add streamlit integration

Makefile

@@ -1,11 +1,11 @@
 run:
-	pipenv run python app.py
+	pipenv run streamlit run app.py
 
 format:
-	pipenv run black py_code_analyzer && \
-	pipenv run isort py_code_analyzer && \
-	pipenv run flake8 py_code_analyzer && \
-	pipenv run mypy py_code_analyzer
+	pipenv run black py_code_analyzer app.py && \
+	pipenv run isort py_code_analyzer app.py && \
+	pipenv run flake8 py_code_analyzer app.py && \
+	pipenv run mypy py_code_analyzer app.py
 
 test:
 	pipenv run pytest --cov

README.md

@@ -33,7 +33,7 @@ input to one GitHub public repo's URL(input)
   - [x] Use `ast` to parse imports among given python files
   - [x] Generate a basic `networkx` graph given python imports
   - [x] Visualize a basic `networkx` graph using `pyvis`
-- [ ] Build a `streamlit` app
+- [x] Build a `streamlit` app
 ## References
 
 - [How to set up a perfect Python project](https://sourcery.ai/blog/python-best-practices/)

app.py

@@ -1,7 +1,30 @@
+import streamlit as st
+import streamlit.components.v1 as components
+
 from py_code_analyzer import CodeFetcher, CodeImportsAnalyzer, ImportsGraphVisualizer
 
-python_files = CodeFetcher().get_python_files(
-    "cyyeh", "py-code-analyzer", "py_code_analyzer"
+TITLE = "Python Code Analyzer"
+st.set_page_config(page_title=TITLE, layout="wide")
+st.title(TITLE)
+st.markdown(
+    "The main purpose of the app is to allow Python developers navigate Python code base much "
+    + "easier by showing dependencies among files included in the directory with better visualization."
+)
+st.markdown(
+    "**Checkout the source code [here](https://github.com/cyyeh/py-code-analyzer)**"
+)
+
+owner = st.text_input("Enter GitHub username", value="cyyeh")
+repo = st.text_input("Enter GitHib repo name", value="py-code-analyzer")
+path = st.text_input(
+    "Enter target directory path, if the value is empty, then the target directory will be the root directory",
+    value="py_code_analyzer",
 )
+
+python_files = CodeFetcher().get_python_files(owner, repo, path)
 imports_graph = CodeImportsAnalyzer(python_files).analyze().generate_imports_graph()
 ImportsGraphVisualizer().visualize(imports_graph)
+
+imports_graph_html = open("nx.html", "r", encoding="utf-8")
+imports_graph_html_text = imports_graph_html.read()
+components.html(imports_graph_html_text, height=800)