I have code like this:
from datetime import datetime
from tabulate import tabulate
def search_projection_date():
projections = open('projections.txt','r').readlines()
date = input("Input projection date: ")
try:
date = date.strptime(date, "%d.%m.%Y.")
except:
print("Date input error!")
#search_projection_date()
for i in projections:
projections = i.strip("\n").split("|")
if date == projections[2]:
table = [['Code:',projections[0]],['Hall:',projections[1]],['Date:',projections[2]],['Start time:',projections[3]],['End time:', projections[4]],['Day(s):', projections[5]], ['Movie:', projections[6]], ['Price:', projections[7]]]
print (tabulate(table))
#break
else:
print("No projection on that date")
And text file like this:
0001|AAA|17.12.2017.|20:30|21:00|sunday|For a few dolars more|150
0002|BBB|17.12.2017.|19:30|21:15|saturday|March on the Drina|300
0003|GGG|19.12.2017.|18:00|19:00|tuesday|A fistful of Dolars|500
0004|GGG|16.12.2017.|21:15|00:00|sunday|The Good, the Bad and the Ugly|350
I try to search movie projections by date...
If there is a projection on the entered date it will find it and print the list, but before printing that list it will always print "Date input error" and after that list "No projection on that date". (if I put break in if statement it will print only the first found projection on entered day, withouth else statement, obvious)
Questions: How to print ONLY list of projections without "date input error" if date is correctly input.
How to print only "No projection on that date" if date is correct but there is no projection and how to ask user for input that until puts it correctly? In this way with recursion it will always throw exception and recursion search_projection_date() function.
There are a whole bunch of major problems with your code. As it happens, they showcase why some general advice we hear so often is actually good advice.
The line date = input("Input projection date: ") creates a string named date. input always returns a string. Strings in Python do not have a method called strptime. Which brings us to issue #2:
You should not catch generic exceptions. You were probably looking to trap a TypeError or ValueError in the except clause. However, you are getting an error that says AttributeError: 'str' object has no attribute 'strptime'. This is because you can't call methods that you want to exist but don't. Your except line should probably read something like except ValueError:.
Your except clause does nothing useful (beyond the problems listed above). If the string is not formatted correctly, you print a message but continue anyway. You probably want to use raise in the except clause to propagate the exception further. Luckily for you, you actually want the date to be a string, which brings us to issue #4:
Why are you attempting to convert the string to a date to begin with? You can not compare a date object and a string that you get from the file and ever expect them to be equal. You want to compare a string to a string. If you had some kind of validation in mind, that's fine, but use datetime.strptime and don't replace the original string; just raise an error if it doesn't convert properly.
The else clause in a for loop will execute whenever the loop terminates normally (i.e., without a break). Since you always iterate through all the lines, you will always trigger the else clause. You need to have another way to determine if you found matching items, like a boolean flag or a counter. I will show an example with a counter, since it is more general.
You never close your input file. Not a huge problem in this tiny example, but can cause major issues with bigger programs. Use a with block instead of raw open.
Your method of iterating through the file is not wrong per-se, but is inefficient. You load the entire file into memory, and then iterate over the lines. In Python, text files are already iterable over the lines, which is much more efficient since it only loads one line at a time into memory, and also doesn't make you process the file twice.
Combining all that, you can make your code look like this:
def search_projection_date():
counter = 0
with open('projections.txt','r') as projections:
date = input("Input projection date: ")
for line in projections:
projection = line.strip("\n").split("|")
if date == projection[2]:
table = [['Code:',projection[0]],
['Hall:',projection[1]],
['Date:',projection[2]],
['Start time:',projection[3]],
['End time:', projection[4]],
['Day(s):', projection[5]],
['Movie:', projection[6]],
['Price:', projection[7]]]
print(tabulate(table))
counter += 1
if not counter:
print("No projection on that date")
else:
print("Found {0} projections on {1}".format(counter, date))
I trusted your use of tabulate since I am not familiar with the module and have no intention of installing it. Keep in mind that the date verification is optional. If the user enters an invalid string, that's the end of it: you don't need to check for dates like 'aaaa' because they will just print No projection on that date. If you insist on keeping the verification, do it more like this:
from datetime import datetime
datetime.strftime(date, '%d.%m.%Y.')
