/
pyserver.patch
251 lines (248 loc) · 8.88 KB
/
pyserver.patch
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Index: nodeServer/scripts.js
IDEA additional info:
Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
<+>UTF-8
===================================================================
diff --git a/nodeServer/scripts.js b/nodeServer/scripts.js
--- a/nodeServer/scripts.js (revision 02355e75a6b51c67b6fbe6eae6024d31e2cdeee9)
+++ b/nodeServer/scripts.js (date 1656392862396)
@@ -68,6 +68,7 @@
let dropProgramSchema;
let documentsTable;
+let getAllDocumentsProcedure;
let participationTable;
let mapButtonsTable;
@@ -432,6 +433,12 @@
\`link_verified\` VARCHAR(255) CHARACTER SET utf8
);`;
+getAllDocumentsProcedure =
+ `CREATE PROCEDURE getAllDocumentsProcedure()\n
+ BEGIN\n
+ SELECT * from documents;\n
+ END;`;
+
participationTable =
`CREATE TABLE participation (
\`id\` INT,
Index: .gitignore
IDEA additional info:
Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
<+>UTF-8
===================================================================
diff --git a/.gitignore b/.gitignore
--- a/.gitignore (revision 02355e75a6b51c67b6fbe6eae6024d31e2cdeee9)
+++ b/.gitignore (date 1656391642343)
@@ -5,3 +5,5 @@
package-lock.json
/.idea/
/.vs/
+
+/pythonServer/config.py
\ No newline at end of file
Index: pythonServer/server.py
IDEA additional info:
Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
<+>UTF-8
===================================================================
diff --git a/pythonServer/server.py b/pythonServer/server.py
new file mode 100644
--- /dev/null (date 1656389991649)
+++ b/pythonServer/server.py (date 1656389991649)
@@ -0,0 +1,31 @@
+from http.server import BaseHTTPRequestHandler, HTTPServer
+import document_reporting
+
+hostName = "localhost"
+serverPort = 8080
+
+
+class MyServer(BaseHTTPRequestHandler):
+ def do_GET(self):
+ document_reporting.main('UBHub_database_test.xlsx', 1, 'doc_type', 'doc_year')
+ self.send_response(200)
+ self.send_header("Content-type", "text/html")
+ self.end_headers()
+ self.wfile.write(bytes("<html><head><title>testfig</title></head>", "utf-8"))
+ self.wfile.write(bytes("<p>Request: %s</p>" % self.path, "utf-8"))
+ self.wfile.write(bytes("<body>", "utf-8"))
+ self.wfile.write(bytes("<p>This is an example web server.</p>", "utf-8"))
+ self.wfile.write(bytes("</body></html>", "utf-8"))
+
+
+if __name__ == "__main__":
+ webServer = HTTPServer((hostName, serverPort), MyServer)
+ print("Server started http://%s:%s" % (hostName, serverPort))
+
+ try:
+ webServer.serve_forever()
+ except KeyboardInterrupt:
+ pass
+
+ webServer.server_close()
+ print("Server stopped.")
Index: pythonServer/document_reporting.py
IDEA additional info:
Subsystem: com.intellij.openapi.diff.impl.patch.CharsetEP
<+>UTF-8
===================================================================
diff --git a/pythonServer/document_reporting.py b/pythonServer/document_reporting.py
new file mode 100644
--- /dev/null (date 1657593265576)
+++ b/pythonServer/document_reporting.py (date 1657593265576)
@@ -0,0 +1,156 @@
+# -*- coding: utf-8 -*-
+import pandas as pd
+import seaborn as sns
+from sqlalchemy import create_engine
+import config
+
+
+def read_sql():
+ engine = create_engine("mysql+pymysql://" + config.username + ":" + config.password + "@" + config.hostname + ":" + config.portnumber + "/" + config.databasename + "")
+ connection = engine.connect()
+ # for chunk in pd.read_sql_query('CALL getAllDocumentsProcedure();', connection, chunksize=5):
+ # print(chunk)
+ cursorResult = engine.execute('CALL getAllDocumentsProcedure();', multi=True)
+
+ dataFrame = pd.DataFrame(cursorResult)
+ # dataFrame = pd.read_sql_query('CALL getAllDocumentsProcedure();', connection)
+ # The above code fails if this limit is removed. We don't know why yet. Additional research: why does sqlalchemy cursor have error closing when there is no limit? We tried iterating with chunks, but that simply fails for more very long reasons.
