Load all files in a directory

hi all! im new to java and i was wondering if u can help me out!
ive wrote a small application which analysises words in a text file, and what i need to do is load all the files in a directory, rather than one at a time like in the following code. I understand that a loop is needed but i really dont know where to start! please help!
thanks for your time
oh also, is there a way of the system printing the filename rather than "this text is.."?
import java.io.BufferedReader;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.util.HashMap;
public class eval {
private String[] words;
private int[] values;
private int num;
private HashMap <String, Integer> hashMap;
private arrays a;
private String[] negwords;
private int[] negvalues;
private HashMap hashMap2;
private int negnum;
public eval() {
initiatemap();
BufferedReader in = null;
try {
in = new BufferedReader (new FileReader ("text.txt")); //id like this to load all files in a directory
String str;
String s;
while ((str = in.readLine()) != null)
str = str.replaceAll("[\\p{Punct}&&[^?????????????????????]]", " ");
String[]temp = str.split(" ");
for (int i = 0; i < temp.length; i++) {
if (hashMap.containsKey(temp)) {
num++;
for (int i = 0; i < temp.length; i++) {
if (hashMap2.containsKey(temp[i])) {
negnum++;
if (num > 0 && negnum > 0 ){
double total = num + negnum;
double txt1 = round((num/total)*100, 2);
if (txt1 < 50)
System.out.println("This text is " + txt1 + "% positive and is therefore not a happy text.");
else if (txt1 >= 50 && txt1 <=65)
System.out.println("This text is " + txt1 + "% positive, but does contain " + (100 - txt1) + "% negative words, it is therefore probably not a happy text.");
else if (txt1 > 65)
System.out.println("This text is " + txt1 + "% positive, and is therefore a happy text.");
in.close();
catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
public static double round(double val, int places) {
long factor = (long)Math.pow(10,places);
// Shift the decimal the correct number of places
// to the right.
val = val * factor;
// Round to the nearest integer.
long tmp = Math.round(val);
// Shift the decimal the correct number of places
// back to the left.
return (double)tmp / factor;
public void initiatemap()
a = new arrays();
words = a.initiateWords();
negwords = a.initiateNegWords();
values = a.initiateValues();
negvalues = a.initiateNegValues();
hashMap = a.initiateMap();
hashMap2 = a.initiateNegMap();
for (int i = 0; i < words.length; i++) {
hashMap.put(words[i], values[i]);}
for (int j = 0; j < negwords.length; j++) {
hashMap2.put(negwords[j], negvalues[j]);}
public static void main(String[] args) {
eval eval = new eval();

