file_name come from your field :
db.table.field.upload_field
Here my field definition :
Field('picture', 'upload', uploadseparate=True, autodelete=True,
label=T('Profile image'),
represent=lambda value, row: image_chooser(value, row, '360px',
'360px')
),
You can read the full code of the module :
http://www.web2pyslices.com/slice/show/1666/improved-smarthumb
Richard
On Tue, Oct 22, 2013 at 10:10 AM, Richard Vézina <
ml.richard.vez...@gmail.com> wrote:
> You actually store the file name in database?
>
> if file_name != '' and file_name is not None:
> image_dir =
> db.auth_user[field].retrieve_file_properties(file_name)['path']
> img = Image.open(os.path.join(image_dir, file_name))
>
> :)
>
> Richard
>
>
> On Tue, Oct 22, 2013 at 10:06 AM, Richard Vézina <
> ml.richard.vez...@gmail.com> wrote:
>
>> 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)
>>>>>> ---
>>>>>> You received this message because you are subscribed to the Google
>>>>>> Groups "web2py-users" group.
>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>> send an email to web2py+un...@**googlegroups.com.
>>>>>>
>>>>>> For more options, visit
>>>>>> https://groups.google.com/**groups/opt_out<https://groups.google.com/groups/opt_out>
>>>>>> .
>>>>>>
>>>>>
>>>>> --
>>>> 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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