Pip install tensorflow ошибка

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to track, document, and discuss build and installation problems.

The following list links error messages to a solution or discussion. If you find
an installation or build problem that is not listed, please search the GitHub
issues and Stack Overflow. If you still can’t find the error message, ask a new
question on Stack Overflow with the tensorflow tag.

Unzipping simple_console_for_windows.zip to create runfiles tree...
[./bazel-bin/tensorflow/tools/pip_package/simple_console_for_windows.zip]
  End-of-central-directory signature not found.  Either this file is not
  a zipfile, or it constitutes one disk of a multi-part archive.  In the
  latter case the central directory and zipfile comment will be found on
  the last disk(s) of this archive.
unzip: cannot find zipfile directory in one of ./bazel-bin/tensorflow/tools/pip_package/simple_console_for_windows.zip or
        ./bazel-bin/tensorflow/tools/pip_package/simple_console_for_windows.zip.zip, and cannot find ./bazel-bin/tensorflow/tools/pip_package/simple_console_for_windows.zip.ZIP, period.

ImportError: libcudart.so.Version: cannot open shared object file:
  No such file or directory

ImportError: libcudnn.Version: cannot open shared object file:
  No such file or directory

libprotobuf ERROR google/protobuf/src/google/protobuf/io/coded_stream.cc:207] A
  protocol message was rejected because it was too big (more than 67108864 bytes).
  To increase the limit (or to disable these warnings), see
  
CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.

Error importing tensorflow. Unless you are using bazel, you should
  not try to import tensorflow from its source directory; please exit the
  tensorflow source tree, and relaunch your python interpreter from
  there.

IOError: [Errno 2] No such file or directory:
  '/tmp/pip-o6Tpui-build/setup.py'

ImportError: Traceback (most recent call last):
  File ".../tensorflow/core/framework/graph_pb2.py", line 6, in 
  from google.protobuf import descriptor as _descriptor
  ImportError: cannot import name 'descriptor'

SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify
  failed

  Installing collected packages: setuptools, protobuf, wheel, numpy, tensorflow
  Found existing installation: setuptools 1.1.6
  Uninstalling setuptools-1.1.6:
  Exception:
  ...
  [Errno 1] Operation not permitted:
  '/tmp/pip-a1DXRT-uninstall/.../lib/python/_markerlib' 

  ...
  Installing collected packages: setuptools, protobuf, wheel, numpy, tensorflow
  Found existing installation: setuptools 1.1.6
  Uninstalling setuptools-1.1.6:
  Exception:
  ...
  [Errno 1] Operation not permitted:
  '/tmp/pip-a1DXRT-uninstall/System/Library/Frameworks/Python.framework/
   Versions/2.7/Extras/lib/python/_markerlib'

ImportError: Traceback (most recent call last):
File ".../tensorflow/core/framework/graph_pb2.py", line 6, in 
from google.protobuf import descriptor as _descriptor
ImportError: cannot import name 'descriptor'

IOError: [Errno 2] No such file or directory:
  '/tmp/pip-o6Tpui-build/setup.py'

SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify
  failed

  Installing collected packages: setuptools, protobuf, wheel, numpy, tensorflow
  Found existing installation: setuptools 1.1.6
  Uninstalling setuptools-1.1.6:
  Exception:
  ...
  [Errno 1] Operation not permitted:
  '/tmp/pip-a1DXRT-uninstall/.../lib/python/_markerlib' 

ImportError: No module named copyreg

OSError: [Errno 1] Operation not permitted

Traceback (most recent call last):
  File "", line 1, in 
  File "/usr/local/lib/python2.7/site-packages/tensorflow/__init__.py",
    line 4, in 
    from tensorflow.python import *
    ...
  File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/tensor_shape_pb2.py",
    line 22, in 
    serialized_pb=_b('n,tensorflow/core/framework/tensor_shape.protox12ntensorflow"dnx10TensorShapeProtox12-nx03x64imx18x02
      x03(x0bx32
      .tensorflow.TensorShapeProto.Dimx1a!nx03x44imx12x0cnx04sizex18x01
      x01(x03x12x0cnx04namex18x02 x01(tbx06proto3')
  TypeError: __init__() got an unexpected keyword argument 'syntax'

