docs(readme): add "Open in Codespaces" button

* feat-dev-container

* point to repo and remove extra stuff

* specify machine config

* point to branch

* point to main repo

.devcontainer/devcontainer.json

@@ -0,0 +1,24 @@
+// Adopting the default GitHub codespaces-jupyter template as starter
+// https://github.com/github/codespaces-jupyter
+
+{
+    "name" : "Sec Parser",
+    "image": "mcr.microsoft.com/devcontainers/universal:2",
+    "hostRequirements": {
+        "cpus": 4
+    },
+    "waitFor": "onCreateCommand",
+    "updateContentCommand": "python3 -m pip install -r .devcontainer/requirements.txt",
+    "postCreateCommand": "",
+    "customizations": {
+      "codespaces": {
+        "openFiles": ["./docs/source/notebooks/user_guide.ipynb"]
+      },
+      "vscode": {
+        "extensions": [
+          "ms-toolsai.jupyter",
+          "ms-python.python"
+        ]
+      }
+    }
+}

.devcontainer/requirements.txt

@@ -0,0 +1,3 @@
+ipywidgets==7.7.1
+sec-parser
+sec_downloader

README.md

@@ -105,6 +105,8 @@ This project, `sec-parser`, is an independent, open-source initiative and has no
 
 This guide will walk you through the process of installing the `sec-parser` package and using it to extract the "Segment Operating Performance" section as a semantic tree from the latest Apple 10-Q filing.
 
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/alphanome-ai/sec-parser?devcontainer_path=.devcontainer/devcontainer.json)
+
 ## Installation
 
 First, install the `sec-parser` package using pip: