Merge pull request #10 from ReagentX/feat/cs/pypi-deploy

Feat/cs/pypi deploy

.github/workflows/pythonpublish.yml

@@ -0,0 +1,26 @@
+name: Upload Python Package
+
+on:
+  release:
+    types: [created]
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v1
+      with:
+        python-version: '3.x'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+    - name: Build and publish
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

.gitignore

@@ -1,7 +1,15 @@
-
-.vscode/*
-venv/*
+# Generated files
 *.pyc
-cache.sqlite
 puepleair_api.egg-info/*
 purpleair_api.egg-info/*
+Purple_Air_API.egg-info/*
+purpleair.egg-info/*
+build/*
+dist/*
+
+# Requests cache
+cache.sqlite
+
+# Dev env
+venv/*
+.vscode/*

README.md

@@ -1,18 +1,31 @@
-# purple_air_api
+# Purple Air API
 
-A Python 3.7 API Class to turn data from the PurpleAir/ThingSpeak API into a Pandas Dataframe with several utility methods.
+A Python 3.x API Class to turn data from the PurpleAir/ThingSpeak API into a Pandas DataFrame with several utility methods.
 
 ![](maps/sensor_map.png)
 
 ## Installation
 
-* Clone this repo
-* `cd` to the folder
-* Create a virtual environment ( `python -m venv venv` )
-* Activate the virtual environment ( `source venv/bin/activate` )
-* `python setup.py develop`
-* `pip install -r requirements/common.txt`
-  * Install development requirements with `pip install -r requirements/dev.txt`
+* To use
+  * Create a virtual environment
+    * `python -m venv venv`
+  * Activate the virtual environment
+    * `source venv/bin/activate`
+  * Install this package
+    * `pip install purpleair`
+* To hack
+  * Clone this repo
+  * `cd` to the folder
+  * Create a virtual environment
+    * `python -m venv venv`
+  * Activate the virtual environment
+    * `source venv/bin/activate`
+  * Install as dependency in the virtual environment
+    * `python setup.py develop`
+  * Install third party dependencies
+    * Required to run: `pip install -r requirements/common.txt`
+    * Install development requirements with `pip install -r requirements/dev.txt`
+    * Install example file requirements with `pip install -r requirements/examples.txt`
 