...
You have not agreed to the Xcode license agreements, please run
'xcodebuild -license' (for user-level acceptance) or
'sudo xcodebuild -license' (for system-wide acceptance) from within a
Terminal window to review and agree to the Xcode license agreements.
...
  File "numpy/core/setup.py", line 653, in get_mathlib_info

    raise RuntimeError("Broken toolchain: cannot link a simple C program")

RuntimeError: Broken toolchain: cannot link a simple C program

[...stream_executordso_loader.cc] Couldn't open CUDA library nvcuda.dll

[...stream_executorcudacuda_dnn.cc] Unable to load cuDNN DSO

ImportError: Traceback (most recent call last):
File "...tensorflowcoreframeworkgraph_pb2.py", line 6, in 
from google.protobuf import descriptor as _descriptor
ImportError: cannot import name 'descriptor'

No module named "pywrap_tensorflow"

OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits

The TensorFlow library wasn't compiled to use SSE instructions

Could not find a version that satisfies the requirement tensorflow

ImportError: Traceback (most recent call last):
File ".../tensorflow/core/framework/graph_pb2.py", line 6, in 
from google.protobuf import descriptor as _descriptor
ImportError: cannot import name 'descriptor'

IOError: [Errno 2] No such file or directory:
  '/tmp/pip-o6Tpui-build/setup.py'

SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify
  failed

  Installing collected packages: setuptools, protobuf, wheel, numpy, tensorflow
  Found existing installation: setuptools 1.1.6
  Uninstalling setuptools-1.1.6:
  Exception:
  ...
  [Errno 1] Operation not permitted:
  '/tmp/pip-a1DXRT-uninstall/.../lib/python/_markerlib' 

ImportError: No module named copyreg

OSError: [Errno 1] Operation not permitted

Traceback (most recent call last):
  File "", line 1, in 
  File "/usr/local/lib/python2.7/site-packages/tensorflow/__init__.py",
    line 4, in 
    from tensorflow.python import *
    ...
  File "/usr/local/lib/python2.7/site-packages/tensorflow/core/framework/tensor_shape_pb2.py",
    line 22, in 
    serialized_pb=_b('n,tensorflow/core/framework/tensor_shape.protox12ntensorflow"dnx10TensorShapeProtox12-nx03x64imx18x02
      x03(x0bx32
      .tensorflow.TensorShapeProto.Dimx1a!nx03x44imx12x0cnx04sizex18x01
      x01(x03x12x0cnx04namex18x02 x01(tbx06proto3')
  TypeError: __init__() got an unexpected keyword argument 'syntax'

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow
  library wasn't compiled to use SSE4.1 instructions, but these are available on
  your machine and could speed up CPU computations.

ImportError: libcudart.so.8.0: cannot open shared object file:
  No such file or directory

ImportError: libcudnn.5: cannot open shared object file:
  No such file or directory

ImportError: cannot import name pywrap_tensorflow

external/local_config_cc/BUILD:50:5: in apple_cc_toolchain rule
  @local_config_cc//:cc-compiler-darwin_x86_64: Xcode version must be specified
  to use an Apple CROSSTOOL.

undefined reference to `cublasGemmEx@libcublas.so.9.0'

ModuleNotFoundError: No module named 'tensorflow.python._pywrap_tensorflow_internal'

ImportError: DLL load failed: The specified module could not be found.

Could not install packages due to an EnvironmentError: [Errno 2] No such file or directory: [long path name]

Создание и установка сообщений об ошибках

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Источник

pip Install Error: don’t could find version that satisfies the requirement tensorflow #39130

hi, I have win10 and I have tried install through cmd tensorflow with:
pip install tensorflow
pip install tensorflow-cpu
pip3 install —upgrade tensorflow

All these pip gave me the same error:

what’s happened? What I need do to fix it?

