Merge branch 'master' of https://github.com/ODM2/ODM2PythonAPI into setup

Getting rid of the set up branch. Fingers crossed.

Author: denvaar

.gitignore

@@ -1,8 +1,7 @@
 *.py[cod]
-
+*~
 
 #  C extensions
-*.ipynb
 *.so
 
 #  Packages

src/Examples/Sample 1.1.py Examples/Sample 1.1.pysrc/Examples/Sample 1.1.py renamed to Examples/Sample 1.1.py

@@ -1,9 +1,9 @@
 __author__ = 'stephanie'
 import sys
 import os
-from api.ODMconnection import dbconnection
+from odm2api.ODMconnection import dbconnection
 import pprint
-from api.ODM1_1_1.services import SeriesService
+from odm2api.ODM1_1_1.services import SeriesService
 
 this_file = os.path.realpath(__file__)
 directory = os.path.dirname(this_file)

src/Examples/Sample.py Examples/Sample.pysrc/Examples/Sample.py renamed to Examples/Sample.py

@@ -13,16 +13,17 @@
 # print directory
 # sys.path.insert(0, directory)
 
-from api.ODMconnection import dbconnection
-from api.ODM2.services.readService import *
+from odm2api.ODMconnection import dbconnection
+from odm2api.ODM2.services.readService import *
 # Create a connection to the ODM2 database
 # ----------------------------------------
 
 
 #connect to database
 #createconnection (dbtype, servername, dbname, username, password)
 #session_factory = dbconnection.createConnection('mysql', 'localhost', 'odm2', 'ODM', 'odm')
-session_factory = dbconnection.createConnection('sqlite', '/Users/stephanie/DEV/DBs/ODM2.sqlite', 2.0)
+#session_factory = dbconnection.createConnection('connection type: sqlite|mysql|mssql|postgresql', '/your/path/to/db/goes/here', 2.0)
+session_factory = dbconnection.createConnection('sqlite', '/Users/denversmith/Downloads/ODM2.sqlite', 2.0)
 # session_factory= dbconnection.createConnection('mssql')
 
 
@@ -68,26 +69,25 @@
     print "Unable to demo getSamplingFeaturesByType", e
 
 
-
 # Now get the SamplingFeature object for a SamplingFeature code
 try:
     sf = read.getSamplingFeatureByCode('USU-LBR-Mendon')
+    print sf
     print "\n-------- Information about an individual SamplingFeature ---------"
-    print (
-        "The following are some of the attributes of a SamplingFeature retrieved using getSamplingFeatureByCode(): \n" +
-        "SamplingFeatureCode: " + sf.SamplingFeatureCode + "\n" +
-        "SamplingFeatureName: " + sf.SamplingFeatureName + "\n" +
-        "SamplingFeatureDescription: " + sf.SamplingFeatureDescription + "\n" +
-        "SamplingFeatureGeotypeCV: " + sf.SamplingFeatureGeotypeCV + "\n" +
-        "SamplingFeatureGeometry: " + sf.FeatureGeometry + "\n" +
-        "Elevation_m: " + str(sf.Elevation_m))
+    print "The following are some of the attributes of a SamplingFeature retrieved using getSamplingFeatureByCode(): \n"
+    print "SamplingFeatureCode: " + sf.SamplingFeatureCode
+    print "SamplingFeatureName: " + sf.SamplingFeatureName
+    print "SamplingFeatureDescription: %s" % sf.SamplingFeatureDescription
+    print "SamplingFeatureGeotypeCV: %s" % sf.SamplingFeatureGeotypeCV
+    print "SamplingFeatureGeometry: %s" % sf.FeatureGeometry
+    print "Elevation_m: %s" % str(sf.Elevation_m)
 except Exception as e:
     print "Unable to demo getSamplingFeatureByCode: ", e
 
 #add sampling feature
 print "\n------------ Create Sampling Feature --------- \n",
 try:
-    from api.ODM2.models import SamplingFeatures
+    from odm2api.ODM2.models import SamplingFeatures
     newsf = SamplingFeatures()
     session = session_factory.getSession()
     newsf.FeatureGeometry = "POINT(-111.946 41.718)"
@@ -127,27 +127,27 @@
 # Now get a particular Result using a ResultID
 print "\n------- Example of Retrieving Attributes of a Time Series Result -------"
 try:
-    tsResult = read.getTimeSeriesResultByResultId(19)
+    tsResult = read.getTimeSeriesResultByResultId(1)
     print (
         "The following are some of the attributes for the TimeSeriesResult retrieved using getTimeSeriesResultByResultID(): \n" +
-        "ResultTypeCV: " + tsResult.ResultTypeCV + "\n" +
+        "ResultTypeCV: " + tsResult.ResultObj.ResultTypeCV + "\n" +
         # Get the ProcessingLevel from the TimeSeriesResult's ProcessingLevel object
-        "ProcessingLevel: " + tsResult.ProcessingLevelObj.Definition + "\n" +
-        "SampledMedium: " + tsResult.SampledMediumCV + "\n" +
+        "ProcessingLevel: " + tsResult.ResultObj.ProcessingLevelObj.Definition + "\n" +
+        "SampledMedium: " + tsResult.ResultObj.SampledMediumCV + "\n" +
         # Get the variable information from the TimeSeriesResult's Variable object
-        "Variable: " + tsResult.VariableObj.VariableCode + ": " + tsResult.VariableObj.VariableNameCV + "\n"
+        "Variable: " + tsResult.ResultObj.VariableObj.VariableCode + ": " + tsResult.ResultObj.VariableObj.VariableNameCV + "\n"
                                                                                                         "AggregationStatistic: " + tsResult.AggregationStatisticCV + "\n" +
         "Elevation_m: " + str(sf.Elevation_m) + "\n" +
         # Get the site information by drilling down
-        "SamplingFeature: " + tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureCode + " - " +
-        tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName)
+        "SamplingFeature: " + tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureCode + " - " +
+        tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName)
 except Exception as e:
     print "Unable to demo Example of retrieving Attributes of a time Series Result: ", e
 