hi again,
ok thanks for the help, ive have made the changes and i am now getting results.. however the results aren't correct!
if i load the texts in one at a time, i get entirely different results to what is being printed. any suggestions?
thanks again, i really really appreciate your help
Torre
private static void readMultipleFilesFromADirectory()
File directory = new File(multipleFilesDirectory);
// just to double check that this is a directory
if (directory.isDirectory())
File[] allFilesWithinThisDirectory = directory.listFiles();
BufferedReader in = null;
for (File file: allFilesWithinThisDirectory)
initiatemap();
try {
in = new BufferedReader (new FileReader (file));
String str;
String s;
while ((str = in.readLine()) != null)
str = str.replaceAll("[
p{Punct}&&--^áâãäéêëìíîïòóôöùúûüçè]--", " ");
String[]temp = str.split(" ");
for (int i = 0; i < temp.length; i++) {
if (hashMap.containsKey(temp)) {
num++;
for (int i = 0; i < temp.length; i++) {
if (hashMap2.containsKey(temp[i])) {
negnum++;
if (num > 0 && negnum > 0 ){
double total = num + negnum;
double txt1 = round((num/total)*100, 2);
if (txt1 < 50)
System.out.println(file + " is " + txt1 + "% positive and is therefore not a happy text.");
else if (txt1 >= 50 && txt1 <=65)
System.out.println(file +" is " + txt1 + "% positive, but does contain " + (100 - txt1) + "% negative words, it is therefore probably not a happy text.");
else if (txt1 > 65)
System.out.println(file +" is " + txt1 + "% positive, and is therefore a happy text.");
in.close();
catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
results:
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv416_11136.txt is 60.65% positive, but does contain 39.35% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv417_13115.txt is 60.66% positive, but does contain 39.34% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv418_14774.txt is 60.68% positive, but does contain 39.32% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv419_13394.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv420_28795.txt is 60.66% positive, but does contain 39.34% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv421_9709.txt is 60.65% positive, but does contain 39.35% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv422_9381.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv423_11155.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv424_8831.txt is 60.67% positive, but does contain 39.33% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv425_8250.txt is 60.67% positive, but does contain 39.33% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv426_10421.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv427_10825.txt is 60.66% positive, but does contain 39.34% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv428_11347.txt is 60.68% positive, but does contain 39.32% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv429_7439.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv430_17351.txt is 60.68% positive, but does contain 39.32% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv431_7085.txt is 60.67% positive, but does contain 39.33% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv432_14224.txt is 60.67% positive, but does contain 39.33% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv433_10144.txt is 60.66% positive, but does contain 39.34% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv434_5793.txt is 60.63% positive, but does contain 39.37% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv435_23110.txt is 60.62% positive, but does contain 39.38% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv436_19179.txt is 60.68% positive, but does contain 39.32% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv437_22849.txt is 60.69% positive, but does contain 39.31% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv438_8043.txt is 60.65% positive, but does contain 39.35% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv439_15970.txt is 60.68% positive, but does contain 39.32% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv440_15243.txt is 60.66% positive, but does contain 39.34% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv441_13711.txt is 60.64% positive, but does contain 39.36% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv442_13846.txt is 60.61% positive, but does contain 39.39% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv443_21118.txt is 60.61% positive, but does contain 39.39% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv444_9974.txt is 60.6% positive, but does contain 39.4% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv445_25882.txt is 60.56% positive, but does contain 39.44% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv446_11353.txt is 60.54% positive, but does contain 39.46% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv447_27332.txt is 60.54% positive, but does contain 39.46% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv448_14695.txt is 60.56% positive, but does contain 39.44% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv449_8785.txt is 60.55% positive, but does contain 39.45% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv450_7890.txt is 60.54% positive, but does contain 39.46% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv451_10690.txt is 60.54% positive, but does contain 39.46% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv452_5088.txt is 60.53% positive, but does contain 39.47% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv453_10379.txt is 60.56% positive, but does contain 39.44% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv454_2053.txt is 60.55% positive, but does contain 39.45% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv455_29000.txt is 60.55% positive, but does contain 39.45% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv456_18985.txt is 60.57% positive, but does contain 39.43% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv457_18453.txt is 60.53% positive, but does contain 39.47% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv458_8604.txt is 60.53% positive, but does contain 39.47% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv459_20319.txt is 60.5% positive, but does contain 39.5% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv460_10842.txt is 60.54% positive, but does contain 39.46% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv461_19600.txt is 60.48% positive, but does contain 39.52% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv462_19350.txt is 60.47% positive, but does contain 39.53% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv463_10343.txt is 60.49% positive, but does contain 39.51% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv464_15650.txt is 60.48% positive, but does contain 39.52% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv465_22431.txt is 60.46% positive, but does contain 39.54% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv466_18722.txt is 60.46% positive, but does contain 39.54% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv467_25773.txt is 60.45% positive, but does contain 39.55% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv468_15228.txt is 60.47% positive, but does contain 39.53% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv469_20630.txt is 60.42% positive, but does contain 39.58% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv470_15952.txt is 60.39% positive, but does contain 39.61% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv471_16858.txt is 60.4% positive, but does contain 39.6% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv472_29280.txt is 60.4% positive, but does contain 39.6% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv473_7367.txt is 60.38% positive, but does contain 39.62% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv474_10209.txt is 60.38% positive, but does contain 39.62% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv475_21692.txt is 60.42% positive, but does contain 39.58% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv476_16856.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv477_22479.txt is 60.48% positive, but does contain 39.52% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv478_14309.txt is 60.47% positive, but does contain 39.53% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv479_5649.txt is 60.44% positive, but does contain 39.56% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv480_19817.txt is 60.45% positive, but does contain 39.55% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv481_7436.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv482_10580.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv483_16378.txt is 60.44% positive, but does contain 39.56% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv484_25054.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv485_26649.txt is 60.45% positive, but does contain 39.55% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv486_9799.txt is 60.44% positive, but does contain 39.56% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv487_10446.txt is 60.42% positive, but does contain 39.58% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv488_19856.txt is 60.41% positive, but does contain 39.59% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv489_17906.txt is 60.4% positive, but does contain 39.6% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv490_17872.txt is 60.42% positive, but does contain 39.58% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv491_12145.txt is 60.44% positive, but does contain 39.56% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv492_18271.txt is 60.44% positive, but does contain 39.56% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv493_12839.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv494_17389.txt is 60.43% positive, but does contain 39.57% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv495_14518.txt is 60.41% positive, but does contain 39.59% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv496_10530.txt is 60.39% positive, but does contain 39.61% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv497_26980.txt is 60.39% positive, but does contain 39.61% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv498_8832.txt is 60.38% positive, but does contain 39.62% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv499_10658.txt is 60.38% positive, but does contain 39.62% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv500_10251.txt is 60.37% positive, but does contain 39.63% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv501_11657.txt is 60.34% positive, but does contain 39.66% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv502_10406.txt is 60.33% positive, but does contain 39.67% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv503_10558.txt is 60.35% positive, but does contain 39.65% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv504_29243.txt is 60.35% positive, but does contain 39.65% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv505_12090.txt is 60.3% positive, but does contain 39.7% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv506_15956.txt is 60.32% positive, but does contain 39.68% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv507_9220.txt is 60.3% positive, but does contain 39.7% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv508_16006.txt is 60.31% positive, but does contain 39.69% negative words, it is therefore probably not a happy text.
C:\Users\Torre\Desktop\panglee\txt_sentoken\pos\cv509_15888.txt is 60.39% positive, but does contain 39.61% negative words, it is therefore probably not a happy text.

