#Install prettytable python for mac install
If you installed Python any other way (from source, using pyenv, virtualenv, etc.), then use pip to install Python packagesįinally, because it often comes up, I should mention that you should never use sudo pip install. If conda tells you the package you want doesn't exist, then use pip (or try conda-forge, which has more packages available than the default conda channel). If you installed Python using Anaconda or Miniconda, then use conda to install Python packages. If you already have a Python installation that you're using, then the choice of which to use is easy:
![install prettytable python for mac install prettytable python for mac](https://miro.medium.com/max/1400/1*NNGQKrDrn1u9C0mbNlzr-g.png)
![install prettytable python for mac install prettytable python for mac](https://www.codegrepper.com/codeimages/python-dotenv.png)
In the wake of several discussions on this topic with colleagues, some online ( exhibit A, exhibit B) and some off, I decided to treat this issue in depth here.įirst, I'll provide a quick, bare-bones answer to the general question, how can I install a Python package so it works with my jupyter notebook, using pip and/or conda?. In other words, the Jupyter notebook, like all abstractions, is leaky. In the simplest contexts this issue does not arise, but when it does, debugging the problem requires knowledge of the intricacies of the operating system, the intricacies of Python package installation, and the intricacies of Jupyter itself. etc.).įundamentally the problem is usually rooted in the fact that the Jupyter kernels are disconnected from Jupyter's shell in other words, the installer points to a different Python version than is being used in the notebook. this, that, here, there, another, this one, that one, and this. This issue is a perrennial source of StackOverflow questions (e.g. I installed package X and now I can't import it in the notebook. I most often see this manifest itself with the following issue: It requires MongoDB version 4.2 or higher for Local DB.In software, it's said that all abstractions are leaky, and this is true for the Jupyter notebook as it is for any other software. If you do not have the repository of Local DB tools, see the clone git repository for the pre installation. It requires to compile Local DB tools in working directory of your DB machine to handle Local DB. It requires several pip modules for Local DB tools compilation. It requires python version 3.6 or higher for Local DB tools compilation.
![install prettytable python for mac install prettytable python for mac](https://imgs.developpaper.com/imgs/90Hp86ZPla.jpg)
It requires several other packages for Local DB tools compilation. It requires cmake version 3 for Local DB tools compilation. It requires g++ version 7.0 or higher for Local DB tools compilation. Installation for DB machine brew packages (DB) brew command $ /usr/bin/ruby -e "$(curl -fsSL )" Once the compile is successful, the binary commands are placed in YARR/bin. DCMAKE_TOOLCHAIN_FILE=./cmake/macos-clang If you do not have the repository of YARR, see the clone git repository for the pre installation. It requires to compile YARR in working directory of your DAQ machine to scan ASICs.
![install prettytable python for mac install prettytable python for mac](https://images1.tqwba.com/20201029/f5ntpwgei5f.png)
$ brew install gawkĪnd you need to install MacTex to output the plots of the scan results proparely. It requires several other packages for YARR SW compilation. It requires cmake version 3 for YARR SW compilation. It requires g++ version 7.0 or higher for YARR SW compilation. Installation for DAQ machine brew packages (DAQ) brew command $ /usr/bin/ruby -e "$(curl -fsSL )"
#Install prettytable python for mac manual
If you want to install on centOS7, see the manual installation guide for centOS7. You can install the requirements for the system on macOS manually following this page.