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cannerflow-jupyter-contents-1.2.0
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مشاهده بیشترتوضیحات
Azure Contents Manager for Jupyter
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cannerflow-jupyter-contents-1.2.0 |
| نام | cannerflow-jupyter-contents |
| نسخه کتابخانه | 1.2.0 |
| نگهدارنده | ['Leo'] |
| ایمیل نگهدارنده | ['leo@canner.io'] |
| نویسنده | - |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/cannerflow-jupyter-contents/ |
| مجوز | Apache License, Version 2.0 |
# CannerFlow Jupyter Contents
An S3, GCS, Blob backed ContentsManager implementation for Jupyter. Based on [s3Contens](http://github.com/danielfrg/s3contents)
## Installation
```
$ pip install cannerflow-jupyter-contents
```
## Jupyter config
Edit `~/.jupyter/jupyter_notebook_config.py` based on the backend you want to
based on the examples below. Replace credentials as needed.
## AWS S3
```python
from s3contents import S3ContentsManager
c = get_config()
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.access_key_id = "{{ AWS Access Key ID / IAM Access Key ID }}"
c.S3ContentsManager.secret_access_key = "{{ AWS Secret Access Key / IAM Secret Access Key }}"
c.S3ContentsManager.session_token = "{{ AWS Session Token / IAM Session Token }}"
c.S3ContentsManager.bucket = "{{ S3 bucket name }}"
# Optional settings:
c.S3ContentsManager.prefix = "this/is/a/prefix/on/the/s3/bucket"
c.S3ContentsManager.sse = "AES256"
c.S3ContentsManager.signature_version = "s3v4"
c.S3ContentsManager.init_s3_hook = init_function # See AWS key refresh
```
Example for `play.minio.io:9000`:
```python
from s3contents import S3ContentsManager
c = get_config()
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.access_key_id = "Q3AM3UQ867SPQQA43P2F"
c.S3ContentsManager.secret_access_key = "zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG"
c.S3ContentsManager.endpoint_url = "http://play.minio.io:9000"
c.S3ContentsManager.bucket = "s3contents-demo"
c.S3ContentsManager.prefix = "notebooks/test"
```
### AWS EC2 role auth setup
It also possible to use IAM Role-based access to the S3 bucket from an Amazon EC2 instance.
To do that just leave `access_key_id` and `secret_access_key` set to their default values (`None`),
and ensure that the EC2 instance has an IAM role which provides sufficient permissions for the bucket and the operations necessary.
### AWS key refresh
The optional `init_s3_hook` configuration can be used to enable AWS key rotation (described [here](https://dev.to/li_chastina/auto-refresh-aws-tokens-using-iam-role-and-boto3-2cjf) and [here](https://www.owenrumney.co.uk/2019/01/15/implementing-refreshingawscredentials-python/)) as follows:
```python
from s3contents import S3ContentsManager
from botocore.credentials import RefreshableCredentials
from botocore.session import get_session
import botocore
import boto3
from configparser import ConfigParser
def refresh_external_credentials():
config = ConfigParser()
config.read('/home/jovyan/.aws/credentials')
return {
"access_key": config['default']['aws_access_key_id'],
"secret_key": config['default']['aws_secret_access_key'],
"token": config['default']['aws_session_token'],
"expiry_time": config['default']['aws_expiration']
}
session_credentials = RefreshableCredentials.create_from_metadata(
metadata = refresh_external_credentials(),
refresh_using = refresh_external_credentials,
method = 'custom-refreshing-key-file-reader'
)
def make_key_refresh_boto3(this_s3contents_instance):
refresh_session = get_session() # from botocore.session
refresh_session._credentials = session_credentials
my_s3_session = boto3.Session(botocore_session=refresh_session)
this_s3contents_instance.boto3_session = my_s3_session
# Tell Jupyter to use S3ContentsManager for all storage.
c.NotebookApp.contents_manager_class = S3ContentsManager
c.S3ContentsManager.init_s3_hook = make_key_refresh_boto3
```
## GCP Cloud Storage
```python
from s3contents import GCSContentsManager
c = get_config(
c.NotebookApp.contents_manager_class = GCSContentsManager
c.GCSContentsManager.project = "{{ your-project }}"
c.GCSContentsManager.token = "~/.config/gcloud/application_default_credentials.json"
c.GCSContentsManager.bucket = "{{ GCP bucket name }}"
```
Note that the file `~/.config/gcloud/application_default_credentials.json` assumes a posix system
when you did `gcloud init`
## Azure blob storage with SAS
import os
from s3contents import BlobContentsManager
from s3contents.blobmanager import auth_shared_access_signature
token = auth_shared_access_signature(
account_key=os.environ["AZURE_ACCOUNT_KEY"],
account_name=os.environ["AZURE_ACCOUNT_NAME"]
)
c.NotebookApp.contents_manager_class = BlobContentsManager
c.BlobContentsManager.credential=token
c.BlobContensManager.account_key=os.environ["AZURE_ACCOUNT_KEY"]
c.BlobContentsManager.container_name=os.environ["AZURE_CONTAINER_NAME"]
c.BlobContentsManager.account_name=os.environ["AZURE_ACCOUNT_NAME"]
## Access local files
To access local file as well as remote files in S3 you can use [hybridcontents](https://github.com/viaduct-ai/hybridcontents).
First install it:
```
pip install hybridcontents
```
Use a configuration similar to this:
```python
from s3contents import S3ContentsManager
from hybridcontents import HybridContentsManager
from IPython.html.services.contents.filemanager import FileContentsManager
c = get_config()
c.NotebookApp.contents_manager_class = HybridContentsManager
c.HybridContentsManager.manager_classes = {
# Associate the root directory with an S3ContentsManager.
# This manager will receive all requests that don"t fall under any of the
# other managers.
"": S3ContentsManager,
# Associate /directory with a FileContentsManager.
"local_directory": FileContentsManager,
}
c.HybridContentsManager.manager_kwargs = {
# Args for root S3ContentsManager.
"": {
"access_key_id": "{{ AWS Access Key ID / IAM Access Key ID }}",
"secret_access_key": "{{ AWS Secret Access Key / IAM Secret Access Key }}",
"bucket": "{{ S3 bucket name }}",
},
# Args for the FileContentsManager mapped to /directory
"local_directory": {
"root_dir": "/Users/danielfrg/Downloads",
},
}
```
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl cannerflow-jupyter-contents-1.2.0:
pip install cannerflow-jupyter-contents-1.2.0.whl
نصب پکیج tar.gz cannerflow-jupyter-contents-1.2.0:
pip install cannerflow-jupyter-contents-1.2.0.tar.gz