I have a bunch of gzipped CSV files that I'd like to open for inspection using Python's built in CSV reader. I'd like to do this without having first to manually unzip them to disk. I guess I want to somehow get a stream to the uncompressed data, and pass this into the CSV reader. Is this possible in Python?
Use the gzip module:
with gzip.open(filename, mode='rt') as f:
reader = csv.reader(f)
#...
I've tried the above version for writing and reading and it didn't work in Python 3.3 due to "bytes" error. However, after some trial and error I could get the following to work. Maybe it also helps others:
import csv
import gzip
import io
with gzip.open("test.gz", "w") as file:
writer = csv.writer(io.TextIOWrapper(file, newline="", write_through=True))
writer.writerow([1, 2, 3])
writer.writerow([4, 5, 6])
with gzip.open("test.gz", "r") as file:
reader = csv.reader(io.TextIOWrapper(file, newline=""))
print(list(reader))
As amohr suggests, the following works as well:
import gzip, csv
with gzip.open("test.gz", "wt", newline="") as file:
writer = csv.writer(file)
writer.writerow([1, 2, 3])
writer.writerow([4, 5, 6])
with gzip.open("test.gz", "rt", newline="") as file:
reader = csv.reader(file)
print(list(reader))
a more complete solution:
import csv, gzip
class GZipCSVReader:
def __init__(self, filename):
self.gzfile = gzip.open(filename)
self.reader = csv.DictReader(self.gzfile)
def next(self):
return self.reader.next()
def close(self):
self.gzfile.close()
def __iter__(self):
return self.reader.__iter__()
now you can use it like this:
r = GZipCSVReader('my.csv')
for map in r:
for k,v in map:
print k,v
r.close()
EDIT: following the below comment, how about a simpler approach:
def gzipped_csv(filename):
with gzip.open(filename) as f:
r = csv.DictReader(f)
for row in r:
yield row
which let's you then
for row in gzipped_csv(filename):
for k, v in row:
print(k, v)
Related
I have data which is being accessed via http request and is sent back by the server in a comma separated format, I have the following code :
site= 'www.example.com'
hdr = {'User-Agent': 'Mozilla/5.0'}
req = urllib2.Request(site,headers=hdr)
page = urllib2.urlopen(req)
soup = BeautifulSoup(page)
soup = soup.get_text()
text=str(soup)
The content of text is as follows:
april,2,5,7
may,3,5,8
june,4,7,3
july,5,6,9
How can I save this data into a CSV file.
I know I can do something along the lines of the following to iterate line by line:
import StringIO
s = StringIO.StringIO(text)
for line in s:
But i'm unsure how to now properly write each line to CSV
EDIT---> Thanks for the feedback as suggested the solution was rather simple and can be seen below.
Solution:
import StringIO
s = StringIO.StringIO(text)
with open('fileName.csv', 'w') as f:
for line in s:
f.write(line)
General way:
##text=List of strings to be written to file
with open('csvfile.csv','wb') as file:
for line in text:
file.write(line)
file.write('\n')
OR
Using CSV writer :
import csv
with open(<path to output_csv>, "wb") as csv_file:
writer = csv.writer(csv_file, delimiter=',')
for line in data:
writer.writerow(line)
OR
Simplest way:
f = open('csvfile.csv','w')
f.write('hi there\n') #Give your csv text here.
## Python will convert \n to os.linesep
f.close()
You could just write to the file as you would write any normal file.
with open('csvfile.csv','wb') as file:
for l in text:
file.write(l)
file.write('\n')
If just in case, it is a list of lists, you could directly use built-in csv module
import csv
with open("csvfile.csv", "wb") as file:
writer = csv.writer(file)
writer.writerows(text)
I would simply write each line to a file, since it's already in a CSV format:
write_file = "output.csv"
with open(write_file, "wt", encoding="utf-8") as output:
for line in text:
output.write(line + '\n')
I can't recall how to write lines with line-breaks at the moment, though :p
Also, you might like to take a look at this answer about write(), writelines(), and '\n'.
To complement the previous answers, I whipped up a quick class to write to CSV files. It makes it easier to manage and close open files and achieve consistency and cleaner code if you have to deal with multiple files.
class CSVWriter():
filename = None
fp = None
writer = None
def __init__(self, filename):
self.filename = filename
self.fp = open(self.filename, 'w', encoding='utf8')
self.writer = csv.writer(self.fp, delimiter=';', quotechar='"', quoting=csv.QUOTE_ALL, lineterminator='\n')
def close(self):
self.fp.close()
def write(self, elems):
self.writer.writerow(elems)
def size(self):
return os.path.getsize(self.filename)
def fname(self):
return self.filename
Example usage:
mycsv = CSVWriter('/tmp/test.csv')
mycsv.write((12,'green','apples'))
mycsv.write((7,'yellow','bananas'))
mycsv.close()
print("Written %d bytes to %s" % (mycsv.size(), mycsv.fname()))
Have fun
What about this:
with open("your_csv_file.csv", "w") as f:
f.write("\n".join(text))
str.join() Return a string which is the concatenation of the strings in iterable.
The separator between elements is
the string providing this method.
In my situation...
with open('UPRN.csv', 'w', newline='') as out_file:
writer = csv.writer(out_file)
writer.writerow(('Name', 'UPRN','ADMIN_AREA','TOWN','STREET','NAME_NUMBER'))
writer.writerows(lines)
you need to include the newline option in the open attribute and it will work
https://www.programiz.com/python-programming/writing-csv-files
Here's my code, really simple stuff...
import csv
import json
csvfile = open('file.csv', 'r')
jsonfile = open('file.json', 'w')
fieldnames = ("FirstName","LastName","IDNumber","Message")
reader = csv.DictReader( csvfile, fieldnames)
out = json.dumps( [ row for row in reader ] )
jsonfile.write(out)
Declare some field names, the reader uses CSV to read the file, and the filed names to dump the file to a JSON format. Here's the problem...
Each record in the CSV file is on a different row. I want the JSON output to be the same way. The problem is it dumps it all on one giant, long line.
I've tried using something like for line in csvfile: and then running my code below that with reader = csv.DictReader( line, fieldnames) which loops through each line, but it does the entire file on one line, then loops through the entire file on another line... continues until it runs out of lines.
Any suggestions for correcting this?
Edit: To clarify, currently I have: (every record on line 1)
[{"FirstName":"John","LastName":"Doe","IDNumber":"123","Message":"None"},{"FirstName":"George","LastName":"Washington","IDNumber":"001","Message":"Something"}]
What I'm looking for: (2 records on 2 lines)
{"FirstName":"John","LastName":"Doe","IDNumber":"123","Message":"None"}
{"FirstName":"George","LastName":"Washington","IDNumber":"001","Message":"Something"}
Not each individual field indented/on a separate line, but each record on it's own line.
Some sample input.
"John","Doe","001","Message1"
"George","Washington","002","Message2"
The problem with your desired output is that it is not valid json document,; it's a stream of json documents!
That's okay, if its what you need, but that means that for each document you want in your output, you'll have to call json.dumps.
Since the newline you want separating your documents is not contained in those documents, you're on the hook for supplying it yourself. So we just need to pull the loop out of the call to json.dump and interpose newlines for each document written.
import csv
import json
csvfile = open('file.csv', 'r')
jsonfile = open('file.json', 'w')
fieldnames = ("FirstName","LastName","IDNumber","Message")
reader = csv.DictReader( csvfile, fieldnames)
for row in reader:
json.dump(row, jsonfile)
jsonfile.write('\n')
You can use Pandas DataFrame to achieve this, with the following Example:
import pandas as pd
csv_file = pd.DataFrame(pd.read_csv("path/to/file.csv", sep = ",", header = 0, index_col = False))
csv_file.to_json("/path/to/new/file.json", orient = "records", date_format = "epoch", double_precision = 10, force_ascii = True, date_unit = "ms", default_handler = None)
import csv
import json
file = 'csv_file_name.csv'
json_file = 'output_file_name.json'
#Read CSV File
def read_CSV(file, json_file):
csv_rows = []
with open(file) as csvfile:
reader = csv.DictReader(csvfile)
field = reader.fieldnames
for row in reader:
csv_rows.extend([{field[i]:row[field[i]] for i in range(len(field))}])
convert_write_json(csv_rows, json_file)
#Convert csv data into json
def convert_write_json(data, json_file):
with open(json_file, "w") as f:
f.write(json.dumps(data, sort_keys=False, indent=4, separators=(',', ': '))) #for pretty
f.write(json.dumps(data))
read_CSV(file,json_file)
Documentation of json.dumps()
I took #SingleNegationElimination's response and simplified it into a three-liner that can be used in a pipeline:
import csv
import json
import sys
for row in csv.DictReader(sys.stdin):
json.dump(row, sys.stdout)
sys.stdout.write('\n')
You can try this
import csvmapper
# how does the object look
mapper = csvmapper.DictMapper([
[
{ 'name' : 'FirstName'},
{ 'name' : 'LastName' },
{ 'name' : 'IDNumber', 'type':'int' },
{ 'name' : 'Messages' }
]
])
# parser instance
parser = csvmapper.CSVParser('sample.csv', mapper)
# conversion service
converter = csvmapper.JSONConverter(parser)
print converter.doConvert(pretty=True)
Edit:
Simpler approach
import csvmapper
fields = ('FirstName', 'LastName', 'IDNumber', 'Messages')
parser = CSVParser('sample.csv', csvmapper.FieldMapper(fields))
converter = csvmapper.JSONConverter(parser)
print converter.doConvert(pretty=True)
I see this is old but I needed the code from SingleNegationElimination however I had issue with the data containing non utf-8 characters. These appeared in fields I was not overly concerned with so I chose to ignore them. However that took some effort. I am new to python so with some trial and error I got it to work. The code is a copy of SingleNegationElimination with the extra handling of utf-8. I tried to do it with https://docs.python.org/2.7/library/csv.html but in the end gave up. The below code worked.
