I have a lot of huge CSV files, some of them contain ill encoded characters: in vi, I see things like "<8f>" or "<8e>", for example.
First, I wanted to search and replace (:%s) all the characters, but it will be a very long process because I will have to do this everytime I have to handle a file, and I'm not always sure whether new characters are here.
Is it possible to detect such characters, so that I can extract lines containing ill encoded characters?
A simple command may exist, taking a file for argument and creating a file containing only the lines with a problem.
I don't know if I explain me very well...
Thanks in advance!
You could use :g/char/p [vim] to print all the lines in a given file, or the bash utility grep:
grep -lr 'char1\|char2\|char2' .
Will output all the files in a directory containing any of the chars you have listed (the -r makes it recursive and the -l lists only the filenames, rather than all the line matches.
I want to grep for a string which I know exists in my files. However, the source it comes from managed to change the number of whitespaces so that the content per se is identical in the string, but the length differs. => ordinary grep does not find it. Is there a way to adjust for it?
I dont's see a system behind the additional whitespace effect
Here's the original string
4FD0-A tr|A5ZLA0|A5ZLA0_9BACE Bacterial
and here's the modified string
4FD0-A tr|A5ZLA0|A5ZLA0_9BACE Bacterial
I believe that egrep would be your friend here. Try the following command:
egrep '4FD0-A\s+tr[|]A5ZLA0[|]A5ZLA0_9BACE\s+Bacterial' filename
I used a rather simple pattern for my example. Feel free to change it to suit.
You can use the "one or more" + operator. For example
grep '^4FD0-A\s\+tr|' myfile
The \s searches for any whitespace. If you want to limit it to only spaces just use a single space in place of the \s
You can use all kind of utilities for deleting spaces.
Try this:
cat file |tr -s '\ ' | grep '4FD0-A tr|A5ZLA0|A5ZLA0_9BACE Bacterial'
I have a list with English words (1 in each line, around 100.000)-> a.txt and a b.txt contains strings (around 50.000 line, one string in each line, can contain pure words, word+something, garbage). I would like to know which strings from b.txt contains English words only (without any additional chars).
Can I do this with grep?
Example:
a.txt:
apple
pie
b.txt:
applepie
applebs
bspie
bsabcbs
Output:
c.txt:
applepie
Since your question is underspecified, maybe this answer can help as a shot in the dark to clarify your question:
c='cat b.txt'
while IFS='' read -e line
do
c="$c | grep '$line'"
done < a.txt
eval "$c" > c.txt
But this would also match a line like this is my apply on a pie. I don't know if that's what you want.
This is another try:
re=''
while IFS='' read -e line
do
re="$re${re:+|}$line"
done < a.txt
grep -E "^($re)*$" b.txt > c.txt
This will let pass only the lines which have nothing but a concatenation of these words. But it will also let pass things like 'appleapplepieapplepiepieapple'. Again, I don't know if this is what you want.
Given your latest explanation in the question I would propose another approach (because building such a list out of 100000+ words is not going to work).
A working approach for this amount of words could be to remove all recognized words from the text and see which lines get emptied in the process. This can easily be done iteratively without exploding the memory usage or other resources. It will take time, though.
cp b.txt inprogress.txt
while IFS='' read -e line
do
sed -i "s/$line//g" inprogress.txt
done < a.txt
for lineNumber in $(grep -n '^$' inprogress.txt | sed 's/://')
do
sed -n "${lineNumber}p" b.txt
done
rm inprogress.txt
But this still would not really solve your issue; consider if you have the words to and potato in your list, and removing the to would occur first, then this would leave a word pota in your text file, and pota is not a word which would then be removed.
You could address that issue by sorting your word file by word length (longest words first) but that still would be problematic in some cases of compound words, e. g. redart (being red + art) but dart would be removed first, so re would remain. If that is not in your word list, you would not recognize this word.
Actually, your problem is one of logical programming and natural language processing and probably does not fit to SO. You should have a look at the language Prolog which is designed around such problems as yours.
I will post this as an answer as well since I feel this is the correct answer to your specific question.
Your requirement is to find non-English words in a file (b.txt) based on a word list ( a.txt) which contains a list of English words. Based on the example in your question said word list does not contain compound words (e.g. applepie) but you would still like to match the file against compound words based on words in your word list (e.g. apple and pie).
