Conda Compilers

We saw in the last exercise that there are about 30,000 linux-64 packages on conda-forge. One of the major remaining tasks to be done before conda can replace the libpack is to provide debug packages. It takes a Python module annotated with a few interface description and turns it into a native Python module with the same interface, but (hopefully) faster. How to learn Conda. These new compiler packages and conda-build 3 were designed to work together. Create a new Conda virtual environment¶ To deal with the fact that labelImg (on Windows) requires the use of pyqt4 , while tensorflow 1. Introduction to anaconda¶. For these, you can find many high-quality crates and some awesome guides on how to get started. I have a conda environment named old_name, how can I change its name to new_name without breaking references? You can't. JET Framework. For example, the numpy package has dependencies such as ATLAS, gfortran, etc. 7, as well as Windows/macOS/Linux. His key id EA5BBD71 was used to sign all other Python 2. Conda isn’t perfect, as I couldn’t get its environment system to work. Then read some of the Using conda documentation. Do you have any ideas how to use gcc with system headers through conda so that I can compile files with system headers like stdio. 6 (and possibly other packages) require pyqt5 , we will create a new virtual environment in which to run labelImg. If you want to compile the extension within the directory for any development, just type:. The intent is to improve the accessibility of these tools to all researchers by enabling one-line installations of highly useful software packages without the need for compilation, etc. $ conda list Lists installed Python modules. conda install tensorflow-gpu==1. Check here to find the appropriate packages for your platform. $ conda create --name nbodykit-env python = 3 # or use python=2 for python 2. It takes a Python module annotated with a few interface description and turns it into a native Python module with the same interface, but (hopefully) faster. P SI 4 is available as a pre-compiled binary for Mac and Linux (and Windows, through the Ubuntu shell) architectures through Continuum Analytics, the company that produces Anaconda Python (a full-fledged scientific python environment with package manager conda) and, more particularly, Miniconda (a lightweight python distribution with same package manager conda). Also, if you are going to install from sources, and a C compiler (Clang, GCC and MSVC 2008 for Python 2, and MSVC 2010 for Python 3, have been tested). Since conda installs binary packages that have already been compiled, this saves you from having to configure the correct compiler settings on your local machine. dev249+623ad64=py36_sse41_0 -c psi4/label/subchannel -c psi4 also install optional runtime addons conda install psi4 psi4-rt -c psi4/label/dev print configuration information. It would be nice to submit this upstream at some point. exe version 19. Anaconda is the installation program used by Fedora, Red Hat Enterprise Linux and some other distributions. If you try to install or compile some projects that required c/gcc compiler, following errors message will be logged : In terminal, type “gcc“, you will get message “command not found”. Choose Python 3. To install this dependency manually (probably not needed unless you are an MFiX developer), run the following command in the Anaconda prompt:. Canada Computers offers the best prices on Computers, Computer Parts, Laptops, Hard Drives, PC Hardware & Accessories with fast shipping and top-rated customer service. pip 30 July, 2018. pyo if you have the optimizer turned on) files that are generated for modules that you import or write yourself. The conda-forge channel provides multitude of community maintained packages. More details on “strong” and “weak” exports (using examples of libpng and libgcc) can be found in the export runtime requirements conda documentation. Pythran is an ahead of time compiler for a subset of the Python language, with a focus on scientific computing. conda create --name py2k python = 2 numpy conda activate py2k pip install 3to2 conda activate cantera and after you’ve cloned the source code , add the following lines to a file called cantera. Installation with pip¶. For example, you will need to use them if you wish to: Install a non-pure Python package from sources with Pip (if there is no Wheel package provided). If python packages cannot be found on conda servers they can simply be installed via pip when called from within the activated conda environment. My procedure has been to create a conda environment inside the external hdd, and then conda install -c conda-forge boost pcl. 1: Apache: X: 2pg cartesian is a framework of optimization algorithms for protein. py2exe is used by BitTorrent, SpamBayes, and thousands more - py2exe averages over 5,000 downloads per month. Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications. The configuration that PDAL uses is valuable raw materials for configuring your own environment because the PDAL team must keep it up to date with both the Conda environment and the Microsoft compiler situation. Note that Conda provides much of the same functionality already present in the HPC environment, namely environment modules which provide Python and other software such as pip and virtualenv. In this post I'll try to give some guidance on relatively easy ways to get started with TensorFlow. This may prevent your Anaconda installation from finding certain packages. conda is designed to work very well with the complex binary packages found in the scientific and numerical Python ecosystem, which are oftentimes very difficult to build and install. Here is a step-by-step outline of how you can install ijavascript within a conda virtual environment. Code, Compile, Run and Debug python program online. $ conda install -c conda-forge tomopy This will install TomoPy and all the dependencies from the conda-forge channel. conda install numpy This should work for Linux and MacOS systems, but it is experimental, and does not provide access to parallel or gpu-optimized codes. The Rigetti Quil Compiler (quilc) which allows compilation and optimization of Quil programs to native gate sets; The QVM and the compiler are packed as program binaries that are accessed through the command line. Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs. How to create and manage Python environments in Visual Studio. The following workaround, making and invoking a new environment, does work: "conda create -n vpclean -c vpython vpython python=3" followed by "source activate vpclean". Optional dependencies: pytest (for running the test suite) matplotlib. 7, RScript (included in R), a C++ compiler, zlib. His key id ED9D77D5 is a v3 key and was used to sign older releases; because it is an old MD5 key and rejected by more recent implementations, ED9D77D5 is no longer included in the public. ''' Online Python Compiler. 04 along with Anaconda (Python 3. x, NumPy, Cython. 7 is too old to compile pygmo, and thus we cannot provide conda packages for Python 2. There's an edit button in the header, and you won't even need an account or any such nonsense. BLAS installation (with Level 3 functionality) Recommended: MKL, which is free through Conda with mkl-service package. 5; To install this package with conda run one of the following: conda install -c conda-forge gcc conda install -c conda-forge/label/cf201901 gcc. To compile the module, we should switch to the GNU compilers. Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs. This compiler can handle C++11 but still generate binaries that have broad binary compatibility. Over time, Python has been built using a variety of different Windows C compilers. Anaconda in version 5. ch The Conda package manager HSF Packaging WG meeting Since conda-build 3 the Anaconda distribution has used CDTs Repackage libraries from CentOS 6 and move them to the sysroot of conda's pseudo-cross compilers Used at build time for linking Use libraries from the host at run time. To install these dependencies manually (probably not needed unless you are an MFiX developer), run the following command in the Anaconda prompt:. Hypothesis Testing using Phylogenies. Anaconda is the installation program used by Fedora, Red Hat Enterprise Linux and some other distributions. $ conda list --export Save package list for future use. Btw, I'm going to be making a PR soon to reduce the amount of cmake options needed. Because this type of installation resolves environments, package-package conflicts, etc. Other ways to install python and gensim may be more complicated. it Upgrade numpy. The latest release is 1. conf in the root of the source directory (creating the file if it doesn’t exist). There are two possible approaches for building NSIS installers with conda: Using 'conda execute'. This wikiHow teaches you how to compile a C program from source code by using the GNU Compiler (GCC) for Linux and Minimalist Gnu (MinGW) for Windows. dev249+623ad64=py36_sse41_0 -c psi4/label/subchannel -c psi4 also install optional runtime addons conda install psi4 psi4-rt -c psi4/label/dev print configuration information. Enter conda install cython numpy matplotlib pytest spyder pybind11. To install mingw-w64 compiler type:. To check the packages, type "conda list" and make sure gensim is included. Whether conda is that "system" level packaging tool is going to depend largely on if you want the cross platform-ness of Anaconda/conda and their C level virtualenvs or if you'd prefer the platform specific but better story for things like security updates and the like. 6 (and possibly other packages) require pyqt5 , we will create a new virtual environment in which to run labelImg. 4 numpy pip mingw conda create -n py3. configdefaults): g++ not available, if using conda: `conda. Even though Python is an interpreted language, you may need to install Windows C++ compilers in some cases. You will need to update the. GFortran development is part of the GNU Project. Conda packages are binaries. 2016-12-01: lda: public: Topic modeling with latent Dirichlet allocation 2016-12-01: pbr: public: Python Build Reasonableness 2016-12-01: nltk: public: Natural Language Toolkit 2016-12-01: python-linkedin: public: Python Interface to the LinkedIn API 2016-12-01. export CONDA_COMPILERS = "clang_osx-64 gfortran_osx-64" Run the following command to build CMOR for your version of Python. Use conda's pinning mechanism in your environment to control which variant you want. Miniconda includes a much smaller set of core packages along with Conda. For packages scanned in the last 2 weeks see cdn clone rss feed. [email protected]:~$ conda install jupyter notebook pandas matplotlib netcdf4 holoviews geoviews Create a virtual environment It may be necessary to use a package that is not the latest version owing to the dependency, which may lead to conflicts among packages. If