Streamlit é um framework Python de código aberto que permite a desenvolvedores e cientistas de dados construir e compartilhar belos aplicativos web personalizados para aprendizado de máquina e ciência de dados em minutos. A Streamlit Community Cloud oferece uma plataforma gratuita para implantar, gerenciar e compartilhar essas aplicações públicas com o mundo, fomentando um ambiente colaborativo para inovação.
Um centro de recursos abrangente de Victor Dibia, um pesquisador líder em ML Aplicado e HCI. Apresenta ferramentas de IA de código aberto como AutoGen Studio e LIDA, artigos aprofundados, trabalhos de pesquisa e palestras sobre IA generativa, sistemas multiagente e interação humano-computador. Uma plataforma valiosa para desenvolvedores, pesquisadores e entusiastas de IA.
Streamlit é um framework Python de código aberto que permite a desenvolvedores e cientistas de dados construir e compartilhar belos aplicativos web personalizados para aprendizado de máquina e ciência de dados em minutos. A Streamlit Community Cloud oferece uma plataforma gratuita para implantar, gerenciar e compartilhar essas aplicações públicas com o mundo, fomentando um ambiente colaborativo para inovação.
Um centro de recursos abrangente de Victor Dibia, um pesquisador líder em ML Aplicado e HCI. Apresenta ferramentas de IA de código aberto como AutoGen Studio e LIDA, artigos aprofundados, trabalhos de pesquisa e palestras sobre IA generativa, sistemas multiagente e interação humano-computador. Uma plataforma valiosa para desenvolvedores, pesquisadores e entusiastas de IA.
| Feature | Streamlit | victordibia |
|---|---|---|
| Categoria principal | Visualização de Dados | Visualização de Dados |
| Adicionado | 2025-08-17 | 2025-08-04 |
| Preço | Freemium | Gratuito |
| Site oficial | share.streamlit.io | victordibia.com |
| Tipo de produto | Site | Site |
| Performance data | ||
| Avaliação | Não verificado | Não verificado |
| Comentários | 0 | 0 |
| Visitas mensais | 918.5K | 22.4K |
| Crescimento mensal | 6.5% | 33.6% |
| Favoritos | 125 | 128 |
| Details | Ver detalhes | Ver detalhes |
Compare Streamlit and victordibia by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
In the Streamlit vs victordibia monthly traffic comparison, Streamlit currently shows 918.5K visits and victordibia shows 22.4K; Streamlit has about 41 times the visible traffic of victordibia, an absolute difference of about 896.1K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 44.68% | 410.4K |
| 🇮🇳India | 25.68% | 235.9K |
| 🇰🇷Korea, Republic of | 12.59% | 115.6K |
| 🇬🇧United Kingdom | 8.9% | 81.7K |
| 🇵🇰Pakistan | 8.15% | 74.9K |
| Source type | Percentage | Traffic |
|---|---|---|
| Direto | 57.82% | 531.1K |
| Referência | 40.37% | 370.8K |
| 1.81% | 16.6K |
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 37.7% | 8.5K |
| 🇮🇳India | 25.61% | 5.7K |
| 🇻🇳Vietnam | 14.63% | 3.3K |
| 🇬🇧United Kingdom | 11.38% | 2.6K |
| 🇮🇩Indonesia | 10.68% | 2.4K |
This in-depth Streamlit vs victordibia comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Streamlit is primarily listed under “Visualização de Dados”, while victordibia is primarily listed under “Visualização de Dados”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Pricing (Streamlit: Freemium; victordibia: Free); Monthly visits (Streamlit: 918.5K; victordibia: 22.4K); Monthly growth (Streamlit: 6.5%; victordibia: 33.6%); Favorites (Streamlit: 125; victordibia: 128); Website (Streamlit: share.streamlit.io; victordibia: victordibia.com). These facts are more useful for selection than brand visibility alone.
In the Streamlit vs victordibia monthly traffic comparison, Streamlit currently shows 918.5K visits and victordibia shows 22.4K; Streamlit has about 41 times the visible traffic of victordibia, an absolute difference of about 896.1K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Streamlit first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Streamlit and victordibia currently overlap in shared categories: Visualização de Dados e Low-code No-code; shared tags: visualização de dados, Ferramentas de desenvolvedor, aprendizado de máquina e Código Aberto. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Streamlit's unique categories/tags are Construtor de Aplicativos, Construtor de aplicativos, Painel, ciência de dados, Python e aplicativo web; victordibia's are Pesquisa, Escrita, Educação em IA, Pesquisa de IA, AutoGen, IA generativa, IHC e Sistemas multiagente. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
Streamlit has no verified rating, 0 comments, 125 favorites, and 125 likes；victordibia has no verified rating, 0 comments, 128 favorites, and 120 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Put Streamlit on the priority trial list when the task aligns with “Visualização de Dados” and especially Construtor de Aplicativos, Construtor de aplicativos, Painel, ciência de dados, Python e aplicativo web. This follows recorded positioning and does not imply unlisted capabilities are absent.
Streamlit also currently records: pricing is freemium, product type is website, 918.5K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
Put victordibia on the priority trial list when the task aligns with “Visualização de Dados” and especially Pesquisa, Escrita, Educação em IA, Pesquisa de IA, AutoGen e IA generativa. This follows recorded positioning and does not imply unlisted capabilities are absent.
victordibia also currently records: pricing is free, product type is website, 22.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Streamlit and victordibia, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.
