Extract a ZIP file programmatically by DotNetZip library?

You need to test each ZipEntry to see if you want to extract it: public void ExtractFileToDirectory(string zipFileName, string outputDirectory) { ZipFile zip = ZipFile.Read(zipFileName); Directory.CreateDirectory(outputDirectory); foreach (ZipEntry e in zip) { // check if you want to extract e or not if(e.FileName == “TheFileToExtract”) e.Extract(outputDirectory, ExtractExistingFileAction.OverwriteSilently); } }

JAR – extracting specific files

From the source: To extract only certain files from a jar file, supply their filenames: C:\Java> jar xf myFile.jar foo bar Using wildcards is a shell thing, and you should not expect it to work when extracting from a JAR file (which, as you’ve realized, is the case). What you can do, is supply a … Read more

C# regex pattern to extract urls from given string – not full html urls but bare links as well

You can write some pretty simple regular expressions to handle this, or go via more traditional string splitting + LINQ methodology. Regex var linkParser = new Regex(@”\b(?:https?://|www\.)\S+\b”, RegexOptions.Compiled | RegexOptions.IgnoreCase); var rawString = “house home go www.monstermmorpg.com nice hospital http://www.monstermmorpg.com this is incorrect url http://www.monstermmorpg.commerged continue”; foreach(Match m in linkParser.Matches(rawString)) MessageBox.Show(m.Value); Explanation Pattern: \b -matches … Read more

Extract .xip file into a folder from command line?

Maybe try: xip -x [path to .xip file] That will unpack the archive into your current working directory. As for extracting into a specific directory, there is not explicitly an option for this, but xip -x will extract into the current working directory. Therefore, cding to where you would like to extract the file should … Read more

pandas extract year from datetime: df[‘year’] = df[‘date’].year is not working

If you’re running a recent-ish version of pandas then you can use the datetime accessor dt to access the datetime components: In [6]: df[‘date’] = pd.to_datetime(df[‘date’]) df[‘year’], df[‘month’] = df[‘date’].dt.year, df[‘date’].dt.month df Out[6]: date Count year month 0 2010-06-30 525 2010 6 1 2010-07-30 136 2010 7 2 2010-08-31 125 2010 8 3 2010-09-30 84 … Read more

Hata!: SQLSTATE[HY000] [1045] Access denied for user 'divattrend_liink'@'localhost' (using password: YES)