The text was updated successfully, but these errors were encountered:

I have a possibly related issue: when I use
pip install tensorflow
pip installs the most recent release candidate: https://pypi.org/project/tensorflow/2.2.0rc4/
I’m trying to get the most recent stable version, 2.1.0.

When I try:
pip install tensorflow==2.1.0

I get the error message:

I updated pip to 20.1. Same behavior.
I tried:
pip install tensorflow>=2.0.0
And still got ver 2.2.0rc4

Why is pip installing only the rc’s?

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

@an-white,
TensorFlow 2 packages require a pip version >19.0. Could you please upgrade pip using the below command and let us know if it works.

pip install —upgrade pip .

For more information please check this TensorFlow guide. Thanks!

hi, I forgot say that I have python 3.8, this can affect? When I have already upgrade pip, this occurs:

@an-white : I suggest creating a new env with python 3.7 and try installing TF2 there.

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

I saw this recommendation on other forums and tried it, but it didn’t work for me.

I’ve tried on 3.7.0 and 3.6.4

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

I saw this recommendation on other forums and tried it, but it didn’t work for me.

I’ve tried on 3.7.0 and 3.6.4

As I expected the problem was my fault. but I think is something that can pass unnoticed and explaining it here may help people with a similar setup and issue.

I’m using Python via pyenv-win which is great, but the thing is that I didn’t realize that pyenv install X.Y.Z will install the 32bit version and tensorflow requires 64bit. So, in my case, it was just a matter of installing an actual 64bit version with pyenv install X.Y.Z-amd64

hi, I forgot say that I have python 3.8, this can affect? When I have already upgrade pip, this occurs:

@an-white,
TensorFlow v2.1 is not compatible with Python 3.8. Instead, could you please try installing TF v2.2.0rc4 using the below command

pip install tensorflow==2.2.0rc4

@an-white,
Also, could you please check if you are using the 64 bit version of Python. TensorFlow is tested and supported only on 64-bit systems. Thanks!

Ok, thanks I’m going to check all this recommendation and find if works

Ready thank you so much, the problem was the version that I have of python 32 bit, and already I install the 64 bit version and only need wait for this finish

Now only need wait, any other problem I’ll tell you

Источник

pip install tensorflow could not find a version #37457

System information

• macOS Catalina version 10.15.3
• pip install tensorflow
• GPU model and memory: Intel Iris Plus Graphics 645 1536 MB

The problem
Both pip install tensorflow and pip install tf-nightly lead to the following error messages:

ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)

ERROR: No matching distribution found for tensorflow

The text was updated successfully, but these errors were encountered:

Did you try updating your pip version?

As per the documentation TensorFlow 2 packages require a pip version >19.0.

Could you please try the following commands and let us know if it works.
python3 -m pip install —upgrade pip or pip install —upgrade pip and then try

pip install tensorflow

@alexcreature Try updating pip version by:

and the you can again install tensorflow by:

or you can specify version which you want to install.

This seems to be the same as an issue I had previously with both Windows 10 and Ubuntu 18 and Ubuntu 16, no matter the operating system.
The previous issue ( #37205 ) was closed because I proposed a WORK AROUND of downloading the .whl and installing Tensorflow through the downloaded wheel, which worked just fine for me.

Something is broken in the pypi pipeline of installation and needs to be taken care of.

Yes, the issue is that systems use old pip / setuptools by default and these don’t know how to install packages with manylinux2010 tags. That’s why you need to upload pip and setuptools first (and always install in a virtualenv, not globally)

@alexcreature,
Any updates regarding this issue? Thanks!

