CUCC Expedition Handbook

QMs and leads

QMs - the fourfold path

You will be familiar with documenting newly found QMs in the survex file when you type it in. But QMs are only useful if they can be easily scanned by people planning the next pushing trip. That's what we are discussing here.

There are four ways we have used to manage QMs:

1. Perl script - Historically QMs were not in the survex file but typed up in a separate list qms.csv for each cave system. A perl script turned that into an HTML file for the website.
2. Perl + troggle - One of troggle's input parsers "QM parser" is specifically designed to import the three HTML files produced from qms.csv but doesn't do anything with that data (yet).
3. Python script - Phil Withnall's 2019 script svx2qm.py scans all the QMs in a single survex file. See below for how to run it on all survex files.
4. New troggle - Sam's recent addition to troggle's "survex parser" makes it recognise and store QMs when it parses the survex files.

QMs all use the same QM description conventions.

tablize-qms.pl

This is a perl script dating from November 2004.

it takes a hand-edited CSV file name as the program's argument and generates an HTML page listing all the QMs.

Copies of it live in the three cave file folders in :expoweb:/1623/, in 258/, 234/, and 204/ . These generated html files are live pages in the cave descriptions:
/1623/258/qm.html
/1623/234/qm.html
/1623/204/qm.html

Note that the qms.csv file file used as input by this script is an entirely different format and table structure from the qms.csv file produced by svx2qm.py.

There are also three versions of the QM list for cave 161 (Kaninchenhohle) apparently produced by this method but hand-edited:
/1623/161/qmaven.html 1996 version
/1623/161/qmtodo.html 1998 version
/1623/161/qmdone.html 1999 (incomplete) version

In the /1623/204/ folder there is a script qmreader.pl which apparently does the inverse of tablize-qms.pl: it transforms a QMs' HTML file into a CSV file.

troggle/parsers/qms.py

The parser troggle/parsers/qms.py currently imports those same qm.csv files from the perl script into troggle using a mixture of csv and html parsers:

parseCaveQMs(cave='stein',inputFile=r"1623/204/qm.csv")
parseCaveQMs(cave='hauch',inputFile=r"1623/234/qm.csv")
parseCaveQMs(cave='kh', inputFile="1623/161/qmtodo.htm")
#parseCaveQMs(cave='balkonhoehle',inputFile=r"1623/264/qm.csv")

Note that the hand-edited qm.csv for Balkonhohle was apparently abandoned unfinished as we transitioned to putting the QMs in the survex files instead. It contains QMs from 2014 and 2016:
/1623/264/qm.csv - unused

svx2qm.py

Philip Withnall's 2019 QM extractor svx2qm.py (in :loser:/qms/) can be used to generate a list of all the QMs in all the svx files in either text or CSV format. When run together with file and xargs it will produce a output listing all the QMs:

cd loser
find -name '*.svx' | xargs qms/svx2qm.py --format csv

The 2019 copies are online in /expofiles/: qms2019.txt and qms2019.csv.

This will work on all survex *.svx files even those which have not yet been run through the troggle import process.

Phil says (13 April 2020): "The generated files are not meant to be served by the webserver, it’s a tool for people to run locally. Someone could modify it to create HTML output (or post-process the CSV output to do the same), but that is work still to be done."

Sam's parser additions

Troggle troggle/parsers/survex.py currently parses and stores all the QMs it finds in survex files. The tables where the data is put are listed in the current data model including structure for ticking them off.

There is not yet a troggle report listing the QMs.

QMs - monitoring progress

find-dead-qms.py

This finds references to completed qms in the qm.csv files in the cave folders (/1623/ etc.) in the :expoweb: repository. It looks to see which QMs have been completed but where there is not yet a matching text in the cave description.

Quick and dirty Python script to find references to completed qms in the cave description pages. Run this to find which bits of description need updating.
The list of qms is read from the qm.csv file and any with an entry in the "Completion description" column (column 7) are searched for in all the html files.
The script prints a list of the completed qms that it found references to and in which file.
Nial Peters - 2011

From: Philip Withnall [tecnocode] 
Sent: 13 April 2020 23:41
To: Philip Sargent (Gmail)
Subject: Re: svx2qm

Hi Philip,

Hope you’re well, thanks for getting in touch about this.

The generated files are not meant to be served by the webserver, it’s a tool for people to run locally. 
Someone could modify it to create HTML output (or post-process the CSV output to do the same), 
but that is work still to be done.

I can't see any problem with moving it all to expoweb/scripts/ - so long as it is 
run with the loser top level directory specified - but I might be mistaken:
find  /home/expo/loser -name '*.svx' | xargs ./svx2qm.py --format human
and it should go into the Makefile too at some point.

Feel free to move it wherever; I am not planning on doing any further work on it. 
The script itself just expects to be passed some (relative or absolute) paths to SVX files, 
so can be placed wherever, as long as it’s passed appropriate relative paths.

I haven’t written any other scripts which post-process the data or otherwise format it.

I guess it all depends on what questions people are trying to answer using the QM data, 
as to how (and where) best to present it. I’m afraid I don’t have any suggestions there.

:Rob Watson wrote some documentation about QMs
:http://expo.survex.com/handbook/survey/qmentry.html 
:is there anything subtle missing  as to how they are used ?

Nope, I think Rob’s page covers it all. That page also documents the correct QM format 
which is what svx2qm.py understands. (There were some older or artisanal QM formats 
floating around at one point, although I think I reformatted them all so the tool 
would understand them, and so people would hopefully standardise on what Rob’s 
documented from then on.)

Philip