you are having difficulty installing DSC and its dependnencies directly from source, we recommend switching to using conda. Cython code is compiled using the cython source-to-source compiler to create C or C++ code, which in turn can be compiled using a C compiler. Note: this needs to be repeated whenever you create a new virtual environment in which you want to build SciPy. Open Anaconda Command prompt as administrator. More details on “strong” and “weak” exports (using examples of libpng and libgcc) can be found in the export runtime requirements conda documentation. OK, after looking at the full build log, now I see this is totally unrelated to mpi4py/MPICH, the problem is with the macOS SDKs. Conda makes it quick and easy to install, run, and upgrade complex data science and machine learning environments like scikit-learn, TensorFlow, and SciPy. From Xcode 4. conda-env 2. com/apache/arrow/tree/master/dev/tasks/conda-recipes/variants to https://github. Conda is a good default choice in Linux and OSX. Cuda out of memory pytorch. Miniconda includes a much smaller set of core packages along with Conda. Conda Binary Distribution¶. It has been built successfully with MSVC on Windows, GCC on Linux and clang/LLVM on OS X. For more detailed instructions, consult the installation guide. Getting the right compiler is especially confusing for Windows users. Configure a Python interpreter. Over time, Python has been built using a variety of different Windows C compilers. The configuration that PDAL uses is valuable raw materials for configuring your own environment because the PDAL team must keep it up to date with both the Conda environment and the Microsoft compiler situation. For example, you can use "python=2. In that case, please just reply saying that you're on Py3, and we can investigate further. Anaconda Python is an Python Language with support to develoment applications in Python for the. The following workaround, making and invoking a new environment, does work: "conda create -n vpclean -c vpython vpython python=3" followed by "source activate vpclean". So, using the compiler(‘c’) function in a conda recipe will pull in the correct compiler for any build platform. While we cannot provide these for all platforms, below you'll find links to binaries for various platforms where creating them by yourself is not easy due to various reasons. To install this dependency manually (probably not needed unless you are an MFiX developer), run the following command in the Anaconda prompt:. The new channel is given the top priority within defaults and holds packages built with the new compiler stack. This website stores cookies on your computer. KmerGenie ----- installation: 1) Prerequisite: Python >= 2. 0 astroid babel In contrast, if you fail to specify an interpreter, as with conda create --name env-00, the environment won't appear in the list. conda install binutils c-compiler compilers cxx-compiler fortran-compiler It is possible to list all of the versions of binutils available on your platform with: conda search binutils --channel conda-forge About conda-forge. You need at least conda 4. Conda Binary Distribution¶. By using our site, you consent to cookies. Getting the right compiler is especially confusing for Windows users. Using Conda forge Command : This type of installation will guarantee that package will be downloaded to the system. ```bash $ conda search --override-channels that removes all potential abi incompatible packages resulting from the compiler switchover from conda. x? Xcode includes command line development tools such as gcc and friends. In PyCharm you are not limited to using just any single Python interpreter. WhatsHap is implemented in C++ and Python. Use conda's pinning mechanism in your environment to control which variant you want. JavaScript is required for this form. Benefits of conda vs. But it’s a lot better than anything out there, and the only one I would recommend, at least on Windows. conda install gensim I tried pip and other methods for gensim, but ran into problems (see below). conda install -c conda-forge compilers Description This package is a generic way to obtain the compilers for your system that conda-forge used to compile its ecosystem. Download Anaconda from here. To keep compatibility with Intel MPI on Windows, at this time one would consider the. Conda-build 3 defines a special jinja2 function, compiler(), to make it easy to specify compiler packages dynamically on many platforms. If this sounds familiar, you might want to check conda the package manager, Anaconda, the distribution, conda forge, and conda build. Hi, Building cx_Oracle requires you to have working C(++) compiler since cx_Oracle is written in C, not in Python even it's a Python module. Optimizing compiler for evaluating mathematical expressions on CPUs and GPUs. Please don't forget that this is a Wiki. NVIDIA worked with The Portland Group (PGI) to develop a CUDA Fortran Compiler that provides Fortran language support for NVIDIA's CUDA-enabled GPUs. 16 July 2010. 6 version), here is an installation guide:. The mapping between what is displayed in the Python version and the actual Visual Studio version is given in this table taken from stackoverflow. Often times, you need c or gcc compiler to compile open source projects in Mac OS X. Both of them provide support for direct command-line interaction, as well as a server mode. The only prerequisite that you have to have is a working C compiler. I'm able to install it using -- WARNING (theano. Conda is an open-source package manager and virtual environment manager for installing packages from Conda compatible distributions. If you want to install Caffe on Ubuntu 16. 