gzip --decompress pypi.db.gz". This feature is particularly useful for Windows users who don't have the gzip utility installed. Other similar tools are available!.. read more  

CLI tools hidden in the Python standard library
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

Using Contextual Bandit models in large action spaces at Instacart

Instacart strives to provide personalized customer experiences by combining multiple considerations in product searches, such as personal relevance, popularity, price, and item availability. They have implemented a contextual bandit (CB) model to train and recommend actions that enhance the shopping.. read more  

Using Contextual Bandit models in large action spaces at Instacart
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

A theme editor for JupyterLab

JupyterLab is a comprehensive web user interface for scientific and technical computing that allows users to choose between light and dark color themes, as well as adjust the contrast, color palette, and font for accessibility purposes. Custom themes can be created using CSS variables, and a theme e.. read more  

A theme editor for JupyterLab
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

Bringing Locality of Behaviour to Django Views and URLs

Django's "LOB Connection View URLs" principle suggests using decorators to connect URLs directly to views, avoiding the disconnect between the URL configuration and the views. This approach allows for more flexibility and improves the organization and management of URL patterns in Django projects... read more  

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@faun shared a link, 2 years, 4 months ago
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Pytest fixtures are magic!

Pytest fixtures are a powerful tool for writing efficient and effective tests. Fixtures can be used to generate specific data needed for testing, making it easier to create and automate tests. Additionally, fixtures can be reused across tests and even across projects, improving development velocity... read more  

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@faun shared a link, 2 years, 4 months ago
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My 20 Year Career is Technical Debt or Deprecated

Technical debt is a common and challenging issue in the software development industry, as technologies and programming languages evolve and become outdated over time. It is important for companies to actively manage and address technical debt to avoid the negative consequences it can have on their p.. read more  

My 20 Year Career is Technical Debt or Deprecated
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

The web's most important decision

Thirty years ago, CERN made a decision to relinquish all intellectual property rights to the World Wide Web, allowing it to enter the public domain and be freely accessible to everyone. This decision, driven by optimism and ambition, transformed the trajectory of the web and enabled unparalleled ope.. read more  

The web's most important decision
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

Vint Cerf’s Career Advice for Engineers

Vint Cerf, the Internet architect and recipient of the 2023 IEEE Medal of Honor, shares career advice for engineers. He emphasizes the importance of seeking help from those who are smarter, being humble and open to possibilities, listening to others' insights, maintaining good relationships, and ack.. read more  

Vint Cerf’s Career Advice for Engineers
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

Supercharging my Telegram group with the help of ChatGPT

A Telegram user has built two new features for a chat group. The first feature, called "/resume," provided a summary of the conversation to help catch up on missed messages. The second feature, called "/fake @username <insert question>," allowed users to impersonate their friends in the chat and ask.. read more  

Supercharging my Telegram group with the help of ChatGPT
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@faun shared a link, 2 years, 4 months ago
FAUN.dev()

Generating Code without Generating Technical Debt?

GPT and other large language models can produce huge volumes of code quickly, allowing for faster prototyping and iterative development. However, this can result in a larger amount of messy code that needs to be maintained... read more  

Generating Code without Generating Technical Debt?

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