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rtmp://localhost/mp3/mp3:x/2
but i want to know is there any way to play all files in my direcotry?
for example, user click the play button, the player(smp) automatic plays all files in the directory, link windows media server.
Should I use playlist? Or there is another better way?
Thanks a lot.

Hi,
FMS do not directly take a directory to play files, the file names have to be fetched some way (through script if needed) to make a playlist and then the play command needs to be repeated as many times.
Thank you !

How to remove all files in a directory in java?

I have tried method delete() of File ,
but no effect!
can anyone help me!
thank you

So, you have a directory and you want to delete all files in the directory. Here is some (untested) code:
File dir = new File("C:\\tempdir");
File[] files = dir.listFiles();
for (int i = 0; i < files.length; ++i) {
if (files.isFile()) {
files[i].delete();
Jesper

Creating an action that treats all files in a directory

How can I make an action which changes the picture size and resolution for all files in a directory and saves the new versions of the files in a subdirectory?
Thanks

Macro Details wrote:
First create your Sub directory. Then start the Action. Open file, Resisize save as (to Sub directory) then close the file.
Now: File- Automate-Batch. Select your action and your folders and overide the open Command and the Save As Command.
Frankly Norbert I think the Image processor way is easier but to each his own as they say.

Deleting all files in a directory

Hi,
Is it possible to use cffile to delete all files in a
directory. I have a function that creates a file in seperate parts
and places the finished file into a folder. But I need a check to
delete all files currently existing in said folder. I understand it
is possible to query a folder for existing files and then use that
query with cffile to delete the files... I just don't know how to
do it.
Thanks for your help

I am not postivie, but I think I recall learning that the
delete all function is prohibited via CF. You can delete specific
files, though.
If this is, in fact, the case, you could query the directory,
and then loop through the resultant query, deleting each file one
at a time.

