`_, and find the latest Linux installer.
-- Right click the installer, and select **"Copy Link Address"**
-- Head back to your WSL terminal, and type "wget " and then right click next to it. This should paste the link you copied, which should produce something like::
-
- wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
-
-- You got it! Not only did you get it, you made it look **easy.** Now just hit enter.
-- At this point, Conda will start installing. Type "yes" and hit Enter for all the various prompts that follow (Accepting the Terms and Conditions, Running Conda Init, etc)
-- Once this is done, close and restart your WSL terminal.
-- Once restarted, verify that conda is working using the following command::
-
- conda env list
-
-Wait wait wait wait just a second.
-Do you realize what just happened?
-
-You've just successfully installed Anaconda!! Hooray!
-Trust me, your life is about to become a LOT easier.
-
-
-- Let's now tap into your newfound powers with Anaconda and create a new virtual environment called "syft_env" by running the following in your WSL shell::
-
- conda create -n syft_env python=3.9 --y
-
-- Let's verify that we created our "syft_env" successfully with the following command (Deja Vu, anyone?)::
-
- conda env list
-
-- You should see two environments in the output. Hooray! Now let's activate the syft virtual env, and let the fun *really* begin::
-
- conda activate syft_env
-
-- Now let's use it to conveniently install a few packages::
-
- sudo apt install python3-pip
- pip3 install pandas matplotlib numpy
- pip3 install jupyterlab
-
-- If the last command fails, try the following instead::
-
- conda install -c conda-forge jupyterlab
-
-
-Step 5: Become the Docker Doctor
-================================
-
-The last tool needed to complete your arsenal is called Docker.
-You can install it by following the instructions `here `_.
-
-Note: The windows user account that launches wsl 2 has to be added to the local group "docker-users". On Windows 10 Home, run netplwiz to add the Windows user to the group "docker-users".
-
-Once you have it running, you just have to ensure the following:
-- You've allocated a sufficient amount of RAM (we recommend atleast 8GB, but you can get by with less)
-- You're using the WSL2 backend
-
-Congratulations, you have reached the end of your journey. Now it is time for your **ultimate test!** Deploying a domain node.
-
-Note that your ultimate test is **optional**- you can do this part later.
-
-
-Step 6: Install Hagrid and PySyft
-=================================
-
-- With the power of WSL and Anaconda, installing our software is as easy as::
-
- pip3 install syft
- pip3 install hagrid
-
-
-Optional: Deploy a Domain Node!
-===============================
-
-Everything we've done so far has been to make this next part as easy as possible. This is the moment we've all been waiting for.
-
-To launch a domain node called "test_domain", ensure your Virtual Environment ("syft_env" in the steps above) is active, that Docker Desktop is running, and run the command below on your WSL terminal::
-
- hagrid launch test_domain
-
-Note: If you get the error message "test_domain is not valid for node_type please use one of the following options: ['domain', 'network']" then rerun the command by changing test_domain to domain.
-
-You should see the containers begin to appear on Docker!
-
-**CONGRATULATIONS!!!**
-
-You have reached the promise land. You're ready to begin remote data science.
-It was a pleasure walking you through the installation process. Now be sure to use your newfound powers and abilities for good!
diff --git a/notebooks/tutorials/hello-syft/01-hello-syft.ipynb b/notebooks/tutorials/hello-syft/01-hello-syft.ipynb
index 8a7f6a674d2..12f01679e3c 100644
--- a/notebooks/tutorials/hello-syft/01-hello-syft.ipynb
+++ b/notebooks/tutorials/hello-syft/01-hello-syft.ipynb
@@ -83,7 +83,7 @@
"source": [
"## Launch a dummy server \n",
"\n",
- "In this tutorial, for the sake of demonstration, we will be using in-memory workers as dummy servers. For details of deploying a server on your own using `syft` and `hagrid`, please refer to the `quickstart` tutorials."
+ "In this tutorial, for the sake of demonstration, we will be using in-memory workers as dummy servers. For details of deploying a server on your own using `syft`."
]
},
{
diff --git a/packages/grid/frontend/src/lib/components/Datasets/DatasetModalNew.svelte b/packages/grid/frontend/src/lib/components/Datasets/DatasetModalNew.svelte
index 66587a5fd63..3b0cb81318a 100644
--- a/packages/grid/frontend/src/lib/components/Datasets/DatasetModalNew.svelte
+++ b/packages/grid/frontend/src/lib/components/Datasets/DatasetModalNew.svelte
@@ -43,10 +43,10 @@
>
2
- Install HAGrid by running the code below in your Jupyter Notebook
+
-
pip install -U hagrid
+
@@ -57,12 +57,10 @@
3
- Once HAGrid is installed open the "Upload Dataset" quickstart tutorial notebook by
- running the code below in your Jupyter Notebook.
From 7d2a46a5dd71aa8e96eeddec68d1ea09c5c56fd0 Mon Sep 17 00:00:00 2001
From: rasswanth-s <43314053+rasswanth-s@users.noreply.github.com>
Date: Thu, 30 May 2024 10:34:00 +0530
Subject: [PATCH 2/2] docs page update
---
.github/workflows/cd-docs.yml | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/.github/workflows/cd-docs.yml b/.github/workflows/cd-docs.yml
index bf6355d4140..ff042e74017 100644
--- a/.github/workflows/cd-docs.yml
+++ b/.github/workflows/cd-docs.yml
@@ -5,12 +5,12 @@ on:
none:
description: "Deploy Syft Documentation"
required: false
- pull_request:
- branches: [dev]
- paths: [docs/]
- push:
- branches: [dev]
- paths: [docs/]
+ # pull_request:
+ # branches: [dev]
+ # paths: [docs/]
+ # push:
+ # branches: [dev]
+ # paths: [docs/]
jobs:
cd-docs: