使用 conda 生成的 requirements.txt 设置 virtualenv [英] Set up virtualenv using a requirements.txt generated by conda

问题描述

我正在使用 Anaconda 虚拟环境建立一个 Python 项目.我正在生成一个 requirements.txt，以便其他人可以轻松地为该项目设置他们自己的虚拟环境.

我想知道，当其他开发人员想要为该项目做出贡献，但想要使用 virtualenv 而不是 Anaconda 时，他们可以这样做吗?

我尝试了以下方法:

• 我在 Anaconda 环境中设置了一个空项目并安装了 aiohttp 模块.然后 conda list --export >requirements.txt 生成以下内容:

  # 该文件可用于创建环境:# $ conda create --name <env>--file <此文件># 平台:win-64aiohttp=2.3.9=py36_0异步超时=2.0.0=py36hc3e01a3_0证书=2018.1.18=py36_0chardet=3.0.4=py36h420ce6e_1multidict=3.3.2=py36h72bac45_0pip=9.0.1=py36h226ae91_4蟒蛇=3.6.4=h6538335_1设置工具=38.4.0=py36_0vc=14=h0510ff6_3vs2015_runtime=14.0.25123=3车轮=0.30.0=py36h6c3ec14_1wincertstore=0.2=py36h7fe50ca_0yarl=0.14.2=py36h27d1bf2_0

• 我在 virtualenv 环境中设置了一个空项目，并在那里安装了 aiohttp 模块.pip 冻结 >requirements.txt 然后生成:

  aiohttp==3.0.1异步超时==2.0.0属性==17.4.0chardet==3.0.4idna==2.6idna-ssl==1.0.0multidict==4.1.0yarl==1.1.0

所以显然两个输出是不同的，我的理论是:一旦我在我的项目中使用 conda 生成我的 requirements.txt，其他开发人员就不能选择 virtualenv - 至少如果他们不准备安装很长时间手动列出需求(当然不仅仅是 aiohttp 模块).

第一眼，在 virtualenv (pip install -r requirements-conda.txt) 上的项目中导入 conda 生成的 requirements.txt 会引发此错误:

无效要求:'aiohttp=2.3.9=py36_0'= 不是有效的运算符.你的意思是 == ?

我是否认为如果开发人员想要这样做，他们需要以编程方式将包列表更改为 virtualenv 理解的格式，或者他们必须手动导入所有包?这意味着如果他们想节省一些额外的工作，我也强迫他们选择 conda 作为虚拟环境?

解决方案

我正在使用 Anaconda 虚拟环境建立一个 Python 项目.不过，我想知道，当其他开发人员想要为该项目做出贡献，但想要使用 virtualenv 而不是 Anaconda 时，他们可以这样做吗?

是的 - 事实上，这就是我的许多项目的结构.为了完成您要查找的内容，这里有一个我们将用作参考的简单目录:

<预><代码>.├── README.md├──应用│ ├── __init__.py│ ├──静态│ ├──模板├── 迁移├── app.py├──环境.yml├──需求.txt

在上面的项目目录中，我们有 environment.yml(对于 Conda 用户)和 requirements.txt(对于 pip).

environment.yml

<块引用>

所以显然两个输出是不同的，我的理论是:一旦我在我的项目中使用 conda 生成我的 requirements.txt，其他开发人员就不能选择 virtualenv - 至少如果他们不准备安装很长时间手动列出需求(当然不仅仅是 aiohttp 模块).

为了解决这个问题，我们使用了两个不同的环境文件，每个文件都有自己独特的格式，允许其他贡献者选择他们喜欢的一个.如果 Adam 使用 Conda 来管理他的环境，那么他只需从 environment.yml 文件中创建他的 Conda:

conda env create -f environment.yml

yml 文件的第一行设置新环境的名称.这就是我们创建 Conda 风格的环境文件的方式.激活您的环境(source activate 或 conda activate)然后:

conda env export >环境.yml

实际上，因为conda env export命令创建的环境文件同时处理环境的pip包和conda包，我们不甚至不需要有两个不同的进程来创建这个文件.conda env export 将导出您环境中的所有包，而不管它们是从哪个渠道安装的.它也会在 environment.yml 中记录此内容:

名称:awesomeflask渠道:- 蟒蛇- 康达锻造- 默认值依赖项:- appnope=0.1.0=py36hf537a9a_0- 回拨=0.1.0=py36_0- cffi=1.11.5=py36h6174b99_1- 装饰器=4.3.0=py36_0- ...

requirements.txt

<块引用>

我是否认为如果开发人员想要这样做，他们需要以编程方式将包列表更改为 virtualenv 理解的格式，或者他们必须手动导入所有包?这意味着如果他们想节省一些额外的工作，我也强迫他们选择 conda 作为虚拟环境?

推荐的(和传统的)方法是通过 requirements.txt _change 为 pip 理解 的格式.激活您的环境(source activate 或 conda activate)然后:

pip freeze >要求.txt

假设 Eve，项目贡献者之一想要从 requirements.txt 创建一个相同的虚拟环境，她可以:

# 使用 pippip install -r requirements.txt# 使用康达conda create --name --文件要求.txt

完整的讨论超出了这个答案的范围，但是

这就像确保每次安装新的依赖项时，我们都运行 conda env export 和 pip freeze > 一样简单.requirements.txt 命令.

I'm setting up a python project, using an Anaconda virtual environment. I'm generating a requirements.txt so other people can easily set up their own virtual environment for the project.

I was wondering though, when other developers want to contribute to the project, but want to use virtualenv instead of Anaconda, can they do that?

I tried the following:

• I set up an empty project in an Anaconda environment and installed the aiohttp module. Then conda list --export > requirements.txt generates the following:

  # This file may be used to create an environment using:
  # $ conda create --name <env> --file <this file>
  # platform: win-64
  aiohttp=2.3.9=py36_0
  async-timeout=2.0.0=py36hc3e01a3_0
  certifi=2018.1.18=py36_0
  chardet=3.0.4=py36h420ce6e_1
  multidict=3.3.2=py36h72bac45_0
  pip=9.0.1=py36h226ae91_4
  python=3.6.4=h6538335_1
  setuptools=38.4.0=py36_0
  vc=14=h0510ff6_3
  vs2015_runtime=14.0.25123=3
  wheel=0.30.0=py36h6c3ec14_1
  wincertstore=0.2=py36h7fe50ca_0
  yarl=0.14.2=py36h27d1bf2_0
  

• I set up an empty project in a virtualenv environment and installed the aiohttp module there too. pip freeze > requirements.txt then generates:

  aiohttp==3.0.1
  async-timeout==2.0.0
  attrs==17.4.0
  chardet==3.0.4
  idna==2.6
  idna-ssl==1.0.0
  multidict==4.1.0
  yarl==1.1.0
  

So apparently both outputs are different, and my theory is: once I generate my requirements.txt with conda on my project, other developers can't choose virtualenv instead - at least not if they're not prepared to install a long list requirements by hand (it will be more than just the aiohttp module of course).

A first sight, importing the conda-generated requirements.txt in a project on virtualenv (pip install -r requirements-conda.txt) throws this error:

Invalid requirement: 'aiohttp=2.3.9=py36_0'
= is not a valid operator. Did you mean == ?

Am I right when I think that if developers would like to do this, they would need to programmatically change the package list to the format that virtualenv understands, or they would have to import all packages manually? Meaning that I impose them to choose conda as virtual environment as well if they want to save themselves some extra work?

解决方案

I'm setting up a python project, using an Anaconda virtual environment. I was wondering though, when other developers want to contribute to the project, but want to use virtualenv instead of Anaconda, can they do that?

Yes - in fact this is how many of my projects are structured. To accomplish what you're looking for, here is a simple directory that we'll use as reference:

.
├── README.md
├── app
│   ├── __init__.py
│   ├── static
│   ├── templates
├── migrations
├── app.py
├── environment.yml
├── requirements.txt

In the project directory above, we have both environment.yml (for Conda users) and requirements.txt (for pip).

environment.yml

So apparently both outputs are different, and my theory is: once I generate my requirements.txt with conda on my project, other developers can't choose virtualenv instead - at least not if they're not prepared to install a long list requirements by hand (it will be more than just the aiohttp module of course).

To overcome this, we are using two different environment files, each in their own distinct format allowing for other contributors to pick the one they prefer. If Adam uses Conda to manage his environments, then all he need to do create his Conda from the environment.yml file:

conda env create -f environment.yml

The first line of the yml file sets the new environment's name. This is how we create the Conda-flavored environment file. Activate your environment (source activate or conda activate) then:

conda env export > environment.yml

In fact, because the environment file created by the conda env export command handles both the environment's pip packages and conda packages, we don't even need to have two distinct processes to create this file. conda env export will export all packages within your environment regardless of the channel they're installed from. It will have a record of this in environment.yml as well:

name: awesomeflask
channels:
- anaconda
- conda-forge
- defaults
dependencies:
- appnope=0.1.0=py36hf537a9a_0
- backcall=0.1.0=py36_0
- cffi=1.11.5=py36h6174b99_1
- decorator=4.3.0=py36_0
- ...

requirements.txt

Am I right when I think that if developers would like to do this, they would need to programmatically change the package list to the format that virtualenv understands, or they would have to import all packages manually? Meaning that I impose them to choose conda as virtual environment as well if they want to save themselves some extra work?

The recommended (and conventional) way to _change to the format that pip understands is through requirements.txt. Activate your environment (source activate or conda activate) then:

pip freeze > requirements.txt

Say Eve, one of the project contributor want to create an identical virtual environment from requirements.txt, she can either:

# using pip
pip install -r requirements.txt

# using Conda
conda create --name <env_name> --file requirements.txt

A full discussion is beyond the scope of this answer, but similar questions are worth a read.

An example of requirements.txt:

alembic==0.9.9
altair==2.2.2
appnope==0.1.0
arrow==0.12.1
asn1crypto==0.24.0
astroid==2.0.2
backcall==0.1.0
...

Tips: always create requirements.txt

In general, even on a project where all members are Conda users, I still recommend creating both the environment.yml (for the contributors) as well as the requirements.txt environment file. I also recommend having both these environment files tracked by version control early on (ideally from the beginning). This has many benefits, among them being the fact that it simplifies your debugging process and your deployment process later on.

A specific example that spring to mind is that of Azure App Service. Say you have a Django / Flask app, and want to deploy the app to a Linux server using Azure App Service with git deployment enabled:

az group create --name myResourceGroup --location "Southeast Asia"
az webapp create --resource-group myResourceGroup --plan myServicePlan

The service will look for two files, one being application.py and another being requirements.txt. You absolutely need both of these file (even if they're blank files) for the automation to work. This varies by cloud infrastructure / providers of course, but I find that having requirements.txt in our project generally saves us a lot of trouble down the road and worth the initial set-up overhead.

If your code is on GitHub, having requirements.txt also give you extra peace of mind by having its vulnerability detection pick up on any issue before alerting you / repo owner. That's a lot of great value for free, on the merit of having this extra dependency file (small price to pay).

This is as easy as making sure that every time a new dependency is installed, we run both the conda env export and pip freeze > requirements.txt command.

这篇关于使用 conda 生成的 requirements.txt 设置 virtualenv的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！