Type4Py: Deep Similarity Learning-Based Type Inference for #python
Over the past decade, machine learning (ML) has been applied successfully to a variety of tasks such as computer vision and natural language processing. Motivated by this, in recent years, researchers have employed ML techniques to solve code-related problems, including but not limited to, code completion, code generation, program repair, and type inference.
Dynamic programming languages like Python and TypeScript allows developers to optionally define type annotations and benefit from the advantages of static typing such as better code completion, early bug detection, and etc. However, retrofitting types is a cumbersome and error-prone process. To address this, we propose Type4Py, an ML-based type auto-completion for Python. It assists developers to gradually add type annotations to their codebases.
Type4Py: Deep Similarity Learning-Based Type Inference for #python
Over the past decade, machine learning (ML) has been applied successfully to a variety of tasks such as computer vision and natural language processing. Motivated by this, in recent years, researchers have employed ML techniques to solve code-related problems, including but not limited to, code completion, code generation, program repair, and type inference.
Dynamic programming languages like Python and TypeScript allows developers to optionally define type annotations and benefit from the advantages of static typing such as better code completion, early bug detection, and etc. However, retrofitting types is a cumbersome and error-prone process. To address this, we propose Type4Py, an ML-based type auto-completion for Python. It assists developers to gradually add type annotations to their codebases.
At a time when the Indian stock market is peaking and has rallied immensely compared to global markets, there are companies that have not performed in the last 10 years. These are definitely a minor portion of the market considering there are hundreds of stocks that have turned multibagger since 2020. What went wrong with these stocks? Reasons vary from corporate governance, sectoral weakness, company specific and so on. But the more important question is, are these stocks worth buying?
That growth environment will include rising inflation and interest rates. Those upward shifts naturally accompany healthy growth periods as the demand for resources, products and services rise. Importantly, the Federal Reserve has laid out the rationale for not interfering with that natural growth transition.It's not exactly a fad, but there is a widespread willingness to pay up for a growth story. Classic fundamental analysis takes a back seat. Even negative earnings are ignored. In fact, positive earnings seem to be a limiting measure, producing the question, "Is that all you've got?" The preference is a vision of untold riches when the exciting story plays out as expected.