 # Get the values for a particular TimeSeriesResult
 print "\n-------- Example of Retrieving Time Series Result Values ---------"
 
-tsValues = read.getTimeSeriesResultValuesByResultId(19)  # Return type is a pandas dataframe
+tsValues = read.getTimeSeriesResultValuesByResultId(1)  # Return type is a pandas dataframe
 
 # Print a few Time Series Values to the console
 # tsValues.set_index('ValueDateTime', inplace=True)
@@ -162,9 +162,9 @@
     fig = plt.figure()
     ax = fig.add_subplot(111)
     tsValues.plot(x='ValueDateTime', y='DataValue', kind='line',
-                  title=tsResult.VariableObj.VariableNameCV + " at " + tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName,
+                  title=tsResult.ResultObj.VariableObj.VariableNameCV + " at " + tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName,
                   ax=ax)
-    ax.set_ylabel(tsResult.VariableObj.VariableNameCV + " (" + tsResult.UnitObj.UnitsAbbreviation + ")")
+    ax.set_ylabel(tsResult.ResultObj.VariableObj.VariableNameCV + " (" + tsResult.ResultObj.UnitsObj.UnitsAbbreviation + ")")
     ax.set_xlabel("Date/Time")
     ax.xaxis.set_minor_locator(dates.MonthLocator())
     ax.xaxis.set_minor_formatter(dates.DateFormatter('%b'))

src/Forms/clsDBConfig.py Forms/clsDBConfig.pysrc/Forms/clsDBConfig.py renamed to Forms/clsDBConfig.py

@@ -0,0 +1,3 @@
+include README.md
+include *.txt
+

src/Forms/frmDBConfig.py Forms/frmDBConfig.pysrc/Forms/frmDBConfig.py renamed to Forms/frmDBConfig.py

@@ -6,3 +6,26 @@ A Python-based application programmer's interface for the Observations Data Mode
 ### Credits
 
 This work was supported by National Science Foundation Grants [EAR-1224638](http://www.nsf.gov/awardsearch/showAward?AWD_ID=1224638) and [ACI-1339834](http://www.nsf.gov/awardsearch/showAward?AWD_ID=1339834). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
+
+### Installation
+
+Currently the easiest and most reliable way to install the ODM2 Python API (`odm2api`) is using the [Conda package management system](http://conda.pydata.org/docs/) via either [Anaconda](https://www.continuum.io/downloads) or [Miniconda](http://conda.pydata.org/miniconda.html). To create a new `odm2api` environment, first download the conda environment file [condaenvironment_1.yml](https://raw.githubusercontent.com/ODM2/ODM2PythonAPI/master/condaenvironment_1.yml). Then, on a terminal shell:
+
+1. Add conda to the PATH; on MacOSX and Linux, it's something like `export PATH=$HOME/miniconda/bin:$PATH`, but the exact path may vary.
+2. Go to the directory where `condaenvironment_1.yml` was downloaded.
+3. Create a new conda environment. This command will create an environment called 'odm2api_env1':    
+
+  ```bash
+  conda env create -f condaenvironment_1.yml
+  ```
+4. Activate the new environment:    
+
+  ```bash
+  activate odm2api_env1  # On Windows
+  source activate odm2api_env1  # On MacOSX or Linux
+  ```
+5. Install the `odm2api` package into the environment:  
+
+  ```bash
+  pip install --process-dependency-links git+https://github.com/ODM2/ODM2PythonAPI.git
+  ```

MANIFEST.in

@@ -0,0 +1,15 @@
+name: odm2api_env1
+channels:
+  - ioos
+dependencies:
+  - python=2.7
+  - pip
+  - ipython-notebook
+  - scipy
+  - pandas
+  - seaborn
+  - sqlalchemy
+  - psycopg2
+  - pymysql
+  - pyodbc
+  - shapely