+ # next debug query to SO: pandas read_sql without limit
+ # https://stackoverflow.com/questions/18107953/how-to-create-a-large-pandas-dataframe-from-an-sql-query-without-running-out-of
+ # dataFrame = pd.DataFrame()
+ # for chunk in pd.read_sql('select * from documents', connection, chunksize=10):
+ # dataFrame.append(chunk)
+ connection.close()
+ print(dataFrame)
+ return dataFrame
+
+
+def read_excel(xlsFile, sheet):
+ dataFrame = pd.read_excel(xlsFile, sheet_name=sheet)
+ return dataFrame
+
+
+def get_unique_values(dataFrame, column):
+ values = sorted(list(dataFrame[column].dropna().unique()))
+ return values
+
+
+def construct_lf_dataframe(dataFrame, colNameDocs, colNameYears):
+ years = get_unique_values(dataFrame, colNameYears)
+ numberYears = len(years)
+
+ docTypes = get_unique_values(dataFrame, colNameDocs)
+ numberDocTypes = len(docTypes)
+
+ N = numberYears*numberDocTypes
+
+ # initialize counter and lists
+ k = 0
+ yearsList = []
+ docTypesList = []
+ numDocsList = []
+
+ # begin loop for building lists to put into empty data frame
+ for i in years:
+ for j in docTypes:
+ # build lists
+ yearsList.append(i)
+ docTypesList.append(j)
+ numDocs = len(dataFrame[(dataFrame[colNameYears] == i) &
+ (dataFrame[colNameDocs] == j)])
+ numDocsList.append(numDocs)
+ k += 1
+
+ # define columns for new dataframe
+ columnNames = ['Year', 'Document Type', 'Number of Documents']
+ # create new dataframe (long form)
+ dataFrameLf = pd.DataFrame(columns=columnNames, index=range(N))
+ dataFrameLf['Year'] = yearsList
+ dataFrameLf['Document Type'] = docTypesList
+ dataFrameLf['Number of Documents'] = numDocsList
+
+ return dataFrameLf, numberDocTypes
+
+
+def plot_data(dataFrame, numberDocTypes):
+
+ # make all the prominent curves in each subgraph green
+ color = sns.cubehelix_palette(start=2, rot=0, dark=0.5,
+ light=0.5, n_colors=numberDocTypes)
+
+ # make relational plots onto facet grid
+ plot = sns.relplot(data=dataFrame, x="Year", y="Number of Documents",
+ col="Document Type", hue="Document Type",
+ kind="line", palette=color,
+ linewidth=4, zorder=5,
+ col_wrap=5, height=1.75, aspect=1.5, legend=False
+ )
+
+ # add text and silhouettes
+ for time, ax in plot.axes_dict.items():
+ ax.text(.1, 1, time,
+ transform=ax.transAxes, fontweight="bold"
+ )
+ sns.lineplot(data=dataFrame, x="Year", y="Number of Documents", units="Document Type",
+ estimator=None, color=".7", linewidth=1, ax=ax
+ )
+
+ # set labels for each subgraph and tighten layout
+ plot.set_titles("")
+ plot.set_axis_labels("Year", "# Documents")
+ plot.tight_layout()
+
+ plot.savefig("test3.svg")
+
+
+def main(excel, sheet, colNameDocType, colNameYear):
+
+ # dataFrame = read_excel(excel, sheet)
+ dataFrame = read_sql()
+
+ # tabulate the number of document types per year into long form dataframe
+ dataFrameLong,numDocumentTypes = construct_lf_dataframe(dataFrame, colNameDocType, colNameYear)
+
+ # plot the data using a relational plot
+ plot_data(dataFrameLong,numDocumentTypes)
+
+
+if __name__ == "__main__":
+
+ ################################### INPUTS ####################################
+
+ # UBHub database location (excel sheet; will need to update)
+ excelFile = 'UBHub_database_test.xlsx'
+ # sheet number in excel file where document type data is stored
+ tab = 1
+ # column name pointing to document type (e.g., Biodiversity Plan)
+ docTypeColName = 'doc_type'
+ # column name pointing to year of document reporting
+ yearColName = 'doc_year'
+ # if false, run through main function
+ testing = False
+
+ ############################### TESTING FLAGS #################################
+
+ # read excel file
+ readExcel = True
+ # get unique values from specific column of dataframe
+ getUniqueValues = False
+ # construct a long form dataframe with number of documents tabulated
+ constructLFDataFrame = True
+ # make relational plot between different document types over time
+ plotData = True
+
+ ###############################################################################
+
+ if testing:
+ if readExcel:
+ df = read_excel(excelFile, tab)
+ if getUniqueValues:
+ vals = get_unique_values(df, docTypeColName)
+ if constructLFDataFrame:
+ dfLongForm,numDocsTypes = construct_lf_dataframe(df, docTypeColName, yearColName)
+ if plotData:
+ plot_data(dfLongForm, numDocsTypes)
+ else:
+ main(excelFile, tab, docTypeColName, yearColName)