在莫烦Python教程的“Dropout 解决 overfitting”一节中,出现错误如下: InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]. Search for default known paths for conda environments on windows. Anaconda compiler tools — conda build 3 - docs. 0 and conda 4. this project containing the Anaconda Python compiler with tools without the Anaconda Python Studio IDE. Installing GCC: Binaries We are often asked about pre-compiled versions of GCC. How do I install gcc on Mac OS X 10. condaPath is set. LSCSoft Conda¶. NumPy; Then you can build and install Numba from the top level of the source tree:. Package plan for installation in environment /Users/jreback/miniconda3/envs/pyarrow-dev:. Over time, Python has been built using a variety of different Windows C compilers. I need to compile a few apps and Perl modules. You can use conda to build any software quite well. Conda is an open-source package manager and virtual environment manager for installing packages from Conda compatible distributions. 2 for Linux and Clang 4. Create Conda environment: Switches to the Python Environments window in which you enter a name for the environment and specify its base interpreter. But it’s a lot better than anything out there, and the only one I would recommend, at least on Windows. If you have a Conda environment, depending on how it is installed, it may just show up in the list of kernels you can use. In compiling TBB, a conda-forge contributor ran across issues with CMake not finding the VS compiler for VS 2008. Cython is an optimising static compiler for both the Python programming language and the extended Cython programming language (based on Pyrex). Code, Compile, Run and Debug python program online. sh script in the top-level dir of the repo. The main performance gain Cython can reach in contrast to pure Python stems from bypassing the CPython API. This guide should help clarify which version of Python uses which compiler by default. 7 is too old to compile pygmo, and thus we cannot provide conda packages for Python 2. x (since release 0. 4 March 2010. R packages. Otherwise, run this command to enable conda-forge in your installation:. Use the following installation steps: Download Anaconda. conda-build=3 gives the ability to use Anaconda 5 compilers, conda-forge is not using these compilers yet. Does anyone know if it would be possible to use the devtoolset compilers, or otherwise achieve the desired effect, in the conda-forge build system? Thanks, Peter. 1 0 conda-forge. some users want to use the latest anaconda packages but do not yet want to use the anaconda compilers. Intel 19 MPI does not support use mpi_f08 the Fortran 2008 bindings. Specifications. Anaconda is a Conda package distribution that includes many python packages and extensions. I'll give a couple of example of using conda but first here are some suggestion to get started. NumPy; Then you can build and install Numba from the top level of the source tree:. The --enable-languages=c,c++ option means that only the C and C++ compilers will be built. 2 package will be using same installation approach as parent Anaconda packages. LSCSoft Conda is a programme to manage and distribute software used by the LIGO Scientific Collaboration and partner groups using the conda package manager, and the conda-forge community. For example, you will need to use them if you wish to: Install a non-pure Python package from sources with Pip (if there is no Wheel package provided). This script creates a new isolated conda environment and runs both unit tests and doctests. If you want to create and work with Python virtual environments, please follow the instructions on venv and virtual environmen. x was the last monolithic release of IPython, containing the notebook server, qtconsole, etc. Conda is focused on a different use-case. Conda-forge is entirely community-founded and community-led, and while conda-forge is probably not yet mature enough to completely replace the default conda channel, Continuum's founders have publicly stated that this is a direction they would support. conda install binutils c-compiler compilers cxx-compiler fortran-compiler It is possible to list all of the versions of binutils available on your platform with: conda search binutils --channel conda-forge About conda-forge. conda create -n pmp -c conda-forge pymeep=*=mpi_mpich_* conda activate pmp The first * requests the latest version of Pymeep, and the mpi_mpich_* says to get a version that includes "mpi_mpich" in the build string (the packages are currently built with the MPICH implementation of MPI). Package plan for installation in environment /Users/jreback/miniconda3/envs/pyarrow-dev:. Regarding the SPAMS-python package: In addition, a version of the SPAMS Python library (available here) is maintained by John Kirkham on the conda-forge (an open source community-led packaging effort supplying release quality binary packages for use on the platforms Mac and GNU/Linux with the conda package manager). For packages scanned in the last 2 weeks see cdn clone rss feed. In Windows, the situation is a bit more complicated. A common installation problem under recent Linux distribution is the incompatibility of the compiler version used to compile the Python binary shipped by AnaConda and the compiler installed by the distribution. For additional conda command documentation see https://conda. Use conda's pinning mechanism in your environment to control which variant you want. P SI 4 is available as a pre-compiled binary for Mac and Linux (and Windows, through the Ubuntu shell) architectures through Continuum Analytics, the company that produces Anaconda Python (a full-fledged scientific python environment with package manager conda) and, more particularly, Miniconda (a lightweight python distribution with same package manager conda). You need to have a C++ compiler, Python 3. Anaconda is a Conda package distribution that includes many python packages and extensions. I write scientific software (primarily a mix of C++ and Python), and I use conda for literally every dependency I need, including pure C or C++ dependencies. Anaconda is a data science platform that comes with a lot of useful features right out of the box. Unfortunately the latest virtualenv, 1. 7 (however, we do provide conda packages for Python 3. conda info -e. MinGW-w64 (Minimalist GNU for Windows, 64-bit) is a fork of the earlier MinGW GCC (GNU Compiler Collection: C, C++ and Fortran compilers and associated tools). functools_lru_cache. For more information about compilers with conda build see compiler-tools. If you use conda to install wrf-python on a supercomputer like Yellowstone or Cheyenne, we recommend that you do not load any python related modules via the 'module load' command. This one doesn't. Choose Python 3. Anaconda is the installation program used by Fedora, Red Hat Enterprise Linux and some other distributions. com offers the best prices on Computers, Computer Parts, Laptops, Hard Drives, PC Hardware & Accessories with fast shipping and top-rated customer service. 4 numpy pip mingw conda create -n py3. This project is still under planning phase. Over time, Python has been built using a variety of different Windows C compilers. Anyone interested in porting Psyco to it is welcome. The bin directory contains the scripts needed to compile and run Kotlin on Windows, OS X and Linux. Installation¶. That will get you started and it wont take long for you to realize how powerful and useful conda is. Check here to find the appropriate packages for your platform. Use conda's pinning mechanism in your environment to control which variant you want. To install these dependencies manually (probably not needed unless you are an MFiX developer), run the following command in the Anaconda prompt:. It provides a way to implement custom GPU algorithms in purely Python syntax when the cudatoolkit package is present. With PyCharm, you can access the command line, connect to a database, create a virtual environment, and manage your version control system all in one place, saving time by avoiding constantly switching between windows. To install mingw-w64 compiler type:. The latest release is 1. The compiler tools section of the conda docs has much more info. py build_ext --inplace --compiler=msvc Using Windows SDK C/C++ compiler (works for all Python versions) The standard way to compile C extensions for CPython (including Cython extensions) is to install the compiler that was used to compile the CPython interpreter. conda create -n local python=3 anaconda If you like to install a specific version of python, you can specify it with "python" option. The Anaconda company supplies us with recent and well integrated compilers. But, lately, I try conda build --build-recipe and typically can get a conda package if it's a straightforward pip package. The majority of all new Anaconda, Inc. Anaconda Accelerate opens up the full capabilities of your GPU or multi-core processor to the Python programming language. Harnessing the Power of Python in ArcGIS Using the Conda Distribution Author: Esri Subject: 2017 Esri Developer Summit-International--Presentation Keywords: 2017 Esri Developer Summit-International--Presentation, 2017 Esri Developer Summit-International, Harnessing the Power of Python in ArcGIS Using the Conda Distribution Created Date. As a well informed reader commented, this does not correspond to the actual Visual Studio major version. Miniconda includes a much smaller set of core packages along with Conda. As of IPython 4. If you use conda to install wrf-python on a supercomputer like Yellowstone or Cheyenne, we recommend that you do not load any python related modules via the 'module load' command. Creating a conda package with compilation and dependencies. We are assuming that you have default Python environment already configured on your computer and you intend to install scikit-image inside of it. Getting the right compiler is especially confusing for Windows users. ```bash $ conda search --override-channels that removes all potential abi incompatible packages resulting from the compiler switchover from conda. Install Nvidia driver and Cuda (Optional) If you want to use GPU to accelerate, follow instructions here to install Nvidia drivers, CUDA 8RC and cuDNN 5 (skip caffe installation there). The C++17 standard is the default for Mac and Linux wheels; it is C++14 for Windows (compiler limitation). The Cygwin DLL currently works with all recent, commercially released x86 32 bit and 64 bit versions of Windows, starting with Windows Vista. Download the Automated MinGW Installer and double-click on it to launch the installation process. sh build with your own intel compilers `psi4-path-advisor --intel` build with add'l cmake options and objdir postfix. Often times, you need c or gcc compiler to compile open source projects in Mac OS X. The conda package manager and it's subproject conda-build are fantastic tools to solve this problem. Install additional packages into your development environment: conda install jupyter ipython matplotlib pytest nose flake8. In this Python Tutorial, we will be learning how to install Anaconda by Continuum Analytics. To verify that a clone has been created, use the command. NumPy does not require any external linear algebra libraries to be. Psyco is unmaintained and dead. We can download it from GitHub Releases. conda-env 2. Since I think most of us are using some *nix OS on the RPi, we probably have compilers, and pip is pretty good at compiling things for you automatically. this project containing the Anaconda Python compiler with tools without the Anaconda Python Studio IDE. LSCSoft Conda is a programme to manage and distribute software used by the LIGO Scientific Collaboration and partner groups using the conda package manager, and the conda-forge community. I write scientific software (primarily a mix of C++ and Python), and I use conda for literally every dependency I need, including pure C or C++ dependencies. 5; To install this package with conda run one of the following: conda install -c conda-forge gcc conda install -c conda-forge/label/cf201901 gcc. Then run conda install -c conda. Anaconda Python is an Python Language with support to develoment applications in Python for the. 1 Optional Install Coral edge tpu compiler. 26 do not have the main channel included as part of the defaults channels. Open MPI: Version Windows Binary Installer Notes. However, like any large research level program it can be challenging to install and configure. Visual Studio 2008 / VS Compiler for Python. 7 is too old to compile pygmo, and thus we cannot provide conda packages for Python 2. Anaconda Accelerate opens up the full capabilities of your GPU or multi-core processor to the Python programming language. Conda can quickly install, run and update packages and their dependencies. For more information on the conda command line, see Conda environments. Compilers for other languages, such as Fortran, Java and Go, will be excluded. A C compiler compatible with your Python installation. The conda packages for 64bit linux are also found at atztogo channel: %. Creating a new topic to continue the discussion about binary and compiler compatibility started here in the context of QML. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. php(143) : runtime-created function(1) : eval()'d code(156) : runtime-created. a build system turning these recipes into conda packages. Conda is the package manager that the Anaconda distribution is built upon. Compilers from other vendors such as Intel, Absoft, Sun, NAG, Compaq, Vast, Porland, Lahey, HP, IBM, Microsoft are only supported in the form of community feedback, and may not work out of the box. With Anaconda, just run (in Anaconda Prompt if on Windows) conda update anaconda to update the distribution as a whole and conda update spyder to update Spyder specifically. Alternatively, we suggest to install OpenBLAS, with the development headers (-dev, -devel, depending on your Linux distribution). The system installation of Python was compiled with the GNU compilers, and this will help avoid any unnecessary complications. See Conda environments. Then read some of the Using conda documentation. All code in a Python project runs within the context of a specific environment, such as a global Python environment, an Anaconda environment, a virtual environment, or a conda environment. The packages installed by the 'module load' system will not play nicely with packages installed via conda. Compilers for other languages, such as Fortran, Java and Go, will be excluded. Over time, Python has been built using a variety of different Windows C compilers. The detailed installation processes for different environments are described below. 2016-12-01: lda: public: Topic modeling with latent Dirichlet allocation 2016-12-01: pbr: public: Python Build Reasonableness 2016-12-01: nltk: public: Natural Language Toolkit 2016-12-01: python-linkedin: public: Python Interface to the LinkedIn API 2016-12-01. How can I run "conda" to install dependencies? I'm trying to use the Python Tool, and here's the scenario we've uncovered -- One of our Python developers has made great use of a library, pymc3. For instructions on how to quickly download and install MinGW (including GCC compilers for C, C++, Fortran, Java, and Ada, binutils, Windows API, runtime, and make), please refer to the instructions for Getting Started with MinGW. This week you'll meet Phil Elson, Kale Franz, and Michael Sarahan who all work on various parts of this ecosystem. If you are having difficulty installing DSC and its dependnencies directly from source, we recommend switching to using conda. To activate the conda environment: (should be activated before running python) source activate myPythonEnv Once the environment is activated, user can update or install packages via conda or pip. Make sure that your setuptools package has at least version 34. But it's a lot better than anything out there, and the only one I would recommend, at least on Windows. Pythran is an ahead of time compiler for a subset of the Python language, with a focus on scientific computing. Bokeh Menu Menu. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: