diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index b4b13be..044d99c 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -86,15 +86,16 @@ jobs:
         export PATH=/home/runner/.local/bin/:$PATH
 
         VERSION=$( echo $GITHUB_REF | /bin/sed 's#.*/v##' )
-        PLACEHOLDER='__version__'
+        SETUP_PLACEHOLDER='__version__ = "dev"'
         SETUP_FILE='setup.py'
+        DOCS_PLACEHOLDER='__version__'
         DOCS_CONF_FILE='docs/source/conf.py'
-
+        
         grep "$PLACEHOLDER" "$SETUP_FILE"
-        /bin/sed -i "s/$PLACEHOLDER/${VERSION}/" "$SETUP_FILE"
+        /bin/sed -i "s/$SETUP_PLACEHOLDER/__version__ = \"${VERSION}\"/g" "$SETUP_FILE"
 
         grep "$PLACEHOLDER" "$DOCS_CONF_FILE"
-        /bin/sed -i "s/$PLACEHOLDER/${VERSION}/" "$DOCS_CONF_FILE"
+        /bin/sed -i "s/$DOCS_PLACEHOLDER/${VERSION}/" "$DOCS_CONF_FILE"
       shell: bash
     - name: Install dependencies
       run: |
diff --git a/README.md b/README.md
index 05a7a7c..19d59e1 100644
--- a/README.md
+++ b/README.md
@@ -71,7 +71,7 @@ UrbanPy lets you download and visualize city boundaries extremely easy:
 ```python
 import urbanpy as up
 
-boundaries = up.download.nominatim_osm('Lima, Peru', expected_position=2)
+boundaries = up.download.nominatim_osm('Lima, Peru', expected_position=2, email="your@email.com")
 boundaries.plot()
 ```
 
diff --git a/setup.py b/setup.py
index 3aa7f51..b23295b 100644
--- a/setup.py
+++ b/setup.py
@@ -6,9 +6,12 @@
 with open("requirements.txt", "r") as f:
     install_requires = f.read().split("\n")[:-1]
 
+# Set a development version for source installs
+__version__ = "dev"
+
 setuptools.setup(
     name="urbanpy",
-    version="__version__",  # This will be replaced with the commit tag
+    version=__version__,  # This will be replaced with the commit tag
     author="Andres Regal, Claudio Ortega & Antonio Vazquez Brust",
     author_email="a.regalludowieg@up.edu.pe",
     description="A library to download, process and visualize high resolution urban data.",