 ## Example code
 
@@ -37,9 +50,12 @@ print(s)  # Sensor 2891 at 10834, Canyon Road, Omaha, Douglas County, Nebraska,
 ```python
 from purpleair import purpleair
 df = p.to_dataframe('all')  # Other options include 'outdoor' and 'useful'
+```
+
+Result:
 
-# Will print
-            age  downgraded  flagged  hidden  humidity           last_seen  ...                  name   parent  pm_2.5 pressure     temp_c  temp_f
+```log
+            age  downgraded  flagged  hidden  humidity         last_seen  ...                  name   parent  pm_2.5 pressure     temp_c  temp_f
 id                                                                        ...
 24115   36026       False    False   False      0.15 2019-01-09 20:33:05  ...   2nd South 12th East      NaN    0.15   869.14  31.666667    89.0
 16791       0       False    False   False      0.60 2019-02-03 20:59:26  ...                DW0435      NaN    1.96  1009.82  30.000000    86.0
@@ -54,8 +70,11 @@ id                                                                        ...
 from purpleair import sensor
 se = sensor.Sensor('2891', parse_location=True)
 print(se.get_historical(weeks_to_get=1, sensor_channel='a').head())
+```
+
+Result:
 
-# Will print
+```log
                         created_at  PM1 CF=ATM ug/m3  PM25 CF=ATM ug/m3  PM10 CF=ATM ug/m3  Free HEAP memory  ADC0 Voltage  Sensor Firmware  Unused  PM25 CF=1 ug/m3
 entry_id
 536245   2019-01-27 00:00:35+00:00             12.87              17.70              18.39           30032.0          0.02           973.99     NaN            17.70

scripts/plot_city.py

@@ -2,8 +2,9 @@
 Install requirements with `pip install -r requirements/common.txt`
 """
 
-from mpl_toolkits.basemap import Basemap
 import matplotlib.pyplot as plt
+from mpl_toolkits.basemap import Basemap
+
 from purpleair import purpleair
 
 # Get the purpleair data
@@ -13,7 +14,8 @@
 # Store the lat and lon coords to plot
 lat = df['lat'].values
 lon = df['lon'].values
-colors = df[var_to_viz].values  # Variable on which to generate the color gradient
+# Variable on which to generate the color gradient
+colors = df[var_to_viz].values
 
 # Coorinates for Los Angeles, CA
 m = Basemap(llcrnrlon=-118.5,
@@ -23,7 +25,7 @@
             lat_0=34.,
             lon_0=-118.,
             projection='lcc',
-            resolution = 'i',
+            resolution='i',
             epsg=3498  # Lookup via https://epsg.io
             )
 

scripts/plot_map.py

@@ -2,27 +2,26 @@
 Install requirements with `pip install -r requirements/common.txt`
 """
 
-#%%
-from mpl_toolkits.basemap import Basemap
-import numpy as np
-import matplotlib.pyplot as plt
-from purpleair import purpleair
 import datetime
 
+import matplotlib.pyplot as plt
+import numpy as np
+from mpl_toolkits.basemap import Basemap
+
+from purpleair import purpleair
 
-#%%
 # Get the purpleair data
 p = purpleair.PurpleAir()
 df = p.to_dataframe('all')
 var_to_viz = 'temp_c'  # The dict item that we want to visualize
 # Store the lat and lon coords to plot
 lat = df['lat'].values
 lon = df['lon'].values
-colors = df[var_to_viz].values  # Variable on which to generate the color gradient
+# Variable on which to generate the color gradient
+colors = df[var_to_viz].values
 print(min(colors), max(colors))
 
 
-#%%
 margin = 0  # buffer to add to the range
 lat_min = min(lat) - margin
 lat_max = max(lat) + margin
@@ -36,24 +35,24 @@
             lat_0=(lat_max - lat_min)/2,
             lon_0=(lon_max-lon_min)/2,
             projection='merc',
-            resolution = 'h',
+            resolution='h',
             area_thresh=10000.,
             )
 m.drawcoastlines()
 m.drawcountries()
 m.drawstates()
 
 
-#%%
 # Colors
 water = '#46bcec'
 land = '#ffffff'
 m.drawmapboundary(fill_color=water)
-m.fillcontinents(color = land, lake_color=water)
+m.fillcontinents(color=land, lake_color=water)
 # convert lat and lon to map projection coordinates
 lons, lats = m(lon, lat)
 # plot points as red dots
 m.scatter(lons, lats, marker='o', c=colors, cmap='plasma', zorder=5, s=2)
 plt.colorbar().set_label(f'{var_to_viz}', rotation=90)
-plt.title(f'Global {var_to_viz} at {datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}')
+plt.title(
+    f'Global {var_to_viz} at {datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}')
 plt.savefig('maps/sensor_map.png', dpi=300)

setup.py

@@ -1,11 +1,28 @@
-from setuptools import setup
+from setuptools import setup, find_packages
 
+with open("README.md", "r") as fh:
+    LONG_DESCRIPTION = fh.read()
 
 setup(
-    name='purpleair_api',
-    version='1.0',
-    description='A Python 3.7 PurpleAir API Class.',
+    name='purpleair',
+    version='1.0.1',
+    description='Python API Client to get and transform PurpleAir data.',
+    long_description=LONG_DESCRIPTION,
+    long_description_content_type="text/markdown",
     author='Christopher Sardegna',
     author_email='[email protected]',
-    scripts=['scripts/run.py']
+    url='https://github.com/ReagentX/purple_air_api/',
+    packages=find_packages(),
+    install_requires=['requests', 'requests_cache', 'thingspeak', 'geopy', 'pandas'],
+    python_requires='>=3.6',
+    classifiers=[
+        'Development Status :: 5 - Production/Stable',
+        'License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)',
+        'Natural Language :: English',
+        'Operating System :: OS Independent',
+        'Programming Language :: Python :: 3.8',
+        'Intended Audience :: Science/Research',
+        'Topic :: Scientific/Engineering :: Information Analysis',
+        'Topic :: Software Development :: Libraries :: Python Modules',
+    ]
 )