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4 Commits
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e3d6952517
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e3d6952517 | ||
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408e2a8de5 | ||
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66b5fd6b31 | ||
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0ca5217ddc |
3
.gitignore
vendored
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3
.gitignore
vendored
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*.pyc
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.idea
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build*
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221
attribution.py
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221
attribution.py
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# -*- coding: utf-8 -*-
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import os
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import datetime
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import logging
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import pandas as pd
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from dateutil.relativedelta import relativedelta
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L = logging.getLogger(__name__)
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class AttributionReport(object):
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def __init__(self, months=6, footer_length=None):
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self.months = months
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self.footer_length = footer_length
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self.SF_DATE_COLUMN = "Date"
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self.DP_DATE_COLUMN = "Date Received"
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self.PI_COLUMN = "PI_Name"
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self.ORG_COLUMN = "Org Name"
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# Output the XLSX in this order
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self.OUTPUT_COLUMN_ORDER = ["Addgene Assigned", "Plasmid ID", "Deposit ID", "Institute", "PI Name",
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"Date Received", "Original Date", "Original ORG", "Original PI"]
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self.ACCEPTABLE_EXTENSIONS = ["*.csv", "*.xls", "*.xlsx"]
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# columns that need to be in the files
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self.REQUIRED_SF_COLUMNS = ["First Name", "Last Name", "Account Name", "Date", "Assigned"]
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self.REQUIRED_DP_COLUMNS = ["Org Name", "Deposit ID", "Plasmid ID", "PI_Name", "Date Received"]
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# After load and merging, delete these columns
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self.SF_TRIM_COLUMNS = ["Subject", "Created Date", "LIMS Organization ID",
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"Account Description"]
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self.DP_TRIM_COLUMNS = ["Org ID", "Deposit Status", "PI_ID", "Date Available", "# Orders",
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"# Plasmids in the Deposit", "Addgene Contact", "Country"]
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self.salesforce_df = None
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self.deposit_df = None
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self.output_dir = None
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self.frames = None
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def _get_dataframe_by_extension(self, path, date_cols):
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"""
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Gets a dataframe either by .csv, or .xls(x),
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or erroring and exiting.
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"""
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_, ext = os.path.splitext(path)
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if ext == ".csv":
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df = pd.read_csv(path, parse_dates=date_cols, encoding='utf-8')
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elif ext in [".xlsx", ".xls"]:
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df = pd.read_excel(path, parse_dates=date_cols, encoding='utf-8')
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else:
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raise Exception("File was not of type {0}.\nQuitting".format(
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" ".join(self.ACCEPTABLE_EXTENSIONS)))
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return df
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def set_dataframe_sf(self, fname):
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self.salesforce_df = None
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try:
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salesforce_df = self._get_dataframe_by_extension(fname, date_cols=[self.SF_DATE_COLUMN, ])
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except IndexError:
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return False
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except ValueError:
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return False
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except:
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raise
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if set(self.REQUIRED_SF_COLUMNS) < set(salesforce_df.columns):
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self.salesforce_df = salesforce_df
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return True
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L.info("Wrong columns")
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return False
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def set_dataframe_deposit(self, fname):
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self.deposit_df = None
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try:
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deposit_df = self._get_dataframe_by_extension(fname, date_cols=[self.DP_DATE_COLUMN, ])
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except IndexError:
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return False
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except ValueError:
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return False
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except:
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raise
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if set(self.REQUIRED_DP_COLUMNS) < set(deposit_df.columns):
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self.deposit_df = deposit_df
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return True
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L.info("Wrong columns")
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return False
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def set_output_dir(self, dir):
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self.output_dir = dir
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def get_dataframes(self):
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salesforce_df, deposit_df = self.clean_dataframes()
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return salesforce_df, deposit_df
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def clean_dataframes(self):
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# Get rid of the footer that Salesforce adds.
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if self.footer_length:
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length_with_footer = len(self.salesforce_df.index)
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self.salesforce_df = self.salesforce_df.head(length_with_footer - self.footer_length)
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# Clean up Salesforce
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self.salesforce_df.sort(self.SF_DATE_COLUMN, ascending=1)
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# Cleanup Deposit Data
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self.deposit_df['Org Name'].fillna('', inplace=True)
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self.deposit_df.sort(self.DP_DATE_COLUMN, ascending=1)
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self.deposit_df['PI_Name'].astype(unicode)
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# Cleanup not needed columns
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for col in self.SF_TRIM_COLUMNS:
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del self.salesforce_df[col]
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for col in self.DP_TRIM_COLUMNS:
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del self.deposit_df[col]
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def get_filtered(self, filtered_df, sf_row, pi_name, pi_org, org=False):
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"""
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Assume kind is PI by default.
