pyrserve

Store large data or a service connection per Flask session

由 独自空忆成欢 提交于 2020-01-25 08:16:59
问题 I'm writing a small Flask application and am having it connect to Rserve using pyRserve. I want every session to initiate and then maintain its own Rserve connection. Something like this: session['my_connection'] = pyRserve.connect() doesn't work because the connection object is not JSON serializable. On the other hand, something like this: flask.g.my_connection = pyRserve.connect() doesn't work because it does not persist between requests. To add to the difficulty, it doesn't seem as though

Python interface for R Programming Language [duplicate]

由 橙三吉。 提交于 2019-11-28 02:51:00
This question already has an answer here: How do Rpy2, pyrserve and PypeR compare? 4 answers I am quite new to R, and pretty much used to python. I am not so comfortable writing R code. I am looking for python interface to R, which lets me use R packages in pythonic way . I have done google research and found few packages which can do that: Rpy2 PypeR pyRserve But not sure which one is better ? Which has more contributers and more actively used ? Please note my main requirement is pythonic way for accessing R packages . gauden As pointed out by @lgautier, there is already another answer on

How do Rpy2, pyrserve and PypeR compare?

由 妖精的绣舞 提交于 2019-11-27 06:24:43
I would like to access R from within a Python program. I am aware of Rpy2, pyrserve and PypeR. What are the advantages or disadvantages of these three options? I know one of the 3 better than the others, but in the order given in the question: rpy2: C-level interface between Python and R (R running as an embedded process) R objects exposed to Python without the need to copy the data over Conversely, Python's numpy arrays can be exposed to R without making a copy Low-level interface (close to the R C-API) and high-level interface (for convenience) In-place modification for vectors and arrays

Python interface for R Programming Language [duplicate]

由 帅比萌擦擦* 提交于 2019-11-26 23:50:49
问题 This question already has an answer here: How do Rpy2, pyrserve and PypeR compare? 4 answers I am quite new to R, and pretty much used to python. I am not so comfortable writing R code. I am looking for python interface to R, which lets me use R packages in pythonic way . I have done google research and found few packages which can do that: Rpy2 PypeR pyRserve But not sure which one is better ? Which has more contributers and more actively used ? Please note my main requirement is pythonic

How do Rpy2, pyrserve and PypeR compare?

由 混江龙づ霸主 提交于 2019-11-26 11:59:43
问题 I would like to access R from within a Python program. I am aware of Rpy2, pyrserve and PypeR. What are the advantages or disadvantages of these three options? 回答1: I know one of the 3 better than the others, but in the order given in the question: rpy2: C-level interface between Python and R (R running as an embedded process) R objects exposed to Python without the need to copy the data over Conversely, Python's numpy arrays can be exposed to R without making a copy Low-level interface

Store large data or a service connection per Flask session

由 ≯℡__Kan透↙ 提交于 2019-11-25 21:53:33
问题 I\'m writing a small Flask application and am having it connect to Rserve using pyRserve. I want every session to initiate and then maintain its own Rserve connection. Something like this: session[\'my_connection\'] = pyRserve.connect() doesn\'t work because the connection object is not JSON serializable. On the other hand, something like this: flask.g.my_connection = pyRserve.connect() doesn\'t work because it does not persist between requests. To add to the difficulty, it doesn\'t seem as
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