I have a .txt file that is being written to by a python script.
Adam,3,2,4
Sorin,3,2,4
Sorin,0,0,0
new_record = studentName+","+str(Score1) +","+str(Score2) +","+str(Score3)
student_class = 0
while student_class != 1 or student_class != 2 or student_class != 3:
student_class=input("What class are you in?(1/2/3): ")
if student_class == "1":
file=open("Class1.txt", "a+")
file.write(new_record)
file.write("\n")
file.close()
with open("Class1.txt", 'r') as fp:
for count, line in enumerate(fp):
pass
break
I want the scores to be overwritten if the student name is the same. For example if I run the script again, and Sorin gets a score of "3,3,3" the .txt file would look like this:
Adam,3,2,4
Sorin,3,2,4
Sorin,0,0,0
Sorin 3,3,3
However I want it to turn out like this:
Adam,3,2,4
Sorin 3,3,3
There are some things missing in your code, like how we know which student we are working on, etc.
But either way, this is the approach I would take if the files you are working on are not too big, as the file contents will be stored in memory while editing.
It uses a StringIO as intermediary location where the rows are appended, except if the name matches the current student, and then the content of the StringIO as put in place of the original file.
Starting with:
Adam,3,2,4
Sorin,3,2,4
Sorin,0,0,0
And running the following
import csv
from io import StringIO
current_student = "Sorin"
current_scores = (3, 3, 3)
# obtain a temporary file-like object in memory with a csv writer
with StringIO() as f_tmp:
writer = csv.writer(f_tmp)
# open the input file for reading with a csv reader
with open("/tmp/classes.csv", "r", newline="") as f_in:
reader = csv.reader(f_in)
for row in reader:
# skip the rows of current_student
if row[0] == current_student:
continue
writer.writerow(row)
# add current_student and their scores
writer.writerow((current_student,) + current_scores)
# open the input file for writing
with open("/tmp/classes.csv", "w") as f_out:
f_out.write(f_tmp.getvalue())
You get
Adam,3,2,4
Sorin,3,3,3
I would like to parse an .ubx File(=my input file). This file contains many different NMEA sentences as well as raw receiver data. The output file should just contain informations out of GGA sentences. This works fine as far as the .ubx File does not contain any raw messages. However if it contains raw data
I get the following error:
Traceback (most recent call last):
File "C:...myParser.py", line 25, in
for row in reader:
Error: line contains NULL byte
My code looks like this:
import csv
from datetime import datetime
import math
# adapt this to your file
INPUT_FILENAME = 'Rover.ubx'
OUTPUT_FILENAME = 'out2.csv'
# open the input file in read mode
with open(INPUT_FILENAME, 'r') as input_file:
# open the output file in write mode
with open(OUTPUT_FILENAME, 'wt') as output_file:
# create a csv reader object from the input file (nmea files are basically csv)
reader = csv.reader(input_file)
# create a csv writer object for the output file
writer = csv.writer(output_file, delimiter=',', lineterminator='\n')
# write the header line to the csv file
writer.writerow(['Time','Longitude','Latitude','Altitude','Quality','Number of Sat.','HDOP','Geoid seperation','diffAge'])
# iterate over all the rows in the nmea file
for row in reader:
if row[0].startswith('$GNGGA'):
time = row[1]
# merge the time and date columns into one Python datetime object (usually more convenient than having both separately)
date_and_time = datetime.strptime(time, '%H%M%S.%f')
date_and_time = date_and_time.strftime('%H:%M:%S.%f')[:-6] #
writer.writerow([date_and_time])
My .ubx file looks like this:
$GNGSA,A,3,16,25,29,20,31,26,05,21,,,,,1.30,0.70,1.10*10
$GNGSA,A,3,88,79,78,81,82,80,72,,,,,,1.30,0.70,1.10*16
$GPGSV,4,1,13,02,08,040,17,04,,,47,05,18,071,44,09,02,348,24*49
$GPGSV,4,2,13,12,03,118,24,16,12,298,36,20,15,118,30,21,44,179,51*74
$GPGSV,4,3,13,23,06,324,35,25,37,121,47,26,40,299,48,29,60,061,49*73
$GPGSV,4,4,13,31,52,239,51*42
$GLGSV,3,1,10,65,07,076,24,70,01,085,,71,04,342,34,72,13,029,35*64
$GLGSV,3,2,10,78,35,164,41,79,75,214,48,80,34,322,46,81,79,269,49*64
$GLGSV,3,3,10,82,28,235,52,88,39,043,43*6D
$GNGLL,4951.69412,N,00839.03672,E,124610.00,A,D*71
$GNGST,124610.00,12,,,,0.010,0.010,0.010*4B
$GNZDA,124610.00,03,07,2016,00,00*79
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AÝ$GNRMC,124611.00,A,4951.69413,N,00839.03672,E,0.009,,030716,,,D*62
$GNVTG,,T,,M,0.009,N,0.016,K,D*36
$GNGNS,124611.00,4951.69413,N,00839.03672,E,RR,15,0.70,162.5,47.6,1.0,0000*42
$GNGGA,124611.00,4951.69413,N,00839.03672,E,4,12,0.70,162.5,M,47.6,M,1.0,0000*6A
$GNGSA,A,3,16,25,29,20,31,26,05,21,,,,,1.31,0.70,1.10*11
$GNGSA,A,3,88,79,78,81,82,80,72,,,,,,1.31,0.70,1.10*17
$GPGSV,4,1,13,02,08,040,18,04,,,47,05,18,071,44,09,02,348,21*43
$GPGSV,4,2,13,12,03,118,24,16,
I already searched for similar problems. However I was not able to find a solution which workes for me.
