There is also : http://d3js.org/
:)
Richard
On Tue, Oct 22, 2013 at 10:04 AM, Richard Vézina <
ml.richard.vez...@gmail.com> wrote:
> request.application ??
>
>
> On Tue, Oct 22, 2013 at 10:01 AM, Thomas S <thomas.schmel...@gmail.com>wrote:
>
>> Yes, I use HDF5 for more than a year now.
>> It's great. The only drawback is the lack of elegant Java tools.
>> I upload those files and store their obfuscated names in a database, but
>> the actual file in uploads.
>> Having said that it's not very elegant to construct the URL to locate the
>> file:
>>
>> def show():
>> csv = db.csv(request.args(0, cast=int))
>>
>> import pandas
>> import os
>>
>> fff = os.path.join("applications", "cda", "uploads", csv.csvfile)
>>
>> session.dataframe = pandas.read_csv(fff, parse_dates=True,
>> index_col=0)
>>
>> return dict(title=csv.title, body=csv.body, author=csv.author,
>> keys=session.dataframe.keys())
>>
>> Note that sesssion,dataframe is now a global variable. And note the ugly
>> os.path.join with the name of the application hardcoded.... UGLY!
>>
>> Here's a link:
>> https://tschmelz.**pythonanywher**e.com/cda<https://tschmelz.pythonanywhere.com/cda>
>>
>> and
>>
>> https://github.com/tschm/cda
>>
>> Thomas
>>
>>
>>
>>
>>
>> On Tuesday, 22 October 2013 15:16:25 UTC+2, Richard wrote:
>>
>>> I heard a lot of good about HDF5 file format to hande important volume
>>> of data hierachical (mean you can query what ever data you need without
>>> load the full data set into a json for instance) :
>>> http://en.wikipedia.org/**wiki/Hierarchical_Data_Format<http://en.wikipedia.org/wiki/Hierarchical_Data_Format>
>>>
>>> It very much faster then postgres (sure postgres is not the faster
>>> backend but it scale gracefully)...
>>>
>>> The intend of this file format is to be used in conjonction with a DB.
>>>
>>> If I remember Pandas can write HDF5, not sure which lib it uses, there
>>> is two major lib in python which have different set of feature, one is more
>>> fancy but not support all the HDF5 feature and the other is supporting
>>> "all" the feature but is less sexy...
>>>
>>> Richard
>>>
>>>
>>> On Tue, Oct 22, 2013 at 6:54 AM, Cliff Kachinske <cjk...@gmail.com>wrote:
>>>
>>>> use the rows field in auth_permission as described here.
>>>>
>>>> http://web2py.com/books/**default/chapter/29/09/access-**
>>>> control#Authorization<http://web2py.com/books/default/chapter/29/09/access-control#Authorization>
>>>>
>>>>
>>>> On Tuesday, October 22, 2013 5:40:49 AM UTC-4, Thomas S wrote:
>>>>>
>>>>> Ok, I am making progress. I guess all those JavaScript tools are not
>>>>> great when it comes to plotting millions of points but I am happy to
>>>>> downsample on the server side and send less points
>>>>>
>>>>> - I am using flot instead of highcharts
>>>>>
>>>>> - Currently, the user is uploading a csv file. I don't do any parsing
>>>>> at this stage. However, I rather keep the file (under uploads) and parse
>>>>> it
>>>>> on request. Having said that this will become a lot more slick soon. This
>>>>> is my first application.
>>>>>
>>>>> One thing that puzzles me for now...
>>>>>
>>>>> A user has to login to upload a file (that's good), but he can then
>>>>> also modify or delete entries in the SQL database created by others. How
>>>>> can I make sure he/she only deletes rows he/she has created in the first
>>>>> place. All users should be able to see all files though.
>>>>>
>>>>> Here's a link:
>>>>> https://tschmelz.**pythonanywher**e.com/csv<https://tschmelz.pythonanywhere.com/csv>
>>>>>
>>>>> I will soon post it to my Github (username tschm)
>>>>> thomas
>>>>>
>>>>>
>>>>> On Sunday, 20 October 2013 15:38:07 UTC+2, Niphlod wrote:
>>>>>>
>>>>>> first things first: are you sure that highcharts can handle 10*100k
>>>>>> points to draw a graph ?
>>>>>> As for the storage, you can do anything you like: if the data doesn't
>>>>>> change that much, storing into the database will be a long process only
>>>>>> on
>>>>>> the first time.
>>>>>> On the other end, if you need to fetch 100k records and transform
>>>>>> them to json, it's going to take some time.
>>>>>> Not sure on how much you'll gain from parsing i.e. a csv file instead
>>>>>> of a querying a db....
>>>>>> if the returning json object is , let's say, 10 mb, it's always gonna
>>>>>> feel heavy.
>>>>>>
>>>>>> On Sunday, October 20, 2013 9:11:07 AM UTC+2, Thomas S wrote:
>>>>>>>
>>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>> I have created a standard application relying on Pandas and PyQt4 to
>>>>>>> browse through a Pandas Dataframe.
>>>>>>> A dataframe is essentially a dictionary of time series data.
>>>>>>>
>>>>>>> I am new to web2py but I have experience with Pandas and matplotlib.
>>>>>>> I am also tempted to embed www.highcharts.com into my application.
>>>>>>>
>>>>>>> Before I dig into web2py I would like to know which route is
>>>>>>> probably most promising.
>>>>>>>
>>>>>>> Should I parse the dataframe on the webserver and write it into a
>>>>>>> SQL database? I guess that could be slow?
>>>>>>> Such a dataframe may consist of a dictionary with 100 elements each
>>>>>>> several 100k points.
>>>>>>>
>>>>>>> Should I parse a time series onto request into a json format and
>>>>>>> export to javaScript?
>>>>>>> In this case how could I provide a way to generate a menu from the
>>>>>>> keys in the dictionary.
>>>>>>> E.g. user clicks on a key, python does all the computations for some
>>>>>>> stats.
>>>>>>>
>>>>>>> The plan is to upload the data using csv files.
>>>>>>>
>>>>>>> So, I am a bit lost by the wide range of possibilities in web2py. I
>>>>>>> would be delighted if you would like to get involved in this open source
>>>>>>> project.
>>>>>>> The main goal for now is to learn web2py :-)
>>>>>>>
>>>>>>> Please find the Github of the original application here
>>>>>>> https://github.com/tschm/**Panda**sMonitor<https://github.com/tschm/PandasMonitor>
>>>>>>>
>>>>>>> Sorry for being so unprecise in my questions but it just reflects
>>>>>>> that I don't have a very precise plan at this stage.
>>>>>>>
>>>>>>> Kind regards
>>>>>>> Thomas
>>>>>>>
>>>>>> --
>>>> Resources:
>>>> - http://web2py.com
>>>> - http://web2py.com/book (Documentation)
>>>> - http://github.com/web2py/**web2py
>>>> <http://github.com/web2py/web2py>(Source code)
>>>> -
>>>> https://code.google.com/p/**web2py/issues/list<https://code.google.com/p/web2py/issues/list>(Report
>>>> Issues)
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>>>>
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>>>> .
>>>>
>>>
>>> --
>> Resources:
>> - http://web2py.com
>> - http://web2py.com/book (Documentation)
>> - http://github.com/web2py/web2py (Source code)
>> - https://code.google.com/p/web2py/issues/list (Report Issues)
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>
>
--
Resources:
- http://web2py.com
- http://web2py.com/book (Documentation)
- http://github.com/web2py/web2py (Source code)
- https://code.google.com/p/web2py/issues/list (Report Issues)
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