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Filter where either the PI and PI match, or the Org and Org match
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If both match, add it to the the double list
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if only one matches, add it to the single list.
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"""
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filter_column = self.PI_COLUMN
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filter_value = pi_name
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single, double = [], []
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if org:
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filter_column = self.ORG_COLUMN
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filter_value = pi_org
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name_match = filtered_df[filtered_df[filter_column] == filter_value]
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if not name_match.empty:
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for _, row in name_match.iterrows():
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data = {
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"Addgene Assigned": sf_row['Assigned'],
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"Plasmid ID": row['Plasmid ID'],
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"Deposit ID": row['Deposit ID'],
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"Institute": row['Org Name'],
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"PI Name": row['PI_Name'],
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"Date Received": row[self.DP_DATE_COLUMN],
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"Original Date": sf_row[self.SF_DATE_COLUMN],
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"Original ORG": pi_org,
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"Original PI": pi_name,
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}
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if (data['Institute'] == data['Original ORG']) and \
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(data['PI Name'] == data['Original PI']):
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double.append(data)
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else:
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single.append(data)
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return single, double
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def get_attribution_dataframes(self):
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self.clean_dataframes()
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name_matches = []
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org_matches = []
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double_matches = []
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mismatches = []
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# Iterate through the Salesforce report as the master document
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for index, sf_row in self.salesforce_df.iterrows():
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# Get a start date and an end date for filtering.
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start_date = sf_row[self.SF_DATE_COLUMN]
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end_date = start_date + relativedelta(months=self.months)
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start = self.deposit_df[self.DP_DATE_COLUMN].searchsorted(start_date)[0]
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end = self.deposit_df[self.DP_DATE_COLUMN].searchsorted(end_date)[0]
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# Filter the deposit data to grab only things within that timeframe.
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filtered_df = self.deposit_df.ix[start:end]
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# Variables for short names, and not having to type index a lot.
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pi_name = unicode(sf_row['First Name']) + " " + unicode(sf_row['Last Name'])
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pi_org = sf_row['Account Name']
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# Get matches by the PI's name
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by_name, pi_by_both = self.get_filtered(filtered_df, sf_row, pi_name, pi_org)
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name_matches.extend(by_name)
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mismatches.extend(by_name)
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double_matches.extend(pi_by_both)
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# Get matches by the organization name
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by_org, org_by_both = self.get_filtered(filtered_df, sf_row, pi_name, pi_org, org=True)
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org_matches.extend(by_org)
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mismatches.extend(by_org)
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double_matches.extend(org_by_both)
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return (
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("PI", pd.DataFrame(name_matches, columns=self.OUTPUT_COLUMN_ORDER)),
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("Institute", pd.DataFrame(org_matches, columns=self.OUTPUT_COLUMN_ORDER)),
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("Double", pd.DataFrame(double_matches, columns=self.OUTPUT_COLUMN_ORDER)),
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("Single", pd.DataFrame(mismatches, columns=self.OUTPUT_COLUMN_ORDER))
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)
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def run(self):
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self.frames = None
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self.frames = self.get_attribution_dataframes()
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def save(self):
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for key, df in self.frames:
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fname = '{0}_Attribution_Report_{1}_Match.xlsx'.format(datetime.date.today(), key)
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output_path = os.path.join(self.output_dir, fname)
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deduped_df = df.drop_duplicates()
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with pd.ExcelWriter(output_path, engine='xlsxwriter') as writer:
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deduped_df.to_excel(writer, sheet_name='Sheet1', index=False)
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if __name__ == '__main__':
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app = AttributionReport(months=6, footer_length=6)
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app.set_dataframe_deposit("/Users/tyrelsouza/Dropbox (Addgene)/Addgene Shared/Dev/Attribution Report/deposit_data.csv")
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app.set_dataframe_sf("/Users/tyrelsouza/Dropbox (Addgene)/Addgene Shared/Dev/Attribution Report/salesforce_report.xlsx")
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app.set_output_dir("/Users