That's it. It will raise a ValueError if the date does not match. You don't need to do anything with the result. If you want to change the error message, or return instead of raising an error, you can catch the exception:
try:
datetime.strftime(date, '%d.%m.%Y.')
except ValueError:
print('Bad date entered')
return
Notice that I am catching a very specific type of exception here, not using a generic except clause.
Related
Please mind you, I'm new to Pandas/Python and I don't know what I'm doing.
I'm working with CSV files and I basically filter currencies.
Every other day, the exported CSV file may contain or not contain certain currencies.
I have several such cells of codes--
AUDdf = df.loc[df['Currency'] == 'AUD']
AUDtable = pd.pivot_table(AUDdf,index=["Username"],values=["Amount"],aggfunc=np.sum)
AUDtable.loc['AUD Amounts Rejected Grand Total'] = (AUDdf['Amount'].sum())
AUDdesc = AUDdf['Amount'].describe()
When the CSV doesn't contain AUD, I get ValueError: cannot set a frame with no defined columns.
What I'd like to produce is a function or an if statement or a loop that checks if the column contains AUD, and if it does, it runs the above code, and if it doesn't, it simply skips it and proceeds to the next line of code for the next currency.
Any idea how I can accomplish this?
Thanks in advance.
This can be done in 2 ways:
You can create a try and except statement, this will try and look for the given currency and if a ValueError occurs it will skip and move on:
try:
AUDdf = df.loc[df['Currency'] == 'AUD']
AUDtable = pd.pivot_table(AUDdf,index=["Username"],values["Amount"],aggfunc=np.sum)
AUDtable.loc['AUD Amounts Rejected Grand Total'] = (AUDdf['Amount'].sum())
AUDdesc = AUDdf['Amount'].describe()
except ValueError:
pass
You can create an if statement which looks for the currencies presence first:
currency_set = set(list(df['Currency'].values))
if 'AUD' in currency_set:
AUDdf = df.loc[df['Currency'] == 'AUD']
AUDtable = pd.pivot_table(AUDdf,index=["Username"],values=["Amount"],aggfunc=np.sum)
AUDtable.loc['AUD Amounts Rejected Grand Total'] = (AUDdf['Amount'].sum())
AUDdesc = AUDdf['Amount'].describe()
1.Worst way to skip over the error/exception:
try:
<Your Code>
except:
pass
The above is probably the worst way because you want to know when an exception occur. using generic Except statements is bad practice because you want to avoid "catch em all" code. You want to be catching exceptions that you know how to handle. You want to know what specific exception occurred and you need to handle them on an exception-by-exception basis. Writing Generic except statements leads to missed bugs and tends to mislead while running the code to test.
Slightly worse way to handle the exception:
try:
<Your Code>
except Exception as e:
<Some code to handle an exception>
Still not optimal as it is still generic handling
Average way to handle it for your case:
try:
<Your Code>
except ValueError:
<Some code to handle this exception>
Other suggestion - Much Better Ways to deal with this:
1.You can get a set of the available columns at run time and aggregate based on if 'AUD' is in the list.
2.Clean your data set
You can use try and except where
try:
#your code here
except:
#some print statement
pass
I have the following code that is throwing up an out of range error on the barcode looping section of the below code.
for each in data['articles']:
f.writerow([each['local']['name'],
each['information'][0]['barcodes'][0]['barcode']])
I wrote a try and except to catch and handle when a barcode is not present within the json I am parsing and this worked perfectly during testing using the print function however I have been having some trouble getting the try and except to work whilst trying to writerow to a csv file.
Does anyone have any suggestions or another method I could try to get this to work.
My try and accept which worked when testing using print was as follows:
for each in data['articles']:
print(each['local']['name'])
try:
print(each['information'][0]['barcodes'][0]['barcode'])
except:
"none"
Any help is much appreciated!
