From 2488ac9538f78bae1aad0370bbec51e553442c90 Mon Sep 17 00:00:00 2001 From: nic <139033898+dicnunz@users.noreply.github.com> Date: Wed, 20 May 2026 16:00:58 -0400 Subject: [PATCH 1/2] Fix broken docs links --- src/content/docs/client-apis/swift.mdx | 2 +- src/content/docs/get-started/graph-algorithms.md | 8 +++----- src/content/docs/installation.mdx | 10 +++++----- src/content/docs/visualization/lbug-explorer/index.mdx | 2 +- 4 files changed, 10 insertions(+), 12 deletions(-) diff --git a/src/content/docs/client-apis/swift.mdx b/src/content/docs/client-apis/swift.mdx index 93fb794..ec747c1 100644 --- a/src/content/docs/client-apis/swift.mdx +++ b/src/content/docs/client-apis/swift.mdx @@ -9,5 +9,5 @@ See the following link for the full documentation of the `swift-ladybug` package diff --git a/src/content/docs/get-started/graph-algorithms.md b/src/content/docs/get-started/graph-algorithms.md index af78a4d..b10addc 100644 --- a/src/content/docs/get-started/graph-algorithms.md +++ b/src/content/docs/get-started/graph-algorithms.md @@ -13,9 +13,8 @@ in Python to run almost any graph algorithm on a Ladybug subgraph. ## Prepare the dataset -A dataset of Nobel laureates and their mentorship network is provided -[here](https://raw.githubusercontent.com/ladybugdb/ladybug/tutorials/main/src/network_analysis/data.zip). -Download the dataset to your local directory and unzip it. +This tutorial uses a dataset of Nobel laureates and their mentorship network. +Create a local `data` directory containing `scholars.csv` and `mentorships.csv` before running the examples below. The nodes in the dataset are scholars who won Nobel prizes, as well as other scholars who didn't win prizes but were involved in mentoring them. The edges represent @@ -408,5 +407,4 @@ For performance and scalability, it's recommended to use Ladybug's native `algo` is available. If not, you can always fall back to using NetworkX, which has a far more extensive suite of graph algorithms. -To reproduce the analysis shown in this tutorial, see the code -[here](https://github.com/LadybugDB/tutorials/tree/main/src/network_analysis). +To reproduce the analysis shown in this tutorial, run the code snippets above after placing the CSV files in `./data`. diff --git a/src/content/docs/installation.mdx b/src/content/docs/installation.mdx index ffde324..d564cd4 100644 --- a/src/content/docs/installation.mdx +++ b/src/content/docs/installation.mdx @@ -20,8 +20,8 @@ tar xzf lbug_cli-*.tar.gz`, macos: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/v${version}/lbug_cli-osx-universal.tar.gz tar xzf lbug_cli-*.tar.gz ./lbug`, - win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip`, - winUrl: `https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip`, + win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip`, + winUrl: `https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip`, }, java: ` com.ladybugdb @@ -41,7 +41,7 @@ tar xzf liblbug-*.tar.gz`, tar xzf liblbug-*.tar.gz`, win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/v${version}/liblbug-windows-x86_64.zip` }, - go: `go get https://github.com/LadybugDB/go-ladybug@v0.13.1`, + go: `go get github.com/LadybugDB/go-ladybug`, swift: `dependencies: [ .package(url: "https://github.com/LadybugDB/swift-ladybug/", branch: "${version}"), ],` @@ -100,10 +100,10 @@ Alternatively, you can download the Ladybug CLI directly. Use a tool like `curl` to download the latest version of the Ladybug CLI to your local machine. Alternatively, -simply open [this URL](https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip) in your browser. +simply open [this URL](https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip) in your browser. ```bash -curl -L -O https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip +curl -L -O https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip ``` Right-click on the `lbug_cli-xxx.zip` file and click on **Extract All**. This will create a directory diff --git a/src/content/docs/visualization/lbug-explorer/index.mdx b/src/content/docs/visualization/lbug-explorer/index.mdx index 9ab0551..884ec67 100644 --- a/src/content/docs/visualization/lbug-explorer/index.mdx +++ b/src/content/docs/visualization/lbug-explorer/index.mdx @@ -20,7 +20,7 @@ Ladybug Explorer is a web application that is launched from a deployed Docker im Please refer to the [Docker documentation](https://docs.docker.com/get-docker/) for details on how to install and use Docker. Below we show two different ways to launch Ladybug Explorer. Each of these options make -Ladybug Explorer accessible on [http://localhost:8000](http://localhost:8000). If the launching is successful, you should see the logs similar to the following in your shell: +Ladybug Explorer accessible at `http://localhost:8000`. If the launching is successful, you should see the logs similar to the following in your shell: ```bash Access mode: READ_WRITE From c87cc4acaae4a56a10783cbb4b9f30cb5efbfe75 Mon Sep 17 00:00:00 2001 From: nic <139033898+dicnunz@users.noreply.github.com> Date: Wed, 20 May 2026 16:54:52 -0400 Subject: [PATCH 2/2] Address docs link review --- src/content/docs/get-started/graph-algorithms.md | 5 +++-- src/content/docs/visualization/lbug-explorer/index.mdx | 2 +- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/src/content/docs/get-started/graph-algorithms.md b/src/content/docs/get-started/graph-algorithms.md index b10addc..d329438 100644 --- a/src/content/docs/get-started/graph-algorithms.md +++ b/src/content/docs/get-started/graph-algorithms.md @@ -13,8 +13,9 @@ in Python to run almost any graph algorithm on a Ladybug subgraph. ## Prepare the dataset -This tutorial uses a dataset of Nobel laureates and their mentorship network. -Create a local `data` directory containing `scholars.csv` and `mentorships.csv` before running the examples below. +A dataset of Nobel laureates and their mentorship network is provided +[here](https://huggingface.co/datasets/ladybugdb/python-tutorial/blob/main/nobel-mentorship.zip). +Download the dataset to your local directory and unzip it. The nodes in the dataset are scholars who won Nobel prizes, as well as other scholars who didn't win prizes but were involved in mentoring them. The edges represent diff --git a/src/content/docs/visualization/lbug-explorer/index.mdx b/src/content/docs/visualization/lbug-explorer/index.mdx index 884ec67..9ab0551 100644 --- a/src/content/docs/visualization/lbug-explorer/index.mdx +++ b/src/content/docs/visualization/lbug-explorer/index.mdx @@ -20,7 +20,7 @@ Ladybug Explorer is a web application that is launched from a deployed Docker im Please refer to the [Docker documentation](https://docs.docker.com/get-docker/) for details on how to install and use Docker. Below we show two different ways to launch Ladybug Explorer. Each of these options make -Ladybug Explorer accessible at `http://localhost:8000`. If the launching is successful, you should see the logs similar to the following in your shell: +Ladybug Explorer accessible on [http://localhost:8000](http://localhost:8000). If the launching is successful, you should see the logs similar to the following in your shell: ```bash Access mode: READ_WRITE