Yes, the issue is that systems use old pip / setuptools by default and these don’t know how to install packages with manylinux2010 tags. That’s why you need to upload pip and setuptools first (and always install in a virtualenv, not globally)

Okay so here are ALL of the things I have tried in my attempts to simply install tensorflow via pip install:

pip 20.0.2
Python 3.7.6
Win10, globally
Ubuntu 18.04, globally (source built python 3.7.6 and alias setup to avoid breaking apt)
Ubuntu 16.xx, globally, same as above
Win10 pipenv environment (most recent version of pipenv)
Ubuntu 16, 18 pipenv environment (most recent version of pipenv)

I have tried and tested everything I can possibly come up with to make things different but nothing seems to install Tensorflow 2.1 for Python 3.7 for me, in any way shape or form. I have tried pip install tensorflow I have tried pip install tensorflow==2.1 and the absolute only thing I can do is install by downloading the wheel and installing that wheel directly.

Is there something we can do with pip or python source to get this back to working properly? I don’t have ANY issues with any other packages I use across the board, except for Black, but even then sometimes that will install without a hitch and other times I get the same error, though it’s been a long time since I tried and that is not relevant to Tensorflow.

Edit: I cannot find any PEP which shows a breaking change in manylinux tags and pip installs. The most relevant is 571 which states that any pip that is capable of installing manylinux2010 tags will be backwards compatible, and 600 which shows a new naming convention for manylinux tags, but also states that old tags should still work, if I’m reading correctly.
PEP 599 also adds the manylinux2014 tag, however in true python fashion, retains support for manylinux1 and manylinux2010 tags, so this definately should not be the issue, however, I am no source developer and am simply relaying the information I have found.

These are the most relevant PEP’s I have found regarding manylinux wheel tags.

Источник

Tensorflow release 2.2.0 not found via pip install #39265

tldr; pip does not find the new release 2.2.0 published yesterday

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Not Applicable
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu Server 20.04
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): Not Applicable
• Python version: 3.8.2
• PIP version: 20.1
• CUDA/cuDNN version: Not Applicable (10.2)
• GPU model and memory: Not Applicable (RTX 2080 Ti)

Describe the current behavior
From the change log and the Github releases I noticed that Tensorflow 2.2.0 was released and that I could upgrade the Tensorflow version currently used in my project (2.2.0rc4). Sadly, pip install failed to install the update as it was unable to find release 2.2.0. (Clearing the cache of pip didn’t help.) The PyPi website also says latest version is the rc4, not the 2.2.0 release.

Describe the expected behavior
Well, I would like to be able to install Tensorflow 2.2.0 over pip .

Standalone code to reproduce the issue
pip install tensorflow==2.2.0

Other info / logs

The text was updated successfully, but these errors were encountered:

Источник

Tensorflow 1.15 doesn’t exists within pip install #34302

Thank you for submitting a TensorFlow documentation issue. Per our GitHub
policy, we only address code/doc bugs, performance issues, feature requests, and
build/installation issues on GitHub.

The TensorFlow docs are open source! To get involved, read the documentation
contributor guide: https://www.tensorflow.org/community/contribute/docs

URL(s) with the issue:

Please provide a link to the documentation entry, for example:
https://www.tensorflow.org/install/pip

Description of issue (what needs changing):

It says tensorflow 1.15 is final version for 1xx versions yet pip install 1.15 returns this

«$ pip3 install tensorflow==1.15
Collecting tensorflow==1.15
Could not find a version that satisfies the requirement tensorflow==1.15 (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)
No matching distribution found for tensorflow==1.15
«

It should be corrected I think.

The text was updated successfully, but these errors were encountered:

Источник

Python is known for its versatile syntax and English-like keywords. With thousands of modules, you can do data visualization, data processing and even deploy machine learning models. There are many known machine learning models published which help you, namely, Keras, Sklearn, Tensorflow, and PyTorch. Although, while using Tensorflow, you can encounter a No Module named Tensorflow error while running your first program.

No Module Named Tensorflow Error is a known error that arises when the Python Environment is unable to fetch TensorFlow files in site-packages. There are two main reasons for this error to appear, either you have not installed the TensorFlow external module or you are working on a different python environment that doesn’t have Tensorflow. There are several easy ways to fix this error which are mentioned later in this post. Let’s understand the root cause of the error before jumping on the solution.

