Is there a way to get a local timestamp in my IPython prompt? I'm using IPython 0.10 and Python 2.6 on 64-bit Windows Vista.
My current default prompt is
[C:Python26/Scripts]
|9>
OK, I tried to follow your directions exactly. However, my experience has been that all config editing is best kept to my ipy_user_conf.py. To quote from it:
User configuration file for IPython (ipy_user_conf.py)
This is a more flexible and safe way to configure ipython than *rc files
(ipythonrc, ipythonrc-pysh etc.)
This file is always imported on ipython startup. You can import the
ipython extensions you need here (see IPython/Extensions directory).
Feel free to edit this file to customize your ipython experience.
Note that as such this file does nothing, for backwards compatibility.
Consult e.g. file 'ipy_profile_sh.py' for an example of the things
you can do here.
See http://ipython.scipy.org/moin/IpythonExtensionApi for detailed
description on what you could do here.
So I now have these lines in main():
# -- prompt
# A different, more compact set of prompts from the default ones, that
# always show your current location in the filesystem:
o.prompt_in1 = r'\C_LightBlue[\C_LightCyan\Y2\C_LightBlue]\C_Normal\n\C_Green|\#>'
o.prompt_in2 = r'.\D: '
o.prompt_out = r'[\#] '
And I get this, for an example:
16:49:50 In[9]:1/7
1 [9] 0.14285714285714285
16:50:09 In[10]:
Questions:
What is that 1?
How can I keep the current directory in the prompt? Before, I had
[C:Python26/Scripts]
|8>
Once more with feeling.
I'm so sorry for the mess I've made. I need to report the lines I either added or modified actually are:
import_all("os sys random datetime")
o.prompt_in1 = r'\C_LightBlue[\C_LightCyan\Y2\C_LightBlue]\C_Normal\n\C_Green|\#>'
o.prompt_in1 = r'${datetime.now().strftime("%H:%M:%S")}[\#]:'
o.prompt_out = r'[\#] '
The easiest way is to edit your ipythonrc (in your home\_ipython directory), and add these lines:
import_mod datetime
prompt_in1 '${datetime.datetime.now()} In [\#]: '
# or
prompt_in1 '${datetime.datetime.now().strftime("%H:%M:%S")} In [\#]: '
Alternatively, you can also just add the import_mod datetime to the rc file, and add this to the main() function of ipy_user_conf.py (in the same directory):
o = ip.options
o.prompt_in1 = r'${datetime.datetime.now()} In [\#]: '
# or
o.prompt_in1 = r'${datetime.datetime.now().strftime("%H:%M:%S")} In [\#]: '
Related
I use python to do my data analysis and lately I came up with the idea to save the current git hash in a log file so I can later check which code version created my results (in case I find inconsistencies or whatever).
It works fine as long as I do it locally.
import git
import os
rep = git.Repo(os.getcwd(), search_parent_directories=True)
git_hash = rep.head.object.hexsha
with open ('logfile.txt', 'w+') as writer:
writer.write('Code version: {}'.format(git_hash))
However, I have a lot of heavy calculations that I run on a cluster to speed things up (run analyses of subjects parallel), using qsub, which looks more or less like this:
qsub -l nodes=1:ppn=12 analysis.py -q shared
This always results in a git.exc.InvalidGitRepositoryError.
EDIT
Printing os.getcwd() showed me, that on the cluster the current working dir is always my $HOME directory no matter from where I submit the job.
My next solution was to get the directory where the file is located using some of the solutions suggested here.
However, these solutions result in the same error because (that's how I understand it) my file is somehow copied to a directory deep in the root structure of the cluster's headnode (/var/spool/torque/mom_priv/jobs).
I could of course write down the location of my file as a hardcoded variable, but I would like a general solution for all my scripts.
So after I explained my problem to IT in detail, they could help me solve the problem.
Apparently the $PBS_O_WORKDIR variable stores the directory from which the job was committed.
