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adding css rule for logo and fixing some ref links
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yuvipanda
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docs/_static/custom.css
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docs/_static/custom.css
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@@ -0,0 +1,3 @@
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div.sphinxsidebarwrapper h1.logo {
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font-size: 2.3rem;
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}
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@@ -1,4 +1,4 @@
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.. _howto/resource-estimation:
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.. _howto/admin/resource-estimation:
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===================================
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Estimate Memory / CPU / Disk needed
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@@ -40,7 +40,7 @@ Maximum memory allowed per user
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Depending on what kinda work your users are doing, they will use different amounts
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of memory. The easiest way to determine this is to run through a typical user
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workflow yourself, and measure how much memory is used. You can use :ref:`howto/nbresuse`
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workflow yourself, and measure how much memory is used. You can use :ref:`howto/admin/nbresuse`
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to determine how much memory your user is using.
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A good rule of thumb is to take the maximum amount of memory you used during
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@@ -6,14 +6,14 @@ Adding data to the JupyterHub
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This section covers how to add data to your JupyterHub either from the internet
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or from your own machine. To learn how to **share data** that is already
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on your JupyterHub, see :ref:`_howto/content/share-data`.
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on your JupyterHub, see :ref:`howto/content/share-data`.
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.. note::
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When you add data using the methods on this page, you will **only add it
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to your user directory**. This is not a place that is accessible to others.
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For information on sharing this data with users on the JupyterHub, see
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:ref:`_howto/content/share-data`.
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:ref:`howto/content/share-data`.
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Adding data from your local machine
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===================================
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@@ -37,7 +37,7 @@ interface. To do so, follow these steps:
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be on your JupyterHub, your home user's home directory.
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To learn how to **share** this data with new users on the JupyterHub,
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see :ref:`_howto/content/share-data`.
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see :ref:`howto/content/share-data`.
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Downloading data from the command line
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======================================
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@@ -90,6 +90,6 @@ time. You can download it from your browser `at this link <https://swcarpentry.g
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#. Confirm that your data was unzipped. It could be in a folder called ``data/``.
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To learn how to **share** this data with new users on the JupyterHub,
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see :ref:`_howto/content/share-data`.
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see :ref:`howto/content/share-data`.
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.. TODO: Downloading data with the "download" module in Python? https://github.com/choldgraf/download
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@@ -16,7 +16,7 @@ contained in the link's target repository is downloaded to the user's home
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directory. Note that a copy of the dataset will be made for each user.
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For information on creating and sharing ``nbgitpuller`` links, see
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:ref:`tutorials/nbgitpuller`.
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:ref:`howto/content/nbgitpuller`.
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Option 2: Create a read-only shared folder for data
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===================================================
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@@ -6,7 +6,7 @@ Install conda, pip or apt packages
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:abbr:`TLJH (The Littlest JupyterHub)` starts all users in the same `conda <https://conda.io/docs/>`_
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environment. Packages / libraries installed in this environment are available
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to all users on the JupyterHub. Users with :ref:`admin rights <howto/admin-users>` can install packages
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to all users on the JupyterHub. Users with :ref:`admin rights <howto/admin/admin-users>` can install packages
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easily.
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.. _howto/envt/user_environment_pip:
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@@ -43,7 +43,7 @@ Let's create the server on which we can run JupyterHub.
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(4GB RAM, 2CPUs, 20 USD / month) is not a bad start. You can resize your server
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later if you need.
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Check out our guide on How To :ref:`howto/resource-estimation` to help pick
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Check out our guide on How To :ref:`howto/admin/resource-estimation` to help pick
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how much Memory, CPU & disk space your server needs.
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#. Scroll down to **Select additional options**, and select **User data**.
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@@ -83,7 +83,7 @@ Let's create the server on which we can run JupyterHub.
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.. image:: ../images/providers/google/machine-type-advanced.png
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:alt: Select a customized VM size
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Check out our guide on How To :ref:`howto/resource-estimation` to help pick
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Check out our guide on How To :ref:`howto/admin/resource-estimation` to help pick
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how much Memory / CPU your server needs.
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#. Under **Boot Disk**, click the **Change** button. This lets us change the
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@@ -109,7 +109,7 @@ Let's create the server on which we can run JupyterHub.
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to a hard drive. **SSD persistent disk** gives you a faster but more expensive
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disk, similar to an SSD.
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Check out our guide on How To :ref:`howto/resource-estimation` to help pick
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Check out our guide on How To :ref:`howto/admin/resource-estimation` to help pick
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how much Disk space your server needs.
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#. Click the **Select** button to dismiss the Boot disk popup and go back to the
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@@ -54,7 +54,7 @@ Let's create the server on which we can run JupyterHub.
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#. Give your server a descriptive **Instance Name**.
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#. Select an appropriate **Instance Size**. We suggest m1.medium or larger.
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Check out our guide on How To :ref:`howto/resource-estimation` to help pick
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Check out our guide on How To :ref:`howto/admin/resource-estimation` to help pick
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how much Memory, CPU & disk space your server needs.
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#. If you have multiple allocations, make sure you are 'charging' this server
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@@ -70,4 +70,4 @@ HTTPS
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=====
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Any internet-facing JupyterHub should use HTTPS to secure its traffic. For
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information on how to use HTTPS with your JupyterHub, see :ref:`_howto/admin/https`.
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information on how to use HTTPS with your JupyterHub, see :ref:`howto/admin/https`.
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