Azure / Azure/MachineLearningNotebooks
Dependency problems (docker/pywin32 and ruamel.yaml)
- 主要語言
- Jupyter Notebook
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- PR 合併指標
- 30 天內沒有已合併 PR
描述
Hello everyone! I'm having problems with Azure packages because apparently, they have some broken dependencies. I'm reporting the following problems:
* `docker`: Required by `azureml-core`, `docker` is pinned to a version lower than `6.0.0` . However, older versions of this library pin `pywin32 227`, and any version of `pywin32` below `300` breaks `default_azure_credential` when using it in `Windows`. This would automatically break `Azure CLI Login` (in my case this is happening). Also, version `6.0.0` fixes `pywin32` I think azure should just update it to `6.0.0` in order to fix the problem
* `ruamel.yaml`: The package `azureml-pipeline-core` depends on `ruamel.yaml` pinned on a version below `16`. This lib requires to compile some binaries in `C` while installing, and any version below `16` uses an installation method not supported by `pip` versions over `20.1`. To solve this, I had to downgrade `pip`, or install it using `poetry`, which is a package manager able to fix this bug
Considering all `AzureML SDK` packages were developed using modular packages, I really recommend using `Poetry` to manage dependencies, and `dependabot` (or something similar) to update automatically update deps. it would reduce installation time, and would prevent future conflicts.
I think `Azure` should fix these problems before fully migrating to `SDK v2` since there are some features still in beta.
Related links:
- [ruamel#1](https://stackoverflow.com/questions/49868091/python-error-when-installing-ruamel-yaml-package-with-pip)
- [ruamel#2](https://stackoverflow.com/questions/70136750/cant-install-azure-packages-with-pip-ruamel-yaml-error)
- [ruamel#3](https://stackoverflow.com/questions/71967150/problem-installing-azure-pipeline-due-to-ruamel-yaml)
貢獻指南
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研究方向
未指定目標檔案或測試。首先找出 azureml-core 和 azureml-pipeline-core 的相依性宣告,然後使用目前的 pip 在 Windows 上重現安裝;當已回報的 pywin32 和 ruamel.yaml 衝突不再阻礙所述的 Azure ML 工作流程時,即視為完成。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- azure, docker, python
- 領域
- devops, machine-learning
- Issue 類型
- 缺陷
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 活躍度
- 停滯
- 描述清晰度
- 基本清楚
- 新手友好度
- 25/100