setuptools

安装TensorFlow报错 安装TensorFlow报错 错误一：Cannot uninstall 'wrapt'. 错误二： setuptools 版本太低 安装TensorFlow报错 错误一：Cannot uninstall ‘wrapt’. ERROR: Cannot uninstall ‘wrapt’. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall. 强制更新： pip install -U --ignore-installed wrapt enum34 simplejson netaddr 错误二： setuptools 版本太低 ERROR: tensorboard 1.14.0 has requirement setuptools>=41.0.0, but you’ll have setuptools 39.1.0 which is incompatible. 强制更新： pip install --upgrade setuptools 来源： https://blog.csdn.net/Naploen8/article

一、安装python 1.下载安装包：https://www.python.org/ftp/python/2.7.13/Python-2.7.13.tgz 2.安装python [root@localhost mnt]# tar -xvzf Python-2.7.13.tgz [root@localhost mnt]# cd Python-2.7.13 [root@localhost Python-2.7.13]# ./configure --prefix=/usr/local/python27 checking build system type... x86_64-unknown-linux-gnu checking host system type... x86_64-unknown-linux-gnu checking for --enable-universalsdk... no checking for --with-universal-archs... 32-bit checking MACHDEP... linux2 checking EXTRAPLATDIR... checking for --without-gcc... no checking for gcc... no checking for cc... no checking for cl.exe...

one_file.py contains some general functions, classes, and a main() . I'd like to make it pip installable with a command line script that calls the main() function. What's a directory structure and setup.py that will do this? You can get away with this with just a setup.py and your module--no additional directories. In your setup.py just use setup(..., py_modules=['one_file'], ...) (you might want to check on the exact spelling). To install the script you can use the console_scripts entry-point: from setuptools import setup setup( name='one-file', version='1.0', py_modules=['one_file'], entry

I'm trying to find the function or class definition of gen_dataset_ops in tensorflow, which has its sourcecode here . I find many places where it is imported like so: from tensorflow.python.ops import gen_dataset_ops But I can't find where it is defined, I'd expect to find something like: def gen_dataset_ops(...): #Do something clever return I don't quite understand the anatomy of python modules in general, so I'm probably missing some basics here,.. any hint is welcome! tensorflow.python.ops.gen_dataset_ops is generated code. (That's why they put gen in front of the name.) You can't find it

setup.py often depends on a couple external files, most notably README.md for long_description , and maybe VERSION for version . e.g. root = os.path.dirname(os.path.abspath(__file__)) setuptools.setup( name = 'package', version = open(os.path.join(root, 'VERSION')).read().strip(), description = 'A Simple Package', long_description = open(os.path.join(root, 'README.md')).read().strip(), # ... ) However, when trying to run tests with tox on such a package, I get the following error: ERROR: invocation failed (exit code 1), logfile: .tox/py36/log/py36-6.log ERROR: actionid: py36 msg: installpkg

I am writing my own python application and I am wondering what is the correct way to include localisation in source distributions. I struggled with the documentation of setuptools ; localisation is not even mentioned there. I use pypabel to extract my message catalogues and to compile them. Questions Is there a possibility to compile *.po to *.mo automatically before creating a source package with setup.py? Currently I have to compile everything before manually for each language... Where should I include those *.mo -files? Several linux distributions have different places for those files. In

I have a python project that has a few dependencies (defined under install_requires in setup.py). My ops people requires a package to be self contained and only depend on a python installation. The litmus test would be that they're able to get a zip-file and then unzip and run it without an internet connection. Is there an easy way to package an install including dependencies? It is acceptable if I have to build on the OS/architecture that it will eventually be run on. For what it's worth, I've tried both setup.py build and setup.py sdist , but they don't seem to fit the bill since they do not