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updated README.md

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Tomasz Dłuski
2020-08-24 00:19:41 +02:00
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@@ -10,9 +10,8 @@ AWS S3 based [on this article ](https://dev.to/goodidea/how-to-fake-aws-locally-
1. Configure `.env` file for your choice 1. Configure `.env` file for your choice
2. Create mlflow bucket. You can do it either using AWS CLI or Python Api 2. Create mlflow bucket. You can do it either using AWS CLI or Python Api
<details><summary>**AWS CLI**</summary>
<summary>AWS CLI
<details>
1. [Install AWS cli](https://aws.amazon.com/cli/) **Yes, i know that you dont have an Amazon Web Services Subscription - dont worry! It wont be needed!** 1. [Install AWS cli](https://aws.amazon.com/cli/) **Yes, i know that you dont have an Amazon Web Services Subscription - dont worry! It wont be needed!**
2. Configure AWS CLI - enter the same credentials from the `.env` file 2. Configure AWS CLI - enter the same credentials from the `.env` file
@@ -28,11 +27,10 @@ aws configure
```shell ```shell
aws --endpoint-url=http://localhost:9000 s3 mb s3://mlflow aws --endpoint-url=http://localhost:9000 s3 mb s3://mlflow
``` ```
</details>
</summary>
<summary>Python API </details>
<details>
<details><summary>**Python API**</summary>
1. Install Minio 1. Install Minio
```shell ```shell
@@ -53,7 +51,6 @@ s3Client.make_bucket('mlflow')
``` ```
</details> </details>
</summary>
3. Open up http://localhost:5000/#/ for MlFlow, and http://localhost:9000/minio/mlflow/ for S3 bucket (you artifacts) with credentials from `.env` file 3. Open up http://localhost:5000/#/ for MlFlow, and http://localhost:9000/minio/mlflow/ for S3 bucket (you artifacts) with credentials from `.env` file