GoPlus – The Go+ language for data science
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Re: GoPlus – The Go+ language for data science
#2I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.
Re: GoPlus – The Go+ language for data science
#3I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.
Agreed, but it might be useful for a full stack data scientist that is forced to work in a Go systems environment.
That's why Python+PyData has had so much success. There are packages to support data science, but the language itself can also be used to implement a system, so integration is rather seamless. That's not true for, say, R.
Re: GoPlus – The Go+ language for data science
#4I'm not a Go user, but is the important idea here that it can be run from a scriptingish environment like Jupyter or something?
Re: GoPlus – The Go+ language for data science
#5I feel where they are trying to go with this, I wrote https://github.com/aunum/gold in Go because of all the nice parts of Go.
This solves some of the pain points but is still fatally flawed as any other Go ML tool in that it can’t accelerate due to the GoC FFI.
Until that issue is resolved Go simply won’t be broadly accepted in data science.
Re: GoPlus – The Go+ language for data science
#6I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.
Agreed, but it might be useful for a full stack data scientist that is forced to work in a Go systems environment. That's why Python+PyData has had so much success. There are packages to support data science, but the language itself can also be used to implement a system, so integration is rather seamless. That's not true for, say, R.
I use Python and R for data science, and I've never had any issue with R. In fact, I find that many tasks are much simpler in R than in Python.
Re: GoPlus – The Go+ language for data science
#7Earlier quoted context omitted.
Agreed, but it might be useful for a full stack data scientist that is forced to work in a Go systems environment. That's why Python+PyData has had so much success. There are packages to support data science, but the language itself can also be used to implement a system, so integration is rather seamless. That's not true for, say, R.
I use Python and R for data science, and I've never had any issue with R. In fact, I find that many tasks are much simpler in R than in Python.
> never had any issue
Re: GoPlus – The Go+ language for data science
#8I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.
The official Github repo of Go+ is hosted on a PaaS company called Qiniu's team repo with their founder & CEO as the top contributor[1][2]. He is a Golang enthusiast[3] and my guess is that this is probably his favorite pet project ;)
[1]: https://github.com/qiniu/goplus/graphs/contributors
Re: GoPlus – The Go+ language for data science
#9I have a feeling languages like this have their niche cases however I'm not getting a good reason for why this is need when compared to Python for data science. Maybe I'm missing something but this is essentially a wrapper for Golang code to make it feel more like Python.
Agreed, but it might be useful for a full stack data scientist that is forced to work in a Go systems environment. That's why Python+PyData has had so much success. There are packages to support data science, but the language itself can also be used to implement a system, so integration is rather seamless. That's not true for, say, R.
I guess it depends on what you’re trying to accomplish (I’ve worked heavily with both R and Python).
If you’re trying to create ETL pipelines that integrate with BigQuery, Mongo, or whatever other database, I think it’s fair to say that the Python packages are generally better documented than their R counterparts.
For most other things, IMO it’s hard to really separate the two languages. Is standing up a Flask API really easier than in plumber?
For dashboarding, it’s is as quick (if not much quicker) to create a decent prototype with Shiny vs Plotly Dash or bokeh.
For simple linear and logistic model training, R’s built-in stats package has much more interpretable outputs vs sklearn, and directly inspired statsmodel. Wes McKinney has acknowledged that pandas draws heavily from R’s native dataframe. And so on and so on.
EDIT:
Also forgot to mention that with R packages like reticulate, you can also directly run Python code within an R environment now. So if there happens to be some Python package that doesn’t have an R equivalent, you can still work in R (though I’ve found the opposite situation to be far more common).
Re: GoPlus – The Go+ language for data science
#10IMHO these conveniences should just be in the language. List comprehensions, dictionary comprehensions, and short-hand for literals are the kind of syntactic sugar that have almost no downsides, save you some RSI, and make code more readable. I'm surprised comprehensions in particular haven't spread to more modern languages.