There are two problem you are facing:
Not every permutation of words in a.txt will be a valid English compound word so just based on this your problem is already impossible to solve.
If you, nonetheless, were to attempt building a list of compound words yourself by compiling a list of all possible permutations you cannot easily do this because of the size of your wordlist (and resulting memory problems). You would most probably have to store your words in a more complex data structure, e.g. a tree, and build permutations on the fly by traversing the tree which is not doable in shell scripting.
Because of these points and your actual question being "can this be done with grep?" the answer is no, this is not possible.
As the title suggests I would like to grep a reasonably large (about 100MB) binary file, for a binary string - this binary string is just under 5K.
I've tried grep using the -P option, but this only seems to return matches when the pattern is only a few bytes - when I go up to about 100 bytes it no longer finds any matches.
I've also tried bgrep. This worked well originally, however, when I needed to extend the pattern to the length I have now I just get "invalid/empty search string" errors.
The irony is, in Windows I can use HxD to search the file and I finds it in a instance. What I really need though is a Linux command line tool.
Thanks for your help,
Simon
Say we have a couple of big binary data files. For a big one that shouldn't match, we create a 100MB file whose contents are all NUL bytes.
dd ibs=1 count=100M if=/dev/zero of=allzero.dat
For the one we want to match, create a hundred random megabytes.
#! /usr/bin/env perl
use warnings;
binmode STDOUT or die "$0: binmode: $!";
for (1 .. 100 * 1024 * 1024) {
print chr rand 256;
}
Execute it as ./mkrand >myfile.dat.
Finally, extract a known match into a file named pattern.
dd skip=42 count=10 if=myfile.dat of=pattern
I assume you want only the files that match (-l) and want your pattern to be treated literally (-F or --fixed-strings). I suspect you may have been running into a length limit with -P.
You may be tempted to use the --file=PATTERN-FILE option, but grep interprets the contents of PATTERN-FILE as newline-separated patterns, so in the likely case that your 5KB pattern contains newlines, you'll hit an encoding problem.
So hope your system's ARG_MAX is big enough and go for it. Be sure to quote the contents of pattern. For example:
$ grep -l --fixed-strings "$(cat pattern)" allzero.dat myfile.dat
myfile.dat
Try using grep -U which treats files as binary.
Also, how are you specifying the search pattern? It might just need escaping to survive shell parameter expansions
As the string you are searching is pretty long. You could benefit by an implementation of the Boyer-Moore search algorithm which is very efficient when search string is very long
http://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm
The wiki also has links to some sample code.
You might want to look at a simple Python script.
match= (b"..."
b"...."
b"..." ) # Some byte string literal of immense proportions
with open("some_big_file","rb") as source:
block= read(len(match))
while block != match:
byte= read(1)
if not byte: break
block= block[1:]+read(1)
This might work reliably under Linux as well as Windows.
I'm a non-computer science student doing a history thesis that involves determining the frequency of specific terms in a number of texts and then plotting these frequencies over time to determine changes and trends. While I have figured out how to determine word frequencies for a given text file, I am dealing with a (relatively, for me) large number of files (>100) and for consistencies sake would like to limit the words included in the frequency count to a specific set of terms (sort of like the opposite of a "stop list")
This should be kept very simple. At the end all I need to have is the frequencies for the specific words for each text file I process, preferably in spreadsheet format (tab delineated file) so that I can then create graphs and visualizations using that data.
I use Linux day-to-day, am comfortable using the command line, and would love an open-source solution (or something I could run with WINE). That is not a requirement however:
I see two ways to solve this problem:
Find a way strip-out all the words in a text file EXCEPT for the pre-defined list and then do the frequency count from there, or:
Find a way to do a frequency count using just the terms from the pre-defined list.
Any ideas?
I would go with the second idea. Here is a simple Perl program that will read a list of words from the first file provided and print a count of each word in the list from the second file provided in tab-separated format. The list of words in the first file should be provided one per line.