When a module is absent from the external site-library of the environment, the Python interpreter throws ModuleNotFoundError No Module Named Tensorflow. This error arises most of the time on low-end devices because TensorFlow requires proper setup of the c++ path and other requirements. Most of the time, this error is solved by using the pip install method. But if you have multiple Python versions installed, then you’ll definitely face this error.

Why do I get No Module Named Tensorflow Error?

There is no other reason for the No Module Named Tensorflow error other than missing module files. The main problem arises when you’re using multiple python versions and their virtual environment. Keep in mind that, Anaconda, PyCharm, Jupyter, and Spyder have their own virtual environment and it’s tricky to install modules in that environment.

Causes of No Module Named Tensorflow Error

There are some known causes of this ModuleNotFoundError. As Python lets you handle these errors easily, you can debug them quickly. Following are the cause of the No Module Tensorflow error –

Module Not Installed

If you haven’t installed TensorFlow yet and tried importing TensorFlow in code, then it’ll throw this error. Modules are managed by ‘pip’ which is a package management system for your python. Most of the time, the users forget to tick Add Python to the PATH option while installing it. This creates problems in managing the modules.

Supporting Module Not Installed

Tensorflow has many other supporting modules like numpy, scipy, jupyter, matplotlib, pillow, and scikit-learn. If any of these modules is absent, then it’ll throw an error. Make sure that these modules exist in your library.

Moreover, there are other supporting TensorFlow modules like, tensorflow-addons, tensorflow.contrib which might be absent from your library leading to this error.

Tip: To check which libraries are installed in your environment, enter pip list on your console.

Working on Different Virtual Environment

Virtual Environment: Method by which you isolate your working Python environment from the globally installed Python. This environment has its own installation directories and doesn’t share the libraries from globally installed Python.

Many of the code editors in Windows come with their own virtual environment. Each of these environments acts independently to global python installation and is started with blank external modules. Many times, you install a module but it’s installed on global python, not the python from your virtual environment. This can lead to ModuleNotFoundError No Module named Tensorflow in the code execution.

Code editors namely, Anaconda, Jupyter, and Spyder have their own virtual environment. If you have a similar case, head over to the corresponding solution for each code editor.

Solutions for No Module Named Tensorflow

Following are the solutions for this error in each code editor and OS –

Windows

In Windows, the path-related issues harras the programmers all the time. As you have limited functionality over the terminal, you’re constantly facing with ModuleNotFoundError error. To install TensorFlow in your Windows, make sure you follow these steps –

1. Uninstall existing python versions to avoid any conflicts.
2. Go to Python.org and install the Python setup. Make sure you install the 64-bit version. Unfortunately, Tensorflow is not supported in 32 bit systems.
3. Open the installer and select the “Add Python x.x to your PATH” option. This will ensure, that python executes from the path.
4. After installing, open the command terminal or PowerShell and enter the command pip install tensorflow in it.
5. Wait for it to finish the installation and run your python file by command python file.py

Linux

In Linux, it’s relatively easier to install TensorFlow. First of all, check if you are working on a virtual environment by a command which python. This command will return the path of python which you’re going to execute. If you are in a virtual environment, either leave the environment directory or enter the command deactivate to deactivate the virtual environment.

Note: Please do not try to uninstall python in Linux as it’ll interfere with your GDM (Graphical Display Manager). Instead, install a new version and then create your own virtual environment.

Follow these steps to install Tensorflow in Linux –

sudo pip3 install tensorflow

Mac

In Mac, No Module named Tensorflow is a persistent error because of environment errors. If you are working on your virtual environment, you need to deactivate and activate it again. Then use the pip list command to check if the TensorFlow module exists in your library. If not, then use the pip3 install tensorflow to install TensorFlow.

Anaconda

If you’re using Anaconda and you face no module named Tensorflow error, then you probably haven’t installed TensorFlow in the conda environment. As anaconda has a different environment than your default python environment, you need to install TensorFlow in it. To do it follow these steps –

1. Open Anaconda Prompt on your computer.
2. Enter the command conda install tensorflow in it.
3. Wait for the installation to complete and restart the conda shell and run your program.