import csv, json
csvfile = open('file.csv', 'r')
jsonfile = open('file.json', 'w')
fieldnames = ("Scope","Comment","OOS Code","In RMF","Code","Status","Name","Sub Code","CAT","LOB","Description","Owner","Manager","Platform Owner")
reader = csv.DictReader(csvfile , fieldnames)
code = ''
for row in reader:
try:
print('+' + row['Code'])
for key in row:
row[key] = row[key].decode('utf-8', 'ignore').encode('utf-8')
json.dump(row, jsonfile)
jsonfile.write('\n')
except:
print('-' + row['Code'])
raise
Add the indent parameter to json.dumps
data = {'this': ['has', 'some', 'things'],
'in': {'it': 'with', 'some': 'more'}}
print(json.dumps(data, indent=4))
Also note that, you can simply use json.dump with the open jsonfile:
json.dump(data, jsonfile)
Use pandas and the json library:
import pandas as pd
import json
filepath = "inputfile.csv"
output_path = "outputfile.json"
df = pd.read_csv(filepath)
# Create a multiline json
json_list = json.loads(df.to_json(orient = "records"))
with open(output_path, 'w') as f:
for item in json_list:
f.write("%s\n" % item)
How about using Pandas to read the csv file into a DataFrame (pd.read_csv), then manipulating the columns if you want (dropping them or updating values) and finally converting the DataFrame back to JSON (pd.DataFrame.to_json).
Note: I haven't checked how efficient this will be but this is definitely one of the easiest ways to manipulate and convert a large csv to json.
As slight improvement to #MONTYHS answer, iterating through a tup of fieldnames:
import csv
import json
csvfilename = 'filename.csv'
jsonfilename = csvfilename.split('.')[0] + '.json'
csvfile = open(csvfilename, 'r')
jsonfile = open(jsonfilename, 'w')
reader = csv.DictReader(csvfile)
fieldnames = ('FirstName', 'LastName', 'IDNumber', 'Message')
output = []
for each in reader:
row = {}
for field in fieldnames:
row[field] = each[field]
output.append(row)
json.dump(output, jsonfile, indent=2, sort_keys=True)
def read():
noOfElem = 200 # no of data you want to import
csv_file_name = "hashtag_donaldtrump.csv" # csv file name
json_file_name = "hashtag_donaldtrump.json" # json file name
with open(csv_file_name, mode='r') as csv_file:
csv_reader = csv.DictReader(csv_file)
with open(json_file_name, 'w') as json_file:
i = 0
json_file.write("[")
for row in csv_reader:
i = i + 1
if i == noOfElem:
json_file.write("]")
return
json_file.write(json.dumps(row))
if i != noOfElem - 1:
json_file.write(",")
Change the above three parameter, everything will be done.
import csv
import json
csvfile = csv.DictReader('filename.csv', 'r'))
output =[]
for each in csvfile:
row ={}
row['FirstName'] = each['FirstName']
row['LastName'] = each['LastName']
row['IDNumber'] = each ['IDNumber']
row['Message'] = each['Message']
output.append(row)
json.dump(output,open('filename.json','w'),indent=4,sort_keys=False)
I have a list like this(python 3)
my_list = [["xxx","moon",150],["wordq","pop",3]]
and i save it on a csv using this code
import csv
myfile = open("pppp.csv", 'wb')
with open("pppp.csv", "w", newline='') as myfile:
wr = csv.writer(myfile, quoting=csv.QUOTE_NONE)
wr.writerows(list_of_DVDsuppliers)
now i need to export this csv in to my program as a list and change the data .
please help me ?