#!/usr/bin/perl
use strict;
use warnings;
my $word_list_file = shift;
my $process_file = shift;
my %word_counts;
# Open the word list file, read a line at a time, remove the newline,
# add it to the hash of words to track, initialize the count to zero
open(WORDS, $word_list_file) or die "Failed to open list file: $!\n";
while (<WORDS>) {
chomp;
# Store words in lowercase for case-insensitive match
$word_counts{lc($_)} = 0;
}
close(WORDS);
# Read the text file one line at a time, break the text up into words
# based on word boundaries (\b), iterate through each word incrementing
# the word count in the word hash if the word is in the hash
open(FILE, $process_file) or die "Failed to open process file: $!\n";
while (<FILE>) {
chomp;
while ( /-$/ ) {
# If the line ends in a hyphen, remove the hyphen and
# continue reading lines until we find one that doesn't
chop;
my $next_line = <FILE>;
defined($next_line) ? $_ .= $next_line : last;
}
my #words = split /\b/, lc; # Split the lower-cased version of the string
foreach my $word (#words) {
$word_counts{$word}++ if exists $word_counts{$word};
}
}
close(FILE);
# Print each word in the hash in alphabetical order along with the
# number of time encountered, delimited by tabs (\t)
foreach my $word (sort keys %word_counts)
{
print "$word\t$word_counts{$word}\n"
}
If the file words.txt contains:
linux
frequencies
science
words
And the file text.txt contains the text of your post, the following command:
perl analyze.pl words.txt text.txt
will print:
frequencies 3
linux 1
science 1
words 3
Note that breaking on word boundaries using \b may not work the way you want in all cases, for example, if your text files contain words that are hyphenated across lines you will need to do something a little more intelligent to match these. In this case you could check to see if the last character in a line is a hyphen and, if it is, just remove the hyphen and read another line before splitting the line into words.
Edit: Updated version that handles words case-insensitively and handles hyphenated words across lines.
Note that if there are hyphenated words, some of which are broken across lines and some that are not, this won't find them all because it only removed hyphens at the end of a line. In this case you may want to just remove all hyphens and match words after the hyphens are removed. You can do this by simply adding the following line right before the split function:
s/-//g;
I do this sort of thing with a script like following (in bash syntax):
for file in *.txt
do
sed -r 's/([^ ]+) +/\1\n/g' "$file" \
| grep -F -f 'go-words' \
| sort | uniq -c > "${file}.frq"
done
You can tweak the regex you use to delimit individual words; in the example I just treat whitespace as the delimiter. The -f argument to grep is a file that contains your words of interest, one per line.
First familiarize yourself with lexical analysis and how to write a scanner generator specification. Read the introductions to using tools like YACC, Lex, Bison, or my personal favorite, JFlex. Here you define what constitutes a token. This is where you learn about how to create a tokenizer.
Next you have what is called a seed list. The opposite of the stop list is usually referred to as the start list or limited lexicon. Lexicon would also be a good thing to learn about. Part of the app needs to load the start list into memory so it can be quickly queried. The typical way to store is a file with one word per line, then read this in at the start of the app, once, into something like a map. You might want to learn about the concept of hashing.
From here you want to think about the basic algorithm and the data structures necessary to store the result. A distribution is easily represented as a two dimensional sparse array. Learn the basics of a sparse matrix. You don't need 6 months of linear algebra to understand what it does.
Because you are working with larger files, I would advocate a stream-based approach. Don't read in the whole file into memory. Read it as a stream into the tokenizer that produces a stream of tokens.
In the next part of the algorithm think about how to transform the token list into a list containing only the words you want. If you think about it, the list is in memory and can be very large, so it is better to filter out non-start-words at the start. So at the critical point where you get a new token from the tokenizer and before adding it to the token list, do a lookup in the in-memory start-words-list to see if the word is a start word. If so, keep it in the output token list. Otherwise ignore it and move to the next token until the whole file is read.
Now you have a list of tokens only of interest. The thing is, you are not looking at other indexing metrics like position and case and context. Therefore, you really don't need a list of all tokens. You really just want a sparse matrix of distinct tokens with associated counts.
So,first create an empty sparse matrix. Then think about the insertion of the newly found token during parsing. When it occurs, increment its count if its in the list or otherwise insert a new token with a count of 1. This time, at the end of parsing the file, you have a list of distinct tokens, each with a frequency of at least 1.
That list is now in-mem and you can do whatever you want. Dumping it to a CSV file would be a trivial process of iterating over the entries and writing each entry per line with its count.
For that matter, take a look at the non-commercial product called "GATE" or a commercial product like TextAnalyst or products listed at http://textanalysis.info
I'm guessing that new files get introduced over time, and that's how things change?