So I adjusted my access to the githash as follows:
try:
script_file_directory = os.environ["PBS_O_WORKDIR"]
except KeyError:
script_file_directory = os.getcwd()
try:
rep = git.Repo(script_file_directory, search_parent_directories=True)
git_hash = rep.head.object.hexsha
except git.InvalidGitRepositoryError:
git_hash = 'not-found'
# create a log file, that saves some information about the run script
with open('logfile.txt'), 'w+') as writer:
writer.write('Codeversion: {} \n'.format(git_hash))
I first check if the PBS_O_WORKDIR variable exists (hence if I run the script as a job on the cluster). If it does get the githash from this directory if it doesn't use the current working directory.
Very specific, but maybe one day someone has the same problem...
I am recovering Stata following a Windows upgrade. I have a list of my packages generated from ado dir in the following format:
[1] package mdesc from http://fmwww.bc.edu/RePEc/bocode/m
'MDESC': module to tabulate prevalence of missing values
[2] package univar from http://fmwww.bc.edu/RePEc/bocode/u
'UNIVAR': module to generate univariate summary with box-and-whiskers plot
[3] package tabmiss from http://www.ats.ucla.edu/stat/stata/ado/analysis
tabmiss. Shows tabulation of number of missing and non-missing values
I have many packages and would like to reinstall them without having to designate each directory/url via net cd. While using net cd along with net install or ssc install along with package names in a loop is trivial (as below), it would seem that an automated method for this task might be available.
net cd http://www.ats.ucla.edu/stat/stata/ado/analysis
local ucla tabmiss csgof powerlog ldfbeta
foreach x of local ucla {
net install `x'
}
To my knowledge, there is no built-in or automated method of tracking and managing your installed packages outside of what is available through ado or net.
I would also tend to agree with #Nick Cox that this task seems strange and I can't imagine how a new Stata install or reinstall could know what was installed previously, but I find the question interesting for other reasons.
The main reason being for users who have Stata installed on multiple machines who need the same packages on both machines. I faced a similar issue when I purchased a new computer and installed Stata but wanted all of the packages I use to be available as well. Outside of moving the ado directory or selected contents I'm not aware of any quick solution.
Here it would be possible to use the output of ado dir on one machine to determine what you need to install on a second machine with a new Stata install.
The method you propose using a foreach loop could save you time from having to type in or copy/paste a lot of packages and URLs. At the same time however, this is only beneficial if you have many packages from only a few repositories because you will need to net cd to the URL each time as you show in your example.
An alternative solution is the programmatic solution. As you know, ado dir will list each installed package, the URL and a short description of the package. Using this, a log file, and the built in I/O functionality, a short program could be written to automate the process and dynamically build a do file that contains the commands to install the already installed packages.
The code below generates a do file containing commands (in this case, net describe package, from(url)) for each package I have installed on my computer.
clear *
tempfile log1
log using "`log1'", text name(mylog)
ado dir
log close mylog
tempname logfile
file open `logfile' using "`log1'", read
file read `logfile' line
file open dfh using "path/to/your/dofile.do", write replace
local pckage "package"
while r(eof) == 0 {
if `: list pckage in line' {
local packageName : word 3 of `line'
local dirName : word 5 of `line'
di "`packageName' `dirName'"
file write dfh "net describe `packageName', from(`dirName')"
file write dfh _newline
}
file read `logfile' line
}
file close `logfile'
file close dfh
In the above code, I create a temp file to write a .txt log file to and store the contents of ado dir in that file.
Then, I open the log file using file open and read it line by line in the while loop.
Above the loop, I'm creating a do file at /path/to/your/dofile.do to hold the output of the loop - the dynamically created commands relating to the installed packages on my machine.
The loop will iterate so long as r(eof) = 0, where r(eof) is an end of file marker. I use an if statement to sort out lines of the log file which contain the word package, as I'm only interested in those lines with the package name and URL in them.
