Develop Reference

Splitting a list into strings

I have a variable that contains multiple lists. I'm trying to split the lists into strings so that I can add them to a csv file but I'm not sure how.
This is what I have been trying to do. For some reason, integrating through the different lists (i.e. participants) doesn't seem to work properly. It only uses the last list instead.
results = open("results.csv", "w")
strings = ""
for participant in contents:
for list in participant:
s = ""
for x in list:
s += x
strings += s
results.write(f"{strings}")

with open('results.csv', 'w') as f:
f.write('\n'.join(','.join(s) for s in [participant for participant in contest]))

Parsing a text file with line breaks in python

I have a text file with about 20 entries. They look like this:
~
England
Link: http://imgur.com/foobar.jpg
Capital: London
~
Iceland
Link: http://imgur.com/foobar2.jpg
Capital: Reykjavik
...
etc.
I would like to take these entries and turn them into a CSV.
There is a '~' separating each entry. I'm scratching my head trying to figure out how to go thru line by line and create the CSV values for each country. Can anyone give me a clue on how to go about this?

Use the libraries luke :)
I'm assuming your data is well formatted. Most real world data isn't that way. So, here goes a solution.
>>> content.split('~')
['\nEngland\nLink: http://imgur.com/foobar.jpg\nCapital: London\n', '\nIceland\nLink: http://imgur.com/foobar2.jpg\nCapital: Reykjavik\n', '\nEngland\nLink: http://imgur.com/foobar.jpg\nCapital: London\n', '\nIceland\nLink: http://imgur.com/foobar2.jpg\nCapital: Reykjavik\n']
For writing the CSV, Python has standard library functions.
>>> import csv
>>> csvfile = open('foo.csv', 'wb')
>>> fieldnames = ['Country', 'Link', 'Capital']
>>> writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
>>> for entry in entries:
... cols = entry.strip().splitlines()
... writer.writerow({'Country': cols[0], 'Link':cols[1].split(': ')[1], 'Capital':cols[2].split(':')[1]})
...
If your data is more semi structured or badly formatted, consider using a library like PyParsing.
Edit:
Second column contains URLs, so we need to handle the splits well.
>>> cols[1]
'Link: http://imgur.com/foobar2.jpg'
>>> cols[1].split(':')[1]
' http'
>>> cols[1].split(': ')[1]
'http://imgur.com/foobar2.jpg'

The way that I would do that would be to use the open() function using the syntax of:
f = open('NameOfFile.extensionType', 'a+')
Where "a+" is append mode. The file will not be overwritten and new data can be appended. You could also use "r+" to open the file in read mode, but would lose the ability to edit. The "+" after a letter signifies that if the document does not exist, it will be created. The "a+" I've never found to work without the "+".
After that I would use a for loop like this:
data = []
tmp = []
for line in f:
line.strip() #Removes formatting marks made by python
if line == '~':
data.append(tmp)
tmp = []
continue
else:
tmp.append(line)
Now you have all of the data stored in a list, but you could also reformat it as a class object using a slightly different algorithm.
I have never edited CSV files using python, but I believe you can use a loop like this to add the data:
f2 = open('CSVfileName.csv', 'w') #Can change "w" for other needs i.e "a+"
for entry in data:
for subentry in entry:
f2.write(str(subentry) + '\n') #Use '\n' to create a new line
From my knowledge of CSV that loop would create a single column of all of the data. At the end remember to close the files in order to save the changes:
f.close()
f2.close()
You could combine the two loops into one in order to save space, but for the sake of explanation I have not.

Extracting variable names and data from csv file using Python

I have a csv file that has each line formatted with the line name followed by 11 pieces of data. Here is an example of a line.
CW1,0,-0.38,2.04,1.34,0.76,1.07,0.98,0.81,0.92,0.70,0.64
There are 12 lines in total, each with a unique name and data.
What I would like to do is extract the first cell from each line and use that to name the corresponding data, either as a variable equal to a list containing that line's data, or maybe as a dictionary, with the first cell being the key.
I am new to working with inputting files, so the farthest I have gotten is to read the file in using the stock solution in the documentation
import csv
path = r'data.csv'
with open(path,'rb') as csvFile:
reader = csv.reader(csvFile,delimiter=' ')
for row in reader:
print(row[0])
I am failing to figure out how to assign each row to a new variable, especially when I am not sure what the variable names will be (this is because the csv file will be created by a user other than myself).
The destination for this data is a tool that I have written. It accepts lists as input such as...
CW1 = [0,-0.38,2.04,1.34,0.76,1.07,0.98,0.81,0.92,0.70,0.64]
so this would be the ideal end solution. If it is easier, and considered better to have the output of the file read be in another format, I can certainly re-write my tool to work with that data type.