[Bash] Massively replace text in all files of a directory

Hi everybody,
I wrote this small recursive function in order to massively replace some strings contained in all files of a directory (and all subdirectories). Any suggestions?
replaceText() {
# set the temporary location
local tFile="/tmp/out.tmp.$$"
# call variables
local script="$2"
local opts="${@:3}"
browse() {
for iFile in "$1"/*; do
if [ -d "$iFile" ];then
# enter subdirectory...
browse "$iFile"
elif [ -f $iFile -a -r $iFile ]; then
echo "$iFile"
sed $opts "s/$(echo $script)/g" "$iFile" > $tFile && mv $tFile "$iFile"
else
echo "Skip $iFile"
fi
done
browse $1
Syntax:
replaceText [path] [script] [sed options (optional)]
For example (it will replace "hello" with "hi" in all files):
replaceText /home/user/mydir hello/hi
Note: It is case-sensitive.
Bye,
grufo
Last edited by grufo (2012-11-10 15:05:43)

falconindy wrote:
Yes, find is recursive and extremely good at its job.
http://mywiki.wooledge.org/UsingFind
Well
falconindy wrote:Your lack of quoting is dangerous, as is your code injection in sed. I'm not sure why you're echoing a var inside a command substitution inside a sed expression, but it's going to be subject to word splitting, all forms of expansion, and may very well break the sed expression entirely, leading to bad things. A contrived example, but passing something like 'foo//;d;s/bar/' should effectively delete the contents of every file the function touches.
So, if you consider it dangerous, you can adopt the whole "sed syntax" and confirm before continue...:
replaceText() {
# set the temporary location
local tFile="/tmp/out.tmp.$$"
# call variables
local sedArgs="${@:2}"
browse() {
for iFile in "$1"/*; do
if [ -d "$iFile" ];then
# enter subdirectory...
browse "$iFile"
elif [ -f $iFile -a -r $iFile ]; then
echo "$iFile"
sed $sedArgs "$iFile" > $tFile && mv $tFile "$iFile"
else
echo "Skip $iFile"
fi
done
while true; do
read -p "Do you want to apply \"sed $sedArgs\" to all files contained in the directory $1? [y/n] " yn
case $yn in
[Yy]* ) browse $1; break;;
* ) exit;;
esac
done
Syntax:
replaceText [parent directory] [sed arguments]
Example:
replaceText /your/path -r 's/OldText/NewText/g'
or, if you want to work directly with the current directory...
replaceText() {
# set the temporary location
local tFile="/tmp/out.tmp.$$"
# call variables
local sedArgs="$@"
browse() {
for iFile in "$1"/*; do
if [ -d "$iFile" ];then
# enter subdirectory...
browse "$iFile"
elif [ -f $iFile -a -r $iFile ]; then
echo "$iFile"
sed $sedArgs "$iFile" > $tFile && mv $tFile "$iFile"
else
echo "Skip $iFile"
fi
done
while true; do
read -p "Do you want to apply \"sed $sedArgs\" to all files contained in the directory $PWD? [y/n] " yn
case $yn in
[Yy]* ) browse $PWD; break;;
* ) exit;;
esac
done
Syntax:
replaceText [sed arguments]
Example:
replaceText -r 's/OldText/NewText/g'
What about?
falconindy wrote:I'll also point out that declaring a function within a function doesn't provide any amount of scoping -- 'browse' will be declared in the user's namespace after running this function for the first time.
See:
function1() {
function2() {
echo "Ciao"
function2
function2 # error
function1 # works

Load all file names in a directory to a SQL Table

I need to load all the file names in a directory to a SQL table. It must be done via TSQL or SSIS. If using TSQL cannot use xp_cmdshell or any undocumented sprocs. So I am guessing it will be SSIS. But still open to suggestions. I am an SSIS newbie and need
a nudge in the right direction of how to get the file names into a SQL table.
Thanks

Let me add a bit of background. We are sent a group of files. Each file has the ccyymmdd date attached to the name. Possible that we miss processing one day and the next day there are two sets of files in the directory. file1_20140101, file2_20140101,
file1_20140102, file2_20140102. I cannot guarantee what the file names will be. Just know that i need to process the 20140101 files in one batch, and then the 20140102 files in the next batch. So thinking that i could read all the file names into a SQL table,
distinct on the date and then sort by the date and pull off those files to process first. Thinking this will be done in SSIS. Open to any ideas or suggestions.