Just convert the data you get from reader() to a list:
data = csv.reader(open('example.csv','r'))
data = list(data)
print data
Unless you have a reason why you are using newline='', you can skip that and below code works with python 2.7,
import csv
my_list = [["xxx","moon",150],["wordq","pop",3]]
myfile = open("pppp.csv", 'wb')
with open("pppp.csv", "w") as myfile:
wr = csv.writer(myfile, quoting=csv.QUOTE_NONE)
wr.writerows(my_list)
data = csv.reader(open('pppp.csv','r'))
for row in data:
print row
This seems like it should be an easy fix, but so far a solution has eluded me. I have a single column csv file with non-ascii chars saved in utf-8 that I want to read in and store in a list. I'm attempting to follow the principle of the "Unicode Sandwich" and decode upon reading the file in:
import codecs
import csv
with codecs.open('utf8file.csv', 'rU', encoding='utf-8') as file:
input_file = csv.reader(file, delimiter=",", quotechar='|')
list = []
for row in input_file:
list.extend(row)
This produces the dread 'codec can't encode characters in position, ordinal not in range(128)' error.
I've also tried adapting a solution from this answer, which returns a similar error
def unicode_csv_reader(utf8_data, dialect=csv.excel, **kwargs):
csv_reader = csv.reader(utf8_data, dialect=dialect, **kwargs)
for row in csv_reader:
yield [unicode(cell, 'utf-8') for cell in row]
filename = 'inputs\encode.csv'
reader = unicode_csv_reader(open(filename))
target_list = []
for field1 in reader:
target_list.extend(field1)
A very similar solution adapted from the docs returns the same error.
def unicode_csv_reader(utf8_data, dialect=csv.excel):
csv_reader = csv.reader(utf_8_encoder(utf8_data), dialect)
for row in csv_reader:
yield [unicode(cell, 'utf-8') for cell in row]
def utf_8_encoder(unicode_csv_data):
for line in unicode_csv_data:
yield line.encode('utf-8')
filename = 'inputs\encode.csv'
reader = unicode_csv_reader(open(filename))
target_list = []
for field1 in reader:
target_list.extend(field1)
Clearly I'm missing something. Most of the questions that I've seen regarding this problem seem to predate Python 2.7, so an update here might be useful.
Your first snippet won't work. You are feeding unicode data to the csv reader, which (as documented) can't handle it.
Your 2nd and 3rd snippets are confused. Something like the following is all that you need:
f = open('your_utf8_encoded_file.csv', 'rb')
reader = csv.reader(f)
for utf8_row in reader:
unicode_row = [x.decode('utf8') for x in utf8_row]
print unicode_row
At it fails from the first char to read, you may have a BOM. Use codecs.open('utf8file.csv', 'rU', encoding='utf-8-sig') if your file is UTF8 and has a BOM at the beginning.
I'd suggest trying just:
input_file = csv.reader(open('utf8file.csv', 'r'), delimiter=",", quotechar='|')
or
input_file = csv.reader(open('utf8file.csv', 'rb'), delimiter=",", quotechar='|')
csv should be unicode aware, and it should just work.
im reading a csv file and then writing a new one:
import csv
with open('thefile.csv', 'rb') as f:
data = list(csv.reader(f))
import collections
counter = collections.defaultdict(int)
for row in data:
counter[row[11]] += 1
writer = csv.writer(open('/pythonwork/thefile_subset1.csv', 'w'))
for row in data:
if counter[row[11]] >= 500:
writer.writerow(row)
for some reason i cannot get the csv.writer to close the file. when i open the file it opens it as READ ONLY because it says that is still open.
how do i close thefile_subset1.csv after i am done with it?
with open('/pythonwork/thefile_subset1.csv', 'w') as outfile:
writer = csv.writer(outfile)
for row in data:
if counter[row[11]] >= 500:
writer.writerow(row)
You can break out the open command into its own variable, so that you can close it later.
f = open('/pythonwork/thefile_subset1.csv', 'w')
writer = csv.writer(f)
f.close()
csv.writer throws a ValueError if you try to write to a closed file.
close the file, not the csv writer. To do this, you'll need to open the file first before instantiating your writer rather than keeping it all in one line.
import csv
import collections
with open('thefile.csv', 'rb') as f:
data = list(csv.reader(f))
counter = collections.defaultdict(int)
for row in data:
counter[row[11]] += 1
f.close() # good idea to close if you're done with it
fSubset = open('/pythonwork/thefile_subset1.csv', 'w')
writer = csv.writer(fSubset)
for row in data:
if counter[row[11]] >= 500:
writer.writerow(row)
fSubset.close()
Also, I would suggest keeping your imports at the top of the script and closing the first file when you're done with it.
Force the writer to clean up:
del writer
Look at the difference:
with open('thefile.csv', 'rb') as f:
data = list(csv.reader(f))
vs:
writer = csv.writer(open('/pythonwork/thefile_subset1.csv', 'w'))