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Apart from Python Generalist course which suits to requirements of a Tech Graduate, TGC also conducts professional level modules in Data Sciences including using Python with Data Analytics Course, Data Visualisation and Machine learning along with Framework Django, Python with MongoDB, Flask, Python for Testing, Advanced Python etc. Following is the course outline for our generalist course in Python for Tech Graduates, For other courses Please request course brochure. Python Training Learn From TGC. Python for Windows. We don't have any change log information yet for version 3.6.5 of Python. Sometimes publishers take a little while to make this information available, so please check back in a few days to see if it has been updated. Can you help? If you have any changelog info you can share with us, we'd love to hear from you! Head over to ourContact pageand let us know. Explore Apps. Related Software. Python Tools for Visual Studio. Python Tools for Visual Studio, or PTVS as it is more commonly known, is an open-source plug-in for Visual Studio that supports programming with the Python language. Key Features include: Supp. Numerical Python. Numerical Python (NumPy) is a package for scientific computing with Python. It adds a fast and sophisticated array facility to the Python language. Numerical Python contains: A powerful N-dime. Notepad++ (64-bit) Notepad++ is a free source code editor and Notepad replacement that supports several languages. Running in the MS Windows environment, its use is governed by GPL Licence. Based on a powerful editing. Microsoft Silverlight. Microsoft Silverlight is a programmable web browser plugin that enables features such as animation, vector graphics and audio-video playback so you can experience rich Internet applications. Silverli. Python 3.6.5rc1. Python 3.6.5rc1 is a release candidate preview of the fifth maintenance release of Python 3.6. The Python 3.6 series contains many new features and optimizations. Among the new major new features in Python 3.6 are: , Preserving Keyword Argument Order , Simpler customization of class creation , Local Time Disambiguation , Literal String Formatting , Adding A Secrets Module To The Standard Library , Add a private version to dict , Underscores in Numeric Literals , Adding a file system path protocol , Preserving Class Attribute Definition Order , Adding a frame evaluation API to CPython , Make os.urandom() blocking on Linux (during system startup) , Asynchronous Generators (provisional) , Syntax for Variable Annotations (provisional) , Change Windows console encoding to UTF-8 , Change Windows filesystem encoding to UTF-8 , Asynchronous Comprehensions. Please see What’s New In Python 3.6 for more information. Note that 3.6.5rc1 is a preview release and thus its use is not recommended for production environments. Установите TensorFlow с помощью pip. 1. Установите среду разработки Python в вашу систему. Убедитесь, что ваша среда Python уже настроена: Если эти пакеты уже установлены, переходите к следующему шагу. В противном случае установите Python , диспетчер пакетов pip и venv : Ubuntu. macOS. Установите с помощью диспетчера пакетов Homebrew : Установите распространяемый компонент Microsoft Visual C ++ для Visual Studio 2015, 2017 и 2019 . Начиная с версии msvcp140_1.dll 2.1.0, из этого пакета требуется файл msvcp140_1.dll (который может не предоставляться из старых распространяемых пакетов). Распространяемый пакет поставляется с Visual Studio 2019, но может быть установлен отдельно: Перейдите к загрузкам Microsoft Visual C ++ , Прокрутите страницу вниз до раздела Visual Studio 2015, 2017 и 2019 . Загрузите и установите распространяемый компонент Microsoft Visual C ++ для Visual Studio 2015, 2017 и 2019 для своей платформы. Установите 64-разрядную версию Python 3 для Windows (выберите pip в качестве дополнительной функции). Другой. 2. Создайте виртуальную среду (рекомендуется). Виртуальные среды Python используются для изоляции установки пакета от системы. Ubuntu / macOS. Создайте новую виртуальную среду, выбрав интерпретатор Python и ./venv каталог ./venv для его хранения: Активируйте виртуальную среду с помощью специальной команды оболочки: Когда виртуальная среда активна, приглашение оболочки имеет префикс (venv) . Устанавливайте пакеты в виртуальной среде, не влияя на настройку хост-системы. Начните с обновления pip : И чтобы выйти из виртуальной среды позже: Создайте новую виртуальную среду, выбрав интерпретатор Python и .\venv каталог .\venv для его хранения: Активируйте виртуальную среду: Устанавливайте пакеты в виртуальной среде, не влияя на настройку хост-системы. Начните с обновления pip : И чтобы выйти из виртуальной среды позже: Конда. Хотя рекомендуется использовать пакет pip, предоставляемый TensorFlow, доступен пакет Anaconda, поддерживаемый сообществом . Чтобы установить, прочтите руководство Anaconda TensorFlow . 3. Установите пакет pip TensorFlow. Выберите один из следующих пакетов TensorFlow для установки из PyPI : tensorflow последний стабильный выпуск с поддержкой CPU и GPU (Ubuntu и Windows) . tf-nightly nightly - предварительная сборка (нестабильная) . Ubuntu и Windows включают поддержку графического процессора . tensorflow==1.15 версия TensorFlow 1.x. Установка виртуальной среды. Установка системы. Расположение пакета. Для некоторых механизмов установки требуется URL-адрес пакета TensorFlow Python. Указанное вами значение зависит от вашей версии Python. Версия URL Linux Поддержка графического процессора Python 3.6 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu- 2.5.0-cp36-cp36m-manylinux2010_x86_64.whl Python 3.6 только для ЦП https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu- 2.5.0-cp36-cp36m-manylinux2010_x86_64.whl Поддержка графического процессора Python 3.7 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.5.0-cp37-cp37m-manylinux2010_x86_64.whl Python 3.7 только для ЦП https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.5.0-cp37-cp37m-manylinux2010_x86_64.whl Поддержка графического процессора Python 3.8 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.5.0-cp38-cp38-manylinux2010_x86_64.whl Python 3.8 только для ЦП https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.5.0-cp38-cp38-manylinux2010_x86_64.whl Поддержка графического процессора