75 lines
3.5 KiB
Markdown
75 lines
3.5 KiB
Markdown
# Services
|
|
|
|
|
|
|
|
|
|
# Playground
|
|
|
|
Within the sandbox, the different disciplines inside the IKID project can provide tasks to be worked on by the respective student groups. Both text-based tasks and programmatic tasks can be provided and processed. For example, Markdown files can be created for editing textual tasks. These files can be converted from the source form (unformatted) to the target form (formatted) using a simple syntax.
|
|
Currently, it is planned for the technical lectures that the students get first in touch with the programming language Python. Therefore, the Sandbox platform was created, in which experiments with Python can be carried out. But if needed, it is possible to add more supported languages in the future.
|
|
|
|
[Sandbox](https://sandbox.iuk.hdm-stuttgart.de/)
|
|
(only accessible from the HdM-Network)
|
|
|
|
|
|
1. **Sign in**, use your **HdM Credentials**
|
|
2. Select the image you want to start (two options)
|
|
1. **Datascience environment**
|
|
2. **GPU environment** (choose only if you realy need the graphic card, otherwise you steal resources from those who need them)
|
|
3. Create or upload a .ipynb file to start with
|
|
1. . **create a empty .ipynb file:**
|
|
|
|
2. **upload a existing .ipynb file:**
|
|
|
|
4. **open** the file from the filebrowser & start working!
|
|
.
|
|
5. **After you finished your work dont forget to shutdown your server!** Therfore you should shutdown your server to release server resources. **Select File, Hub Control Panel**
|
|
|
|
7. Select **Stop Server**
|
|
|
|
1. Select the arrow in the upper right corner to **Logout**
|
|
|
|
|
|
|
|
|
|
# Training
|
|
Coming Soon ...
|
|
|
|
|
|
# Storage
|
|
|
|
In the following section we describe how to store data on the Sandbox. There are three diffrent ways to do so: Inside the Sandbox, Object Storage, Git LFS.
|
|
|
|
## Inside the Sandbox
|
|
To store the data inside the Sandbox, you just have to drag & drop or click on the upload button to save the file to your running instance. You can also create folders and new Notebooks. The only limitation is, that each user has 1GB of storage.
|
|
|
|
|
|
|
|
## Object storage
|
|
To use the Object storage, you can upload a file via REST-Interface and access it by the key you get provided in the response. If you want to upload your file:
|
|
|
|
**Upload Example**
|
|
```python
|
|
import requests
|
|
|
|
url = "https://share.storage.sandbox.iuk.hdm-stuttgart.de/upload"
|
|
filename = "ds_salaries.csv"
|
|
files = {'fileUpload': (filename, open(filename, 'rb'),'text/csv')}
|
|
r = requests.post(url, files=files)
|
|
```
|
|
|
|
**Usage Example**
|
|
```python
|
|
import pandas as pd
|
|
|
|
url = "https://storage.sandbox.iuk.hdm-stuttgart.de/upload/ec6c1c9c-ea9b-47ff-97cf-f92d870e8fb9/ds_salaries.csv"
|
|
df = pd.read_csv(url)
|
|
```
|
|
|
|
## Git LFS
|
|
The following solution we highly recomment only for users which are familiar with git command line tools! Git Large File Storage (LFS). An open source Git extension for versioning large files. Git LFS replaces large files (audio, sample, datasets, videos) by a text pointer inside git. The files get stored on our gitea Server.
|
|
For further information visit [Git LFS](https://git-lfs.com/).
|
|
|
|
|
|
## Tmp Binary
|
|
headless binary curl |