Roger Leite

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Roger Leite

Roger Leite

@rogerleite

Living life with family and friends. Philosopher developer without fear to remix good ideas. 😎 | Software Engineer @Nubank he/him

São Paulo / Brazil Katılım Ekim 2008
673 Takip Edilen456 Takipçiler
Roger Leite retweetledi
NARCISA
NARCISA@narcisa·
Quanto custa o twitter?
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PotHix
PotHix@PotHix·
Best way to discuss a code change: create a PR that goes in the direction you need it to go. It doesn't really matter if it's wrong, it just needs to go in the right direction and mention the people involved. They will be right in context for the discussion and bring ideas.
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el hombre pulpo
el hombre pulpo@coproduto·
Bom, enquanto não morre isso aqui, vou mandar o que eu tava planejando pro começo da semana que vem Estamos abrindo uma vaga de BACKEND PLENO ELIXIR na Cumbuca Deem um RT aqui para que chegue nas pessoas antes do apocalipse Requisitos: - 1 ano de experiência com programação - Experiência prévia com frameworks web - Interesse em programação funcional - Interesse em sistemas financeiros Diferenciais: - Experiência prévia com programação funcional - Experiência prévia com sistemas financeiros Interessados enviar email com currículo e um parágrafo explicando por que você é um(a) bom(boa) candidato(a) para tech@cumbuca.com com o assunto "Vaga Backend Pleno"
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Guillaume Duboc
Guillaume Duboc@duboc_guillaume·
Our preprint on proving type safety for Elixir's gradual type system. Feedback welcome! arxiv.org/abs/2408.14345
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Ryan Els
Ryan Els@ryanels·
any 😂😏
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todd resudek ☠️
todd resudek ☠️@sprsmpl·
If anyone in my network is looking for work as an Elixir engineer, we have an opening at Draft Kings working on our lottery product. DM me if you want to know more. #myelixirstatus
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Nikki Siapno
Nikki Siapno@NikkiSiapno·
Database caching strategies explained. Let's look at five of the most common methods: 🔹 Cache-aside strategy This strategy grants applications explicit control over the caching process. Applications check the cache before the database, enabling precise control suited to dynamic data or irregular access patterns. However, this approach requires manual cache management, which can increase complexity. 🔹 Write-through strategy By simultaneously writing to the cache and the database, this technique guarantees data consistency. For applications requiring high data reliability, it eliminates inconsistencies and ensures immediate cache availability, despite increased write latency. 🔹 Write-behind strategy Write performance is improved by caching data first and updating the database asynchronously—a strategy that prioritizes speed over immediate consistency. This approach boosts responsiveness and reduces database load but risks data loss if the cache expires before syncing. Applications that can handle delayed data consistency and demand fast write speeds are best suited for it. 🔹 Read-through strategy When a cache misses, this strategy stores data in the cache by automatically retrieving it from the database. While this method simplifies application code by abstracting caching procedures, initial cache misses can delay data retrieval. It supports applications with stable data sets and high read demands by efficiently reducing database load. 🔹 Write-around strategy This method bypasses the cache, which is only refreshed upon further read requests, and writes data straight to the database. It keeps space for frequently accessed data by postponing cache updates, preventing premature cache saturation. Cache efficiency is maximized in write-intensive applications where instantaneous read access to fresh data is not essential. Database caching greatly improves application performance by reducing latency, increasing scalability, and enhancing user experiences. By selecting and implementing the optimal database caching solutions, we can meet unique application demands efficiently while maintaining high speed and resource efficiency. ~~ Thank you to our partner Postman who keeps our content free to the community. Do you have team members who are blocked because they're waiting for you to ship a new API? Unblock them using mock servers. Learn more here: drp.li/postman-mock-s…
GIF
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Granite Man 🏴󠁧󠁢󠁳󠁣󠁴󠁿
I remember when a computer didn't automatically connect to the internet, it used to make a screaming noise. We should have listened.
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Raul Junco
Raul Junco@RaulJuncoV·
Bad data is the root of all evil. SQL constraints will help you prevent it. Here are 6 Constraints simply explained. PRIMARY Key Constraint This means that the column's values are not null and unique. Each table in the database should have a primary key to identify its records. FOREIGN Key Constraint This means the column's values must match those in another table column, which is usually a primary key. Establishes a relationship between two tables using a column or set of columns. UNIQUE Constraint This means the column cannot have duplicate values across the whole table. Great for a username or email field on a User's table. CHECK Constraint The data must meet a custom expression for acceptance. For example, if you have a Score percentage column with values between 0 and 100, you can use a check constraint to enforce that. NOT NULL Constraint Ensures that a column does not contain NULL values. The column must have a value for each row. Define NOT NULL columns when your application assumes the existence of a value. DEFAULT Constraint The system assigns a default value to the column if you don't provide an explicit one. It is Useful when you want to provide a default value instead of leaving it NULL. Better Data = Better Software!
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Brian Kariuki
Brian Kariuki@briankariuki·
I've published the first release of tremorx, a phoenix component library. Its also been about 1 year since I wrote my first line of code in elixir 🤩. Check it out at: hexdocs.pm/tremorx/ #myelixirstatus
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Work Chronicles
Work Chronicles@_workchronicles·
Promotions and Stretch Assignments
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trash
trash@trashh_dev·
the truth hurts.
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