Jupyter

If you’ve installed Juptyter Notebook from Anaconda, it’ll use a conda environment. By default, the libraries in this environment need to be installed via command. To do the same, open your Conda Prompt and enter the command conda install tensorflow. This will ensure that your Juptyer Notebook has TensorFlow in it.

If your Jupyter is not installed via Anaconda, then use the pip install tensorflow to install the TensorFlow module. This will resolve the error ModuleNotFoundError No module named Tensorflow instantly.

Spyder

Spyder is installed via Anaconda which operates an Anaconda environment. Simply use the command conda install tensorflow in your Anaconda Prompt to install TensorFlow.

PyCharm

PyCharm is a special application that operates in its own virtual environment. Due to the unavailability of the TensorFlow error, you can face the no module found error. Follow these steps to install TensorFlow –

1. Press Settings and select the Project Interpreter tab under projects.
2. Now enter Tensorflow in the box and install it.
3. After installing the package, your error will be resolved.

Supporting ModuleNotFoundError for Tensorflow

Tensorflow has many addons which come in handy to avoid writing long code. These addons and contributions are added separately in other packages and combine with the original TensorFlow module. Following are the examples of ModuleNotFoundError –

No module named ‘tensorflow.contrib’

Unfortunately, the contrib module in TensorFlow is not included in version 2.0. If you still want to use the contrib module, you’ll have to install the previous version of TensorFlow. Follow these steps –

pip uninstall tensorflow
pip install tensorflow==1.13.2

No module named ‘tensorflow_addons’

Use pip install tensorflow-addons to install the addons for TensorFlow.

No Module Named Tensorflow Still Not Resolved?

If you’ve tried all the methods and were still not able to solve the issue then, there might be some hardware limitations. Tensorflow requires Python 3.5-3.7, 64-bit system, and pip>=19.0. If you’re unable to fulfill these hardware + software requirements, then don’t worry, we still have a solution for you!

Google released a free product named ‘Colab‘ in 2018. Colab allows you to run and test machine learning models online. To explain more, it’s a replica of the jupyter notebook with all modules installed. To use Tensorflow in Google Colab follow these steps –

1. Sign in to your Google account.
2. Open Colab in your browser.
3. Create a new Jupyter Notebook. (This notebook will be saved in your google drive).
4. Type your code and run it.

Colab has many libraries like TensorFlow, numpy, pandas, etc pre-installed in its shell. Make sure you make good use of it.

Tip: Do not use Colab to store/process peer-to-peer files. This may result in a ban!

See Also

Conclusion

Tensor flow has a flexible architecture. The easy deployment of the code makes it special in nature. However, we have to be very careful before using it. Any small syntax error can result in incorrect importing of the library.

При попытке установить tensorflow: py -3.8 -m pip install —user —upgrade tensorflow
Вылетает ошибка о разрыве соединения, при чем интернет стабильный:
Requirement already satisfied: tensorflow in c:pythonpython38libsite-packages (2.2.0)
Collecting tensorflow
Downloading tensorflow-2.4.0-cp38-cp38-win_amd64.whl (370.7 MB)
|█████████▌ | 111.6 MB 128 kB/s eta 0:33:35ERROR: Exception:
Traceback (most recent call last):
File «C:PythonPython38libsite-packagespip_vendorurllib3response.py», line 438, in _error_catcher
yield
File «C:PythonPython38libsite-packagespip_vendorurllib3response.py», line 519, in read
data = self._fp.read(amt) if not fp_closed else b»»
File «C:PythonPython38libsite-packagespip_vendorcachecontrolfilewrapper.py», line 62, in read
data = self.__fp.read(amt)
File «C:PythonPython38libhttpclient.py», line 454, in read
n = self.readinto(b)
File «C:PythonPython38libhttpclient.py», line 498, in readinto
n = self.fp.readinto(b)
File «C:PythonPython38libsocket.py», line 669, in readinto
return self._sock.recv_into(b)
File «C:PythonPython38libssl.py», line 1241, in recv_into
return self.read(nbytes, buffer)
File «C:PythonPython38libssl.py», line 1099, in read
return self._sslobj.read(len, buffer)
ConnectionResetError: [WinError 10054] Удаленный хост принудительно разорвал существующее подключение