JFileChooser - Select All Files in the Directory

Hi all. I am currently using JFileChooser and I need a functionality that will let the user choose a directory and then automatically select all the files that exists in that directory. I have tried looking around for references, but no luck so far. I hope someone can help. Thanks in advance.

This is what I use frequently in my applications :
* Requests the loading of all Images
* in a directory.
private void loadImageDirectory() {
//create a FileFilter so the user only sees directories
javax.swing.filechooser.FileFilter dirfilter=new javax.swing.filechooser.FileFilter() {
    public boolean accept(File f) {
      if(f==null)
        return false;
      if(!f.isDirectory())
        return false;
      return true;
    public String getDescription() {
      return "Directories only";
//now create the filechooser
JFileChooser jfc=new JFileChooser();
jfc.setDialogTitle("Select a directory");
jfc.setFileSelectionMode(JFileChooser.DIRECTORIES_ONLY);
//remove the standard FileFilters (otherwise shows files too
jfc.resetChoosableFileFilters();
//Set a FileFilter for directories only
jfc.addChoosableFileFilter(dirfilter);
int result=jfc.showOpenDialog(this);
jfc_image_dir=jfc.getCurrentDirectory();
if(result==JFileChooser.APPROVE_OPTION) {
    //here i call a method that does something with the directory
    iv.addDirectory(jfc.getSelectedFile());
}This always worked for me ??
You might want to try??

How to get all files in one directory

Hi there,
is there any way to get all the files in one directory?
e.g. a method
File[] getAllFiles(String directory){
Thank you

Just out of interest, which part of the File API was confusing?
http://java.sun.com/j2se/1.5.0/docs/api/index.html
If you look down the left-hand side, you'll see a frame listing "All File". If you select "File" from that list, it opens up the API in the right-hand frame. Quite near the top you'll find "listFiles".
I only ask as this (and other questions easily answered by looking at the API) are frequently asked. Did you overlook it when you read the API or did you just not read it?
I really want to know. I think there is scope to cater for that behaviour within this site. A nice API finder would be good; something more intelligent than the search function (which people use less frequently even than the API docs).

How do U to get the names of all files in a directory?

Is there a simple way to get all names of the files in a directory and put them in an array of Strings? Sounds simple, but I don't have a clue how to do this. Thanks.

Hi Kindoo,
Create a instance of File object using the path of the Directory
File fileDir = new File(directoryPath);
To get the List of all the files in the directory use
String[] strFiles = fileDir.list();
This will solve your problem,
Cheers
Nagaraj

Transfer of all files in a directory tree using FTP adapter?

Hi,
I'm looking for a solution to transfer a whole directory tree, including the content, from one location to another using the FTP adapter.
Is there an easy way to accomplish this?
Any help would be appreciated.
Thanks
Sigrid

Hi Sigrid,
I'm just wondering on the need to do that using SOA. Is it a regular transfer or one time?
There's a way to move a single file from one FTP location to another on the same or different FTP server (link to the cases). But in order to move all the files in a directory, you'll have to loop this. The high level steps will be:
- List all the files recursively that are present in your directory using File List operation
- Implement the MOVE file operation (or COPY operation) of the FTP Adapter
- Invoke this MOVE operation in a while loop and pass the file names, as gathered from the File List operation, one by one to MOVE operation
You can also use single Java Embedding activity and call a Java class that does the File Transfer but depends on your requirements.
Let us know how you get along.
Regards,
Neeraj Sehgal

Load all files in a directory

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