As Scironic said in their answer, it is best to use a dict for this sort of thing.
However, be aware that dict objects do not have any "order" - the order of the rows will be lost if you use one. If this is a problem, you can use an OrderedDict instead (which is just what it sounds like: a dict that "remembers" the order of its contents):
import csv
from collections import OrderedDict as od
data = od() # ordered dict object remembers the order in the csv file
with open(path,'rb') as csvFile:
reader = csv.reader(csvFile, delimiter = ' ')
for row in reader:
data[row[0]] = row[1:] # Slice the row up into 0 (first item) and 1: (remaining)
Now if you go looping through your data object, the contents will be in the same order as in the csv file:
for d in data.values():
myspecialtool(*d)

You need to use a dict for these kinds of things (dynamic variables):
import csv
path = r'data.csv'
data = {}
with open(path,'rb') as csvFile:
reader = csv.reader(csvFile,delimiter=' ')
for row in reader:
data[row[0]] = row[1:]
dicts are especially useful for dynamic variables and are the best method to store things like this. to access you just need to use:
data['CW1']
This solution also means that if you add any extra rows in with new names, you won't have to change anything.
If you are desperate to have the variable names in the global namespace and not within a dict, use exec (N.B. IF ANY OF THIS USES INPUT FROM OUTSIDE SOURCES, USING EXEC/EVAL CAN BE HIGHLY DANGEROUS (rm * level) SO MAKE SURE ALL INPUT IS CONTROLLED AND UNDERSTOOD BY YOURSELF).
with open(path,'rb') as csvFile:
reader = csv.reader(csvFile,delimiter=' ')
for row in reader:
exec("{} = {}".format(row[0], row[1:])

In python, you can use slicing: row[1:] will contain the row, except the first element, so you could do:
>>> d={}
>>> with open("f") as f:
... c = csv.reader(f, delimiter=',')
... for r in c:
... d[r[0]]=map(int,r[1:])
...
>>> d
{'var1': [1, 3, 1], 'var2': [3, 0, -1]}
Regarding variable variables, check How do I do variable variables in Python? or How to get a variable name as a string in Python?. I would stick to dictionary though.

An alternative to using the proper csv library could be as follows:
path = r'data.csv'
csvRows = open(path, "r").readlines()
dataRows = [[float(col) for col in row.rstrip("\n").split(",")[1:]] for row in csvRows]
for dataRow in dataRows: # Where dataRow is a list of numbers
print dataRow
You could then call your function where the print statement is.
This reads the whole file in and produces a list of lines with trailing newlines. It then removes each newline and splits each row into a list of strings. It skips the initial column and calls float() for each entry. Resulting in a list of lists. It depends how important the first column is?

Python 2 - iterating through csv with determinating specific lines as dicitonary

I generated csv from multiple dictionaries (to be readable and editable too) with help of this question. Output is simple
//Dictionary
key,value
key2,value2
//Dictionary2
key4, value4
key5, value5
i want double backslash to be separator to create new dictionary, but every calling csv.reader(open("input.csv")) evaluates through lines so i have no use of:
import csv
dict = {}
for key, val in csv.reader(open("input.csv")):
dict[key] = val
Thanks for helping me out..
Edit: i made this piece of.. well "code".. I'll be glad if you can check it out and review:
#! /usr/bin/python
import csv
# list of dictionaries
l = []
# evalute throught csv
for row in csv.reader(open("test.csv")):
if row[0].startswith("//"):
# stripped "//" line is name for dictionary
n = row[0][2:]
# append stripped "//" line as name for dictionary
#debug
print n
l.append(n)
#debug print l[:]
elif len(row) == 2:
# debug
print "len(row) %s" % len(row)
# debug
print "row[:] %s" % row[:]
for key, val in row:
# print key,val
l[-1] = dic
dic = {}
dic[key] = val
# debug
for d in l:
print l
for key, value in d:
print key, value
unfortunately i got this Error:
DictName
len(row) 2
row[:] ['key', ' value']
Traceback (most recent call last):
File "reader.py", line 31, in <module>
for key, val in row:
ValueError: too many values to unpack