I reckon your best bet would be to go with something like your option 2. There's not much point pre-processing the files, if all you want to do is count occurrences of keywords. I'd just go through each file once, counting each time a word in your list appears. Personally I'd do it in Ruby, but a language like perl or python would also make this task pretty straightforward. E.g., you could use an associative array with the keywords as the keys, and a count of occurrences as the values. (But this might be too simplistic if you need to store more information about the occurrences).
I'm not sure if you want to store information per file, or about the whole dataset? I guess that wouldn't be too hard to incorporate.
I'm not sure about what to do with the data once you've got it -- exporting it to a spreadsheet would be fine, if that gives you what you need. Or you might find it easier in the long-run just to write a bit of extra code that displays the data nicely for you. Depends on what you want to do with the data (e.g. if you want to produce just a few charts at the end of the exercise and put them into a report, then exporting to CSV would probably make most sense, whereas if you want to generate a new set of data every day for a year then building a tool to do that automatically is almost certainly the best idea.
Edit: I just figured out that since you're studying history, the chances are your documents are not changing over time, but rather reflect a set of changes that happened already. Sorry for misunderstanding that. Anyway, I think pretty much everything I said above still applies, but I guess you'll lean towards going with exporting to CSV or what have you rather than an automated display.
Sounds like a fun project -- good luck!
Ben
I'd do a "grep" on the files to find all the lines that contain your key words. (Grep -f can be used to specify an input file of words to search for (pipe the output of grep to a file). That will give you a list of lines which contain instances of your words. Then do a "sed" to replace your word separators (most likely spaces) with newlines, to give you a file of separate words (one word per line). Now run through grep again, with your same word list, except this time specify -c (to get a count of the lines with the specified words; i.e. a count of the occurrences of the word in the original file).
The two-pass method simply makes life easier for "sed"; the first grep should eliminate a lot of lines.
You can do this all in basic linux command-line commands. Once you're comfortable with the process, you can put it all into shell script pretty easily.
Another Perl attempt:
#!/usr/bin/perl -w
use strict;
use File::Slurp;
use Tie::File;
# Usage:
#
# $ perl WordCount.pl <Files>
#
# Example:
#
# $ perl WordCount.pl *.text
#
# Counts words in all files given as arguments.
# The words are taken from the file "WordList".
# The output is appended to the file "WordCount.out" in the format implied in the
# following example:
#
# File,Word1,Word2,Word3,...
# File1,0,5,3,...
# File2,6,3,4,...
# .
# .
# .
#
### Configuration
my $CaseSensitive = 1; # 0 or 1
my $OutputSeparator = ","; # another option might be "\t" (TAB)
my $RemoveHyphenation = 0; # 0 or 1. Careful, may be too greedy.
###
my #WordList = read_file("WordList");
chomp #WordList;
tie (my #Output, 'Tie::File', "WordCount.out");
push (#Output, join ($OutputSeparator, "File", #WordList));
for my $InFile (#ARGV)
{ my $Text = read_file($InFile);
if ($RemoveHyphenation) { $Text =~ s/-\n//g; };
my %Count;
for my $Word (#WordList)
{ if ($CaseSensitive)
{ $Count{$Word} = ($Text =~ s/(\b$Word\b)/$1/g); }
else
{ $Count{$Word} = ($Text =~ s/(\b$Word\b)/$1/gi); }; };
my $OutputLine = "$InFile";
for my $Word (#WordList)
{ if ($Count{$Word})
{ $OutputLine .= $OutputSeparator . $Count{$Word}; }
else
{ $OutputLine .= $OutputSeparator . "0"; }; };
push (#Output, $OutputLine); };
untie #Output;
When I put your question in the file wc-test and Robert Gamble's answer into wc-ans-test, the Output file looks like this:
File,linux,frequencies,science,words
wc-ans-test,2,2,2,12
wc-test,1,3,1,3
This is a comma separated value (csv) file (but you can change the separator in the script). It should be readable for any spreadsheet application. For plotting graphs, I would recommend gnuplot, which is fully scriptable, so you can tweak your output independently of the input data.
To hell with big scripts. If you're willing to grab all words, try this shell fu:
cat *.txt | tr A-Z a-z | tr -cs a-z '\n' | sort | uniq -c | sort -rn |
sed '/[0-9] /&, /'
That (tested) will give you a list of all words sorted by frequency in CSV format, easily imported by your favorite spreadsheet. If you must have the stop words then try inserting grep -w -F -f stopwords.txt into the pipeline (not tested).