As komatiraju032 points out, one way of doing this is via get(), although if there are different elements of the dictionary that might have empty/incorrect values, it might get unwieldy to provide a default for each one. To do this via a try/except you might do:
for each in data['articles']:
row = [each['local']['name']]
try:
row.append(each['information'][0]['barcodes'][0]['barcode'])
except (IndexError, KeyError):
row.append("none")
f.writerow(row)
This will give you that "none" replacement value regardless of which of those lists/dicts is missing the requested index/key, since any of those lookups might raise but they'll all end up at the same except.
Use dict.get() method. It will return None if key not exist
res = each['information'][0]['barcodes'][0].get('barcode')
Hi I have looked at many answers to this but I'm not sure what to do. My code is looking at a list and I think when it hits the column headings, I get this error (ValueError)
but if I can get through the headings, I know it will work - Here's my code
your_price = [float(i.get_attribute('value')) for I in driver.find_elements_by_xpath("//input[#maxlength='23']")]
Suggestions?
// not sure how iterating your data is controlled. try to wrap each increment
in a try/catch/finally - might gracefully skip the headers
try
your_price = [float(i.get_attribute('value')) for I in
driver.find_elements_by_xpath("//input[#maxlength='23']")]
catch/except
print value to log as a string data that caused the exception
end
I am using python 3. I use database to lookup the country of IP, if the IP is not in the database, return None or AAA. After all process, show the return result (either a country name or None or AAA ) in a new column on the data frame, Specifically, I have three columns that are date time and IP in the data frame, I would like to add a new column "code1" that shows the country name or None of this IP.
I add error exception in the code, however, it doesn't work. The code and error message are as below. Can anyone help?
The following is the report when I add "from geoip2.errors import AddressNotFoundError" to my code. I guess it means when there is address not found in the database, it return nothing rather a "none" (see, there is a empty square brackets), therefore, when I use df['code1']=code1, it reports the number of value is not equal to the number of index. (I am not sure).
In fact,my aim is to add a column to my original data frame that report the country of each ip or none if it is not in the database. Is there any other way to do so instead of " df['code1']=code1 "? Any help will be appreciated. Thanks
Exceptions are just like any other object in Python. They have to be defined somewhere. In this case, AddressNotFoundError is not defined so the interpreter has no idea what it means.
It has to be imported:
from geoip2.errors import AddressNotFoundError
or
import geoip2.errors.AddressNotFoundError
See relevant part of geoip2 documentation.
You can just leave out the AddressNotFoundError and instead do
try:
response1 = reader.country(row1)
code1.append(response1.country.iso_code)
except:
response1 = None
but if you really want to just except the AddressNotFoundError then at the top do
import geoip.errors.AddressNotFoundError
I have a directory where csv files are located. The code reads the files and creates histograms based on the data in the files.
I have made this a command prompt code where I can enter the arguments and the code will look through the csv files to see if the arguments I listed are there. I am trying to make it so that an error message comes up when I misspell a command. The following code works if the first argument is spelled correctly and the second is not, but does not display an error message if the first is misspelled and the second is correct. What's wrong?
Example: python untitled14.py "Folder" Are Perimeter DOES NOT DISPLAY ERROR MESSAGE FOR ARE
BUT python untitled14.py "Folder" Perimeter Are DOES DISPLAY ERROR FOR ARE
for x in arguments:
found_match = False
for column in df:
os.chdir(directory)
if x.endswith(column):
found_match = True
#histogram code
continue
else:
pass
if found_match==False:
print files+" " + x + " does not exist"
You have unnecessary things (and some other questionable things) in your loop logic. For example, the three lines continue; else: pass do literal nothing.
The best thing to do would be to refactor your code to call a function that would return True if all the arguments validated. You didn't provide enough code for that, so I would clean the whole thing up with:
for x in arguments:
for column in df:
os.chdir(directory)
if x.endswith(column):
#histogram code
break
else:
print "{0} {1} does not exist".format(files,x)
break #or not, depending on what you want to do
This takes advantage of the somewhat rarely-used for/else to do something if the for loop did not break - which, in your case, is an error.
If you want to really make this re-usable, you should raise an Exception instead of just printing on an error.