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File «C:PythonPython38libsite-packagespip_internalclibase_command.py», line 224, in _main
status = self.run(options, args)
File «C:PythonPython38libsite-packagespip_internalclireq_command.py», line 180, in wrapper
return func(self, options, args)
File «C:PythonPython38libsite-packagespip_internalcommandsinstall.py», line 320, in run
requirement_set = resolver.resolve(
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibresolver.py», line 121, in resolve
self._result = resolver.resolve(
File «C:PythonPython38libsite-packagespip_vendorresolvelibresolvers.py», line 445, in resolve
state = resolution.resolve(requirements, max_rounds=max_rounds)
File «C:PythonPython38libsite-packagespip_vendorresolvelibresolvers.py», line 339, in resolve
failure_causes = self._attempt_to_pin_criterion(name, criterion)
File «C:PythonPython38libsite-packagespip_vendorresolvelibresolvers.py», line 207, in _attempt_to_pin_criterion
criteria = self._get_criteria_to_update(candidate)
File «C:PythonPython38libsite-packagespip_vendorresolvelibresolvers.py», line 198, in _get_criteria_to_update
for r in self._p.get_dependencies(candidate):
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibprovider.py», line 170, in get_dependencies
return [
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibprovider.py», line 170, in
return [
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibcandidates.py», line 257, in iter_dependencies
requires = self.dist.requires() if with_requires else ()
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibcandidates.py», line 239, in dist
self._prepare()
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibcandidates.py», line 226, in _prepare
dist = self._prepare_distribution()
File «C:PythonPython38libsite-packagespip_internalresolutionresolvelibcandidates.py», line 318, in _prepare_distribution
return self._factory.preparer.prepare_linked_requirement(
File «C:PythonPython38libsite-packagespip_internaloperationsprepare.py», line 480, in prepare_linked_requirement
return self._prepare_linked_requirement(req, parallel_builds)
File «C:PythonPython38libsite-packagespip_internaloperationsprepare.py», line 503, in _prepare_linked_requirement
local_file = unpack_url(
File «C:PythonPython38libsite-packagespip_internaloperationsprepare.py», line 253, in unpack_url
file = get_http_url(
File «C:PythonPython38libsite-packagespip_internaloperationsprepare.py», line 130, in get_http_url
from_path, content_type = download(link, temp_dir.path)
File «C:PythonPython38libsite-packagespip_internalnetworkdownload.py», line 163, in __call__
for chunk in chunks:
File «C:PythonPython38libsite-packagespip_internalcliprogress_bars.py», line 168, in iter
for x in it:
File «C:PythonPython38libsite-packagespip_internalnetworkutils.py», line 64, in response_chunks
for chunk in response.raw.stream(
File «C:PythonPython38libsite-packagespip_vendorurllib3response.py», line 576, in stream
data = self.read(amt=amt, decode_content=decode_content)
File «C:PythonPython38libsite-packagespip_vendorurllib3response.py», line 541, in read
raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
File «C:PythonPython38libcontextlib.py», line 131, in __exit__
self.gen.throw(type, value, traceback)
File «C:PythonPython38libsite-packagespip_vendorurllib3response.py», line 455, in _error_catcher
raise ProtocolError(«Connection broken: %r» % e, e)
pip._vendor.urllib3.exceptions.ProtocolError: («Connection broken: ConnectionResetError(10054, ‘Удаленный хост принудительно разорвал существующее подключение’, None, 10054, None)», ConnectionResetError(10054, ‘Удаленный хост принудительно разорвал существующее подключение’, None, 10054, None))