FdF | School 42 project // 3D Wireframe Viewer | 3D Animation library
kandi X-RAY | FdF Summary
kandi X-RAY | FdF Summary
FdF is a 3D Wireframe Viewer. (macOS is only supported). fdf.en.pdf is the task file.
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QUESTION
I have the following array, further details below
...ANSWER
Answered 2021-Mar-26 at 03:01You need to first filter the overall array before splitting the remaining objects into pieces:
QUESTION
I've got a string fdf=232232&lid=19974832&number=1&aa_result1_1=someId1&aa_resuuuuuult2_2=someId2&aa_resuuuult3_3=someId3
and if aa
exists I need to take values and add them to dictionary like:
ANSWER
Answered 2021-Mar-17 at 07:12this is a query string, you can use HttpUtility.ParseQueryString
to parse it
see
https://docs.microsoft.com/en-us/dotnet/api/system.web.httputility.parsequerystring?view=net-5.0
QUESTION
I have xml from a soap response that looks like the below (which I dont control the format of), note the nested Campaigns.Campaign.Campaign
ANSWER
Answered 2021-Mar-04 at 11:11You have two different namespace "..."which is giving an issue. Try code below :
QUESTION
I've started working on writing functions to make table generation quicker, but want to make the function respect earlier grouping choices made by the user in the pipe.
Example data:
...ANSWER
Answered 2021-Feb-22 at 22:16I added some lines that will merge both, the existing grouping variables and the new grouping variables inside the dots into one character vector. We can get the existing grouping variablers with group_vars
. To merge old and new together we have to get the expression get_expr
of the quoted grouping variables and turn them into strings. We can use !!! syms
to evaluate and all_of
to select the grouping variables.
Is this what you had in mind?
QUESTION
I'm using the FileDialog to select a folder for use with OutputTo. I have coded the file name. When I select a folder, I get a properly format string ie: "C:\Documents\export.xls". However, when I select the root folder, I get a improper format ie: "C:\\export.xls". Note the double slashes.
Any thoughts on what is causing this behavior?
...ANSWER
Answered 2021-Feb-22 at 18:04This is how the folder picker works - you need to handle both cases, e.g.
QUESTION
ddict = defaultdict(set)
file_str = query_csv_s3(s3, BUCKET_NAME, filename, sql_exp, use_header)
# read CSV to dataframe
df = pd.read_csv(StringIO(file_str))
fdf = df.drop_duplicates(subset='cleverTapId', keep='first')
fdf.dropna(inplace=True)
col_one_list = fdf['identity'].tolist()
col_two_list = fdf['cleverTapId'].tolist()
for k, v in zip(col_one_list, col_two_list):
ddict[k].add(v)
for imkey in ddict:
im_length = len(str(imkey))
if im_length == 9:
if len(ddict[imkey]) == 1:
for value in ddict[imkey]:
tdict = {imkey:value}
write_to_csv(FILE_NAME,tdict)
else:
ctlist = list(ddict[imkey])
snp_dict = {imkey:'|'.join(ctlist)}
write_to_csv(SNAP_FILE_NAME, snp_dict)
elif im_length > 0:
if len(ddict[imkey]) == 1:
for value in ddict[imkey]:
fdict = {imkey:value}
write_to_csv(FRAUD_FILE_NAME,fdict)
else:
pass
# mult_ct = list(ddict[imkey])
# mydict = {imkey:','.join(mult_ct)}
# write_to_csv(MY_FILENAME,mydict)
else:
pass
...ANSWER
Answered 2021-Feb-17 at 14:24This is essentially a guess, because I can't run your code. The way you write data to your CSV files is extremely inefficient.
I/O operations to SSDs or Disks are among the more expensive operations in IT. Right now you open a file for each line you want to append, then append it and close the file again. That means for a 530 MB file you're probably doing millions of these expensive operations.
If you check out the performance tab in task manager you'll probably see a very high disk usage.
It's much more efficient to buffer a few of these (or all if RAM is big enough) in memory and flush them to disk at the end.
Roughly like this:
QUESTION
I have names like this :
...ANSWER
Answered 2021-Feb-16 at 15:41You can use
QUESTION
I'm using PDFTron's Java SDK, and I want to change the name of an element, then write the modified PDF to a new file, but I get the following output:
...ANSWER
Answered 2021-Feb-11 at 19:48The API Field.GetName()
is technically an amalgamation of this leaf Field and any parent ones, delimited by a .
.
So while Field.getName()
might return name.first
the Field's T
value might just be first
. This is why there is Field.getPartialName()
exists.
So the better/safer code to change the T
value is.
QUESTION
I have two pyspark dataframe tdf
and fdf
, where fdf
is extremely larger than tdf
. And the sizes of these dataframes are changing daily, and I don't know them. I want to randomly pick data from fdf
to compose a new dataframe rdf
, where size of rdf
is approximately equal to the size of tdf
. Currently I have these lines:
ANSWER
Answered 2021-Jan-30 at 07:59You can try sampling from the dataframe to get an estimated count:
QUESTION
I apologize if this is a silly question, but is there an easy way to invert a MongoDB result? My aggregation pipeline returns this:
...ANSWER
Answered 2021-Jan-08 at 07:28You have two challenges, first you have to convert field values to field names. This is achieved with $objectToArray
and $arrayToObject
.
Second you have to translate all documents into one document. For this I use $group
and $reduce
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