Python 3.9 https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.5.0-cp39-cp39- manylinux2010_x86_64.whl Python 3.9 только для ЦП https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.5.0-cp39-cp39- manylinux2010_x86_64.whl macOS (только для ЦП) Python 3.6 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.5.0-cp36- cp36m-macosx_10_11_x86_64.whl Python 3.7 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.5.0-cp37-cp37m- macosx_10_11_x86_64.whl Python 3.8 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.5.0-cp38-cp38- macosx_10_11_x86_64.whl Python 3.8 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.5.0-cp39-cp39- macosx_10_11_x86_64.whl Окна Поддержка графического процессора Python 3.6 https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.5.0-cp36-cp36m-win_amd64.whl Python 3.6 только для ЦП https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.5.0-cp36-cp36m-win_amd64.whl Поддержка графического процессора Python 3.7 https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.5.0-cp37-cp37m-win_amd64.whl Python 3.7 только для ЦП https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.5.0-cp37-cp37m-win_amd64.whl Поддержка графического процессора Python 3.8 https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.5.0-cp38-cp38- win_amd64.whl Python 3.8 только для ЦП https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.5.0-cp38-cp38- win_amd64.whl Поддержка графического процессора Python 3.9 https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu- 2.5.0-cp39-cp39-win_amd64.whl Python 3.9 только для ЦП https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.5.0- cp39-cp39-win_amd64.whl. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Python version 3.6.5 download. Learn the difference between the Chocolatey Editions and what will fit your needs the best. I'm ready to get started now! Search the largest online registry of Windows packages. Chocolatey packages encapsulate everything required to manage a particular piece of software into one deployment artifact by wrapping installers, executables, zips, and scripts into a compiled package file. New to Chocolatey? Learn the requirements and how to get Chocolatey up and running in no time! Need help? Read our Support FAQ to find out the next steps. Welcome to the Chocolatey Community Package Repository! 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Your use of the packages on this site means you understand they are not supported or guaranteed in any way. Learn more. Passing Failing Pending Unknown / Exempted. Downloads: 6,988,377. Downloads of v 3.6.5: 63,222. Last Update: 29 Mar 2018. Package Maintainer(s): chocolatey-community purity. Software Author(s): Python Software Foundation. Tags: Software Specific: Package Specific: Download. Python. This is not the latest version of Python available. 3.6.5 | Updated: 29 Mar 2018. Software Specific: Package Specific: Download. chocolatey-community purity. Python Software Foundation. Edit Package. To edit the metadata for a package, please upload an updated version of the package. Chocolatey's Community Package Repository currently does not allow updating package metadata on the website. This helps ensure that the package itself (and the source used to build the package) remains the one true source of package metadata. This does require that you increment the package version. This is not the latest version of Python available. This Package Contains an Exempted Check. Not All Tests Have Passed. Validation Testing Passed. Verification Testing Exemption: Python3 is bypassing verifier, so this package will need to as well. Scan Testing Successful: No detections found in any package files. Individual Organization. Install Upgrade Uninstall. To install Python, run the following command from the command line or from PowerShell: To upgrade Python, run the following command from the command line or from PowerShell: To uninstall Python, run the following command from the command line or from PowerShell: NOTE: This applies to both open source and commercial editions of Chocolatey. 1. Ensure you are set for organizational deployment. Open Source or Commercial: Proxy Repository - Create a proxy nuget repository on Nexus, Artifactory Pro, or a proxy Chocolatey repository on ProGet. Point your upstream to https://community.chocolatey.org/api/v2 . Packages cache on first access automatically. Make sure your choco clients are using your proxy repository as a source and NOT the default community repository. See source command for more information. You can also just download the package and push it to a repository Download. Open Source Download the Package Download Run choco download python --internalize --version=3.6.5 -- source=https://community.chocolatey.org/api/v2 (additional options) Run choco push --source="'http://internal/odata/repo'" for package and dependencies. 3. Enter your internal repository url. 4. Choose your deployment method: Generic Ansible Chef Otter PS DSC Puppet Salt. Add this to a PowerShell script or use a Batch script with tools and in places where you are calling directly to Chocolatey. If you are integrating, keep in mind enhanced exit codes. If you do use a PowerShell script, use the following to ensure bad exit codes are shown as failures: Requires Otter Chocolatey Extension. See docs at https://inedo.com/den/otter/chocolatey. Requires cChoco DSC Resource. See docs at https://github.com/chocolatey/cChoco. Requires Puppet Chocolatey Provider module. See docs at https://forge.puppet.com/puppetlabs/chocolatey. 5. If applicable - Chocolatey configuration/installation. See infrastructure management matrix for Chocolatey configuration elements and examples. This package was approved as a trusted package on 29 Mar 2018. Python is a programming language that lets you work more quickly and integrate your systems more effectively. You can learn to use Python and see almost immediate gains in productivity and lower maintenance costs. Notes. This package depends on the the latest major version of python package. Log in or click on link to see number of positives. python.3.6.5.nupkg (96d213292b52) - ## / 60. In cases where actual malware is found, the packages are subject to removal. Software sometimes has false positives. 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