Consider not using CSV
First of all, your overall strategy to the data problem is probably not optimal. The less tabular your data looks, the less sense it makes to keep it in a CSV file (though your needs aren't too far out of the realm).
For example, it would be really easy to solve this problem using json:
import json
# First the data
data = dict(dict1=dict(key1="value1", key2="value2"),
dict2=dict(key3="value3", key4="value4"))
# Convert and write
js = json.dumps(data)
f = file("data.json", 'w')
f.write(js)
f.close()
# Now read back
f = file("data.json", 'r')
data = json.load(f)
print data
Answering the question as written
However, if you are really set on this strategy, you can do something along the lines suggested by jonrsharpe. You can't just use the csv module to do all the work for you, but actually have to go through and filter out (and split by) the "//" lines.
import csv
import re
def header_matcher(line):
"Returns something truthy if the line looks like a dict separator"
return re.match("//", line)
# Open the file and ...
f = open("data.csv")
# create some containers we can populate as we iterate
data = []
d = {}
for line in f:
if not header_matcher(line):
# We have a non-header row, so we make a new entry in our draft dictionary
key, val = line.strip().split(',')
d[key] = val
else:
# We've hit a new header, so we should throw our draft dictionary in our data list
if d:
# ... but only if we actually have had data since the last header
data.append(d)
d = {}
# The very last chunk will need to be captured as well
if d:
data.append(d)
# And we're done...
print data
This is quite a bit messier, and if there is any chance of needed to escape commas, it will get messier still. If you needed, you could probably find a clever way of chunking up the file into generators that you read with CSV readers, but it won't be particularly clean/easy (I started an approach like this but it looked like pain...). This is all a testament to your approach likely being the wrong way to store this data.
An alternative if you're set on CSV
Another way to go if you really want CSV but aren't stuck on the exact data format you specify: Add a column in the CSV file corresponding to the dictionary the data should go into. Imagine a file (data2.csv) that looks like this:
dict1,key1,value1
dict1,key2,value2
dict2,key3,value3
dict2,key4,value4
Now we can do something cleaner, like the following:
import csv
data = dict()
for chunk, key, val in csv.reader(file('test2.csv')):
try:
# If we already have a dict for the given chunk id, this should add the key/value pair
data[chunk][key] = val
except KeyError:
# Otherwise, we catch the exception and add a fresh dictionary with the key/value pair
data[chunk] = {key: val}
print data
Much nicer...
The only good argument for doing something closer to what you have in mind over this is if there is LOTS of data, and space is a concern. But that is not very likely to be case in most situations.
And pandas
Oh yes... one more possible solution is pandas. I haven't used it much yet, so I'm not as much help, but there is something along the lines of a group_by function it provides, which would let you group by the first column if you end up structuring the data as in the the 3-column CSV approach.

I decided to use json instead
Reading this is easier for the program and there's no need to filter text. For generating the data inside database in external file.json will serve python program.
#! /usr/bin/python
import json
category1 = {"server name1":"ip address1","server name2":"ip address2"}
category2 = {"server name1":"ip address1","server name1":"ip address1"}
servers = { "category Alias1":category1,"category Alias2":category2}
js = json.dumps(servers)
f = file("servers.json", "w")
f.write(js)
f.close()
# Now read back
f = file("servers.json", "r")
data = json.load(f)
print data
So the output is dictionary containing keys for categories and as values are another dictionaries. Exactly as i wanted.

Python csvreader separate lines

I am using the csv module for Python. I have had a good look at the CSV File Reading and Writing guide. I want to write a loop that runs through each row in the CSV file and assigns each row do a different variable. Does anyone have any ideas on this?
I am aware that there is a .next() and .line_num, I didn't think that these would be suitable in this case although I might be wrong.
Currently I have the following code, which print out the whole CSV file:
print_csv = csv.reader(open(csv_name, 'rb'), delimiter=' ', quotechar='|')
for row in print_csv:
print ', '.join(row)
[EDIT]
I am now aware, from this question thread, that the best way to do this will depend on what the first line is going to be used for.
What I want to do with the first line of the CSV file is to check whether it is in the correct format. This would involve:
checking to see whether it has the expected number of columns
checking to see whether the column headers have the correct name
checking to see whether to columns are in the correct order.

1.- Fast Answer
Instead of setting different independent variables you could do:
mydict = {}
for idx, item in enumerate(reader):
mydict['var%i' %idx] = item
then you call your var like:
mydict['var0']
Or still shorter in py3k:
mydict = {'var%i' %idx : item for idx, item in enumerate(reader)}
But this doesnt have much sense applied this way
As a commenter said this is not different than doing directly:
mylist = list(reader)
and then
mylist[0] # instead of 'var0'
and this option is much better.
The dictionary strategy is best suited when you extract the dictionary key from the very same reader line. For example, if it were at pos pos 0,:
mydict = {item[0] : item for item in reader}
2.- The Proper Answer
But if what you want is simply to check the format of the first line (maybe to calculate the space you need for printing), the method could be:
line = reader.next()
like_this = check_how_is_my(line)
if like_this == 'something_long':
spaces = 23
else:
spaces = 0
while True:
try:
print_with_spaces(line, spaces)
reader.next()
except StopIteration:
break

Well, you can obviously do:
var1 = reader.next()
var2 = reader.next()
var3 = reader.next()
var4 = reader.next()
var5 = reader.next()
or any variation thereof. This is not my favorite coding style, but it works.