I have 2 questions about using PIP requirements.txt with a constraint.
Let's say I have a requirements.txt file and I add a constraint file. What happens if I try to specify a different version in req.txt than that which is in the constraints? For example in my req file it says x==1.2 but in my constraint file it says x==1.1
Will it install either version of x? Or neither version?
When using a constraint file which specifies let's say x==1.1, is it best to remove the version number from x in the req.txt?
I tried testing this out, but wasn't sure if either version was getting installed. I expect that it will install the version in the constraints and not the version in the req.txt
I realize that a requirements.txt file can be used to pin the versions used in pip install. Sometimes I don't want to go through all that- and just simply want to protect my installation from downgrades. Is there any way to instruct pip install to do that?
An example: I just installed librosa and it downgraded numpy from 1.24.1 to 1.23.5 . I don't want that behavior to happen unless I explicitly request. On the other hand if there are missing dependencies then please let's grab them.
For this installation of python it is acceptable to take the risk of occasionally ending up with a mismatch due to installing newer versions [ but I don't want older ones].
When I use iPython to run some scripts, I've got the following warning message in iTerm:
/Users/###/anaconda3/lib/python3.6/site-packages/ipykernel/displayhook.py:12:
VisibleDeprecationWarning: zmq.eventloop.minitornado is deprecated in pyzmq 14.0 and will be removed.
Install tornado itself to use zmq with the tornado IOLoop.
When I try to run my code in Visual Studio Code, I've got the following error message:
Error message in VSCode
I have already tried to update Anaconda, I have already tried to install nomkl with conda as well, without any success.
iTerm and VisualStudio on Mac OS 10.14.6, Anaconda up to date (4.7.12)
Remedy Option A)
Use anaconda-tools to separate an environment, say aLastWorkingENV, where you make use of anaconda-tooling to roll-back all components to a last working state, which does not whine about future deprecations. In such aLastWorkingENV environment, all thus synchronised programs will work smooth (as they did before a first component update, that has moved the stick)
Remedy Option B)
Use anaconda-tools to update all current components and all their supporting modules and all packages versions [ python, ipython, pyzmq, jupyter, ..., ] to their most recent versions, where products QA coverage ought either confirm the PASS, or provide a remedy or workaround or the last-trouble-free version ( to eventually downgrade one such package, based on such exception, if present and relevant )
Either way, your code would stop throwing the soft-warnings and remain in such state, until any un-coordinated package update takes place.
I want to install the package dataframe of Octave on one of my servers, which does not have internet access. I used my laptop to download dataframe-1.1.0.tar.gz. I wonder how I can install it on my server manually.
In the README.html of Octave 4.0.0 folder you can find the following passage:
Included Octave Forge Packages
A number of Octave-Forge packages have been included with Octave, however they must be installed in order to use them.
To install:
• Start Octave and then open the build_packages.m file found in the src folder where Octave was installed.
• Run the script build_packages.m to build and install the packages.
Installation is a one-time procedure. After installation packages must still be loaded in order to use them with the pkg load PACKAGENAME command.
Other packages are available from Octave-Forge.
What you need to do for other packages, which are not included with Octave, is: download the package from http://octave.sourceforge.net/packages.php. Then put the package in the src folder and modify build_packages.m respectively before executing it.
According to the Octave documentation:
37.1 Installing and Removing Packages
Assuming a package is available in the file image-1.0.0.tar.gz it can
be installed from the Octave prompt with the command
pkg install image-1.0.0.tar.gz
If the package is installed successfully nothing will be printed on
the prompt, but if an error occurred during installation it will be
reported. It is possible to install several packages at once by
writing several package files after the pkg install command. If a
different version of the package is already installed it will be
removed prior to installing the new package. This makes it easy to
upgrade and downgrade the version of a package, but makes it
impossible to have several versions of the same package installed at
once.
A friend sent me along this great tutorial on webscraping The New York Times with R. I would really love to try it. However, the first step is to install a package called [RJSONIO][2] from source.
I know R reasonably well, but I have no idea how to install a package from source.
I'm running macOS (OS X).
If you have the file locally, then use install.packages() and set the repos=NULL:
install.packages(path_to_file, repos = NULL, type="source")
Where path_to_file would represent the full path and file name:
On Windows it will look something like this: "C:\\RJSONIO_0.2-3.tar.gz".
On UNIX it will look like this: "/home/blah/RJSONIO_0.2-3.tar.gz".
Download the source package, open Terminal.app, navigate to the directory where you currently have the file, and then execute:
R CMD INSTALL RJSONIO_0.2-3.tar.gz
Do note that this will only succeed when either: a) the package does not need compilation or b) the needed system tools for compilation are present. See: R for Mac OS X
You can install directly from the repository (note the type="source"):
install.packages("RJSONIO", repos = "http://www.omegahat.org/R", type="source")
A supplementarily handy (but trivial) tip for installing older version of packages from source.
First, if you call "install.packages", it always installs the latest package from repo. If you want to install the older version of packages, say for compatibility, you can call install.packages("url_to_source", repo=NULL, type="source"). For example:
install.packages("http://cran.r-project.org/src/contrib/Archive/RNetLogo/RNetLogo_0.9-6.tar.gz", repo=NULL, type="source")
Without manually downloading packages to the local disk and switching to the command line or installing from local disk, I found it is very convenient and simplify the call (one-step).
Plus: you can use this trick with devtools library's dev_mode, in order to manage different versions of packages:
Reference: doc devtools
From CRAN, you can install directly from a GitHub repository address. So if you want the package at https://github.com/twitter/AnomalyDetection, using
library(devtools)
install_github("twitter/AnomalyDetection")
does the trick.
In addition, you can build the binary package using the --binary option.
R CMD build --binary RJSONIO_0.2-3.tar.gz
If you have source code you wrote yourself, downloaded (cloned) from GitHub, or otherwise copied or moved to your computer from some other source, a nice simple way to install the package/library is:
In R
It's as simple as:
# install.packages("devtools")
devtools::install('path/to/package')
From terminal
From here, you can clone a GitHub repo and install it with:
git clone https://github.com/user/repo.git
R -e "install.packages('devtools');devtools::install('path/to/package')"
Or if you already have devtools installed, you can skip that first bit and just clone the repo and run:
R -e "devtools::install('path/to/package')"
Note that if you're on ubuntu, install these system libraries before installing devtools (or devtools won't install properly).
apt-get update
apt-get install build-essential libcurl4-gnutls-dev libxml2-dev libssl-dev libfontconfig1-dev libharfbuzz-dev libfribidi-dev libfreetype6-dev libpng-dev libtiff5-dev libjpeg-dev -y