Inside of the if block, I parse the local macro line to pull the package name and the URL/directory name.
this is important: this section of code assumes that the 3rd and 5th words in the macro will always be the package name and URL respectively - Confirm this from the output of ado dir before executing.
You will also need to change the command that is being written to the file handle dfh inside of the loop to what you want (net install, etc) when you are ready to execute.
For more help on using file, locals, and tempfiles execute any of the following in Stata:
help file
help extended_fcn
help macrolists
There may be nicer ways to parse the contents of ado dir but this has worked for me. And of course I'd always advise that you take the time to understand what the code is doing so that you can make any necessary tweaks to fit your particular situation.
I am new to octave and need to plot a 2-D graph with customized title either as a file name or current directory name. I tried passing pwd in the plot.m file but it gives me a complete path instead of directory name only. Actually all I need is a customized title without manually hard coding the string inside xlabel('strings').
I don't have Octave but this works on MATLAB:
current_directory_name = pwd;
current_directory_split = regexp(current_directory_name,'/','split');
string_of_interest = current_directory_split(end);
xlabel(string_of_interest);
I am assuming you are on *NIX computer. For Windows computer, change / to \ in the split command.
If I understood your question correctly, you want a portable way of retrieving the file name w/o the directory name. Use fileparts():
[dir, name, ext, ver] = fileparts(pwd)
If you later decide to join strings, use filesep which is portable no matter if you're on Unix or not.
I have a folder which has subfolders containing 1000s of DICOM images which I want to read in from IDLE and analyze.
I have used the following code to find file paths:
import sys
print sys.path
I subsequently tried placing my folder which I want to access in these file paths, however I still can not access the files and I get the following error:
>>> fp = open(fp, 'rb')
IOError: [Errno 2] No such file or directory: 'IM-0268-0001.dcm'
I have also tried:
sys.path.insert(0, 'C:/desktop/James_Phantom_CT_Dec_16th/Images')
But this did not work for me either. Help much appreciated, very frustrated.
(using Python 2.7, 64 bit windows OS).
When opening a file, Python does not search the path. You must specify the full path to open:
d = 'C:/desktop/James_Phantom_CT_Dec_16th/Images'
fp = open(d +'IM-0268-0001.dcm',"rb")
Edit: d is the string that will hold the path so that you don't have to re-type it for each file. fp will hold the file object that you will work with. The "rb" is the way you want to open the file:
r - read
w - write with truncate
a - append
r+ - read and write
Also, if working in windows, add "b" to work with binary files. See here.
I am struggeling to read an *.xls file into R:
I did the following:
I set my working directory to the *.xls file and then:
> library(gdata) # load the gdata package
> mydata = read.xls("comprice.xls", sheet=1, verbose=FALSE)
Mistake in findPerl(verbose = verbose) : perl executable not found. Use perl= argument to specify the correct path. mistake in file.exists(tfn) : unknown 'file' argument
However, my path is correct and there is the file! Whats wrong?
UPDATE
I have installed it already, however now I get: Exception: cannot find function "read.xls"...
This error message means that perl is not installed on your computer or it is not set on your path.
If the perl is installed then you can put argument perl= inside read.xls() function.
read.xls(xlsfile, perl="C:/perl/bin/perl.exe")
As an alternative, you could try xlsxpackage:
read.xlsx("comprice.xls", 1) reads your file and makes the data.frame column classes nearly useful, but is very slow for large data sets.
read.xlsx2("comprice.xls", 1) is faster, but you'll have to define column classes manually. If you run the command twice, you will not need to count columns so much:
data <- read.xlsx2("comprice.xls", 1)
data <- read.xlsx2("comprice.xls", 1, colClasses= rep("numeric", ncol(data)))
Perl is either not installed or cannot be found. You can either install it, or specify the path where it is installed using
perl='path of perl installation'
in the call.