Tag: python,django,django-admin
will be possible to display a confirmation hearing to modify a record in a table, as is done when you delete a record?
as to modify a record and press the button save this did not request any confirmation or performs the action.
find out what would have to occupy the pre_save() but I could not make the confirmation hearing
https://docs.djangoproject.com/en/dev/ref/signals/#pre-save
thank you for your help.
In the formtools contrib package you'll find form-preview, which is a class that lets you load a form, preview it, and then provides hooks to do whatever you would like with the cleaned form data.
It takes care of the following flow:
This would solve your confirmation problem.
Django templates do not use inclusion so much as template inheritance. The idea is you set up a hierarchy of templates, specializing some common thing. For instance: you could have a base.html that has some basic page structure, common to all pages of your website. you could then have a...
Use collections.OrderedDict: from collections import OrderedDict od = OrderedDict() lst = [2, 0, 1, 1, 3, 2, 1, 2] for i, x in enumerate(lst): od.setdefault(x, []).append(i) ... >>> od.values() [[0, 5, 7], [1], [2, 3, 6], [4]] ...
python,similarity,locality-sensitive-hash
a. It's a left shift: https://docs.python.org/2/reference/expressions.html#shifting-operations It shifts the bits one to the left. b. Note that ^ is not the "to the power of" but "bitwise XOR" in Python. c. As the comment states: it defines "number of bits per signature" as 2**10 → 1024 d. The lines calculate...
django,rest,django-models,django-rest-framework,imagefield
As noted in the docs, .update() doesn't call the model .save() or fire the post_save/pre_save signals for each matched model. It almost directly translates into a SQL UPDATE statement. https://docs.djangoproject.com/en/1.8/ref/models/querysets/#update Finally, realize that update() does an update at the SQL level and, thus, does not call any save() methods on...
You need to use the configure method of each widget: def rakhi(): entry1.configure(state="normal") entry2.configure(state="normal") ...
I don't know what you are exactly trying to achieve but if you are trying to count R and K in the string there are more elegant ways to achieve it. But for your reference I had modified your code. N = int(raw_input()) s = [] for i in range(N):...
Check the code before the print line for errors. This can be caused by an error in a previous line; for example: def x(): y = [ print "hello" x() This produces the following error: File "E:\Python\test.py", line 14 print "hello" ^ SyntaxError: invalid syntax When clearly the error is...
python,html,django,templates,django-1.4
You can use the include tag in order to supply the included template with a consistent variable name: For example: parent.html <div class="row"> <div class="col-md-12 col-lg-12 block block-color-1"> {% include 'templates/child.html' with list_item=mylist.0 t=50 only %} </div> </div> child.html {{ list_item.text|truncatewords:t }} UPDATE: As spectras recommended, you can use the...
python,amazon-web-services,boto
Make sure you have set properly with ~/.boto and connect to aws, have the boto module ready in python. If not, go through this first: Getting Started with Boto For example, you need assign a new EIP 54.12.23.34 to the instance i-12345678 Make sure, EIP has been allocated(existed) and you...
Afraid I don't know much about python, but I can probably help you with the algorithm. The encoding process repeats the following: multiply the current total by 17 add a value (a = 1, b = 2, ..., z = 26) for the next letter to the total So at...
Just use photoshop or G.I.M.P.. I assure you, doing it that way will be much simpler and less redundant than essentially getting Tkinter to photo edit for you (not to mention what you're talking about is just bad practice when it comes to coding) Anyways, I guess if you really...
python,automated-tests,robotframework
By default variables are string in Robot. So your first two statements are assigning strings like "xx,yy" to your vars. Then "evaluate" just execute your statement as Python would do. So, adding your two strings with commas will produce a list: $ python >>> 1,2+3,4 (1, 5, 4) So you...
python,list,numpy,multidimensional-array
According to documentation of numpy.reshape , it returns a new array object with the new shape specified by the parameters (given that, with the new shape, the amount of elements in the array remain unchanged) , without changing the shape of the original object, so when you are calling the...
python,image-processing,imagej
The display range of your image might not be set correctly. Try outputImp.resetDisplayRange() or outputImp.setDisplayRange(Stats.min, Stats.max) See the ImagePlus javadoc for more info....
python,bash,environment-variables
After updating your .bashrc, perform source ~/.bashrc to apply the changes. Also, merge the two BONSAI-related calls into one: export BONSAI=/home/me/Utils/bonsai_v3.2 UPDATE: It was actually an attempt to update the environment for some Eclipse-based IDE. This is a different usecase altogether. It should be described in the Eclipse help. Also,...
You can just subscript the columns: df = df[df.columns[:11]] This will return just the first 11 columns or you can do: df.drop(df.columns[11:], axis=1) To drop all the columns after the 11th one....
If you want the None and '' values to appear last, you can have your key function return a tuple, so the list is sorted by the natural order of that tuple. The tuple has the form (is_none, is_empty, value); this way, the tuple for a None value will be...
How about using Regular Expression def get_info(string_to_search): res_dict = {} import re find_type = re.compile("Type:[\s]*[\w]*") res = find_type.search(string_to_search) res_dict["Type"] = res.group(0).split(":")[1].strip() find_Status = re.compile("Status:[\s]*[\w]*") res = find_Status.search(string_to_search) res_dict["Status"] = res.group(0).split(":")[1].strip() find_date = re.compile("Date:[\s]*[/0-9]*") res = find_date.search(string_to_search) res_dict["Date"] = res.group(0).split(":")[1].strip() res_dict["description"] =...
if you only need to do this for a handful of points, you could do something like this. If intensites and radius are numpy arrays of your data: bin_width = 0.1 # Depending on how narrow you want your bins def get_avg(rad): average_intensity = intensities[(radius>=rad-bin_width/2.) & (radius<rad+bin_width/2.)].mean() return average_intensities #...
I think the problem is with your start.py file. You have a function refreshgui which re imports start.py import will run every part of the code in the file. It is customary to wrap the main functionality in an ''if __name__ == '__main__': to prevent code from being run on...
python,scikit-learn,pipeline,feature-selection
The pipeline calls transform on the preprocessing and feature selection steps if you call pl.predict. That means that the features selected in training will be selected from the test data (the only thing that makes sense here). It is unclear what you mean by "apply" here. Nothing new will be...
Your list contains one dictionary you can access the data inside like this : >>> yourlist[0]["popularity"] 2354 [0] for the first item in the list (the dictionary). ["popularity"] to get the value associated to the key 'popularity' in the dictionary....
Remove the comma on your first line of code, this turns it into a tuple optional_message = form.cleaned_data['optional_message'], should be optional_message = form.cleaned_data['optional_message'] ...
python,python-2.7,pandas,dataframes
I believe the following does what you want: In [24]: df['New_Col'] = df['ActualCitations']/pd.rolling_sum(df['totalPubs'].shift(), window=2) df Out[24]: Year totalPubs ActualCitations New_Col 0 1994 71 191.002034 NaN 1 1995 77 2763.911781 NaN 2 1996 69 2022.374474 13.664692 3 1997 78 3393.094951 23.240376 So the above uses rolling_sum and shift to generate the...
Since you want to convert python script to exe have a look at py2exe
Yes. See .vocabulary_ on your fitted/transformed TF-IDF vectorizer. In [1]: from sklearn.datasets import fetch_20newsgroups In [2]: data = fetch_20newsgroups(categories=['rec.autos']) In [3]: from sklearn.feature_extraction.text import TfidfVectorizer In [4]: cv = TfidfVectorizer() In [5]: X = cv.fit_transform(data.data) In [6]: cv.vocabulary_ It is a dictionary of the form: {word : column index in...