I ended up with code like that:
import csv
def unfussy_reader(csv_reader):
while True:
try:
yield next(csv_reader)
except csv.Error:
# log the problem or whatever
print("Problem with some row")
continue
if __name__ == '__main__':
#
# Generate malformed csv file for
# demonstration purposes
#
with open("temp.csv", "w") as fout:
fout.write("abc,def\nghi\x00,klm\n123,456")
#
# Open the malformed file for reading, fire up a
# conventional CSV reader over it, wrap that reader
# in our "unfussy" generator and enumerate over that
# generator.
#
with open("Rover.ubx") as fin:
reader = unfussy_reader(csv.reader(fin))
for n, row in enumerate(reader):
fout.write(row[0])
However I was not able to simply write a file containing just all the rows read in with the unfuss_reader wrapper using the above code.
Would be glad if you could help me.
Here is an Image of how the .ubx file looks in notepad++image
Thanks!
I am not quite sure but your file looks pretty binary. You should try to open it as such
with open(INPUT_FILENAME, 'rb') as input_file:
It seems like you did not open the file with correct coding format.
So the raw message cannot be read correctly.
If it is encoded as UTF8, you need to open the file with coding option:
with open(INPUT_FILENAME, 'r', newline='', encoding='utf8') as input_file
Hey if anyone else has this proglem to read in NMEA sentences of uBlox .ubx files
this pyhton code worked for me:
def read_in():
with open('GNGGA.txt', 'w') as GNGGA:
with open('GNRMC.txt','w') as GNRMC:
with open('rover.ubx', 'rb') as f:
for line in f:
#print line
if line.startswith('$GNGGA'):
#print line
GNGGA.write(line)
if line.startswith('$GNRMC'):
GNRMC.write(line)
read_in()
You could also use the gnssdump command line utility which is installed with the PyGPSClient and pygnssutils Python packages.
e.g.
gnssdump filename=Rover.ubx msgfilter=GNGGA
See gnssdump -h for help.
Alternatively if you want a simple Python script you could use the pyubx2 Python package, e.g.
from pyubx2 import UBXReader
with open("Rover.ubx", "rb") as stream:
ubr = UBXReader(stream)
for (_, parsed_data) in ubr.iterate():
if parsed_data.identity in ("GNGGA", "GNRMC"):
print(parsed_data)
I am trying to append values to a json file. How can i append the data? I have been trying so many ways but none are working ?
Code:
def all(title,author,body,type):
title = "hello"
author = "njas"
body = "vgbhn"
data = {
"id" : id,
"author": author,
"body" : body,
"title" : title,
"type" : type
}
data_json = json.dumps(data)
#data = ast.literal_eval(data)
#print data_json
if(os.path.isfile("offline_post.json")):
with open('offline_post.json','a') as f:
new = json.loads(f)
new.update(a_dict)
json.dump(new,f)
else:
open('offline_post.json', 'a')
with open('offline_post.json','a') as f:
new = json.loads(f)
new.update(a_dict)
json.dump(new,f)
How can I append data to json file when this function is called?
I suspect you left out that you're getting a TypeError in the blocks where you're trying to write the file. Here's where you're trying to write:
with open('offline_post.json','a') as f:
new = json.loads(f)
new.update(a_dict)
json.dump(new,f)
There's a couple of problems here. First, you're passing a file object to the json.loads command, which expects a string. You probably meant to use json.load.
Second, you're opening the file in append mode, which places the pointer at the end of the file. When you run the json.load, you're not going to get anything because it's reading at the end of the file. You would need to seek to 0 before loading (edit: this would fail anyway, as append mode is not readable).
Third, when you json.dump the new data to the file, it's going to append it to the file in addition to the old data. From the structure, it appears you want to replace the contents of the file (as the new data contains the old data already).
You probably want to use r+ mode, seeking back to the start of the file between the read and write, and truncateing at the end just in case the size of the data structure ever shrinks.
with open('offline_post.json', 'r+') as f:
new = json.load(f)
new.update(a_dict)
f.seek(0)
json.dump(new, f)
f.truncate()
Alternatively, you can open the file twice:
with open('offline_post.json', 'r') as f:
new = json.load(f)
new.update(a_dict)
with open('offline_post.json', 'w') as f:
json.dump(new, f)
This is a different approach, I just wanted to append without reloading all the data. Running on a raspberry pi so want to look after memory. The test code -
import os
json_file_exists = 0
filename = "/home/pi/scratch_pad/test.json"
# remove the last run json data
try:
os.remove(filename)
except OSError:
pass
count = 0
boiler = 90
tower = 78
while count<10:
if json_file_exists==0:
# create the json file
with open(filename, mode = 'w') as fw:
json_string = "[\n\t{'boiler':"+str(boiler)+",'tower':"+str(tower)+"}\n]"
fw.write(json_string)
json_file_exists=1
else:
# append to the json file
char = ""
boiler = boiler + .01
tower = tower + .02
while(char<>"}"):
with open(filename, mode = 'rb+') as f:
f.seek(-1,2)
size=f.tell()
char = f.read()
if char == "}":
break
f.truncate(size-1)
with open(filename, mode = 'a') as fw:
json_string = "\n\t,{'boiler':"+str(boiler)+",'tower':"+str(tower)+"}\n]"
fw.seek(-1, os.SEEK_END)
fw.write(json_string)
count = count + 1
I have a csv file with several hundred organism IDs and a second csv file with several thousand organism IDs and additional characteristics (taxonomic information, abundances per sample, etc)
I am trying to write a code that will extract the information from the larger csv using the smaller csv file as a reference. Meaning it will look at both smaller and larger files, and if the IDs are in both files, it will extract all the information form the larger file and write that in a new file (basically write the entire row for that ID).
so far I have written the following, and while the code does not error out on me, I get a blank file in the end and I don't exactly know why. I am a graduate student that knows some simple coding but I'm still very much a novice,
thank you
import sys
import csv
import os.path
SparCCnames=open(sys.argv[1],"rU")
OTU_table=open(sys.argv[2],"rU")
new_file=open(sys.argv[3],"w")
Sparcc_OTUs=csv.writer(new_file)
d=csv.DictReader(SparCCnames)
ids=csv.DictReader(OTU_table)
for record in ids:
idstopull=record["OTUid"]
if idstopull[0]=="OTUid":
continue
if idstopull[0] in d:
new_id.writerow[idstopull[0]]
SparCCnames.close()
OTU_table.close()
new_file.close()
I'm not sure what you're trying to do in your code but you can try this:
def csv_to_dict(csv_file_path):
csv_file = open(csv_file_path, 'rb')
csv_file.seek(0)
sniffdialect = csv.Sniffer().sniff(csv_file.read(10000), delimiters='\t,;')
csv_file.seek(0)
dict_reader = csv.DictReader(csv_file, dialect=sniffdialect)
csv_file.seek(0)
dict_data = []
for record in dict_reader:
dict_data.append(record)
csv_file.close()
return dict_data
def dict_to_csv(csv_file_path, dict_data):
csv_file = open(csv_file_path, 'wb')
writer = csv.writer(csv_file, dialect='excel')
headers = dict_data[0].keys()
writer.writerow(headers)
# headers must be the same with dat.keys()
for dat in dict_data:
line = []
for field in headers:
line.append(dat[field])
writer.writerow(line)
csv_file.close()
if __name__ == "__main__":
big_csv = csv_to_dict('/path/to/big_csv_file.csv')
small_csv = csv_to_dict('/path/to/small_csv_file.csv')
output = []
for s in small_csv:
for b in big_csv:
if s['id'] == b['id']:
output.append(b)
if output:
dict_to_csv('/path/to/output.csv', output)
else:
print "Nothing."
Hope that will help.
You need to read the data into a data structure, assuming OTUid is unique you can store this into a dictionary for fast lookup:
with open(sys.argv[1],"rU") as SparCCnames:
d = csv.DictReader(SparCCnames)
fieldnames = d.fieldnames
data = {i['OTUid']: i for i in d}
with open(sys.argv[2],"rU") as OTU_table, open(sys.argv[3],"w") as new_file:
Sparcc_OTUs = csv.DictWriter(new_file, fieldnames)
ids = csv.DictReader(OTU_table)
for record in ids:
if record['OTUid'] in data:
Sparcc_OTUs.writerow(data[record['OTUid']])
Thank you everyone for your help. I played with things and consulted with an advisor, and finally got a working script. I am posting it in case it helps someone else in the future.
Thanks!
import sys
import csv
input_file = csv.DictReader(open(sys.argv[1], "rU")) #has all info
ref_list = csv.DictReader(open(sys.argv[2], "rU")) #reference list
output_file = csv.DictWriter(
open(sys.argv[3], "w"), input_file.fieldnames) #to write output file with headers
output_file.writeheader() #write headers in output file
white_list={} #create empty dictionary
for record in ref_list: #for every line in my reference list
white_list[record["Sample_ID"]] = None #store into the dictionary the ID's as keys
for record in input_file: #for every line in my input file
record_id = record["Sample_ID"] #store ID's into variable record_id
if (record_id in white_list): #if the ID is in the reference list
output_file.writerow(record) #write the entire row into a new file
else: #if it is not in my reference list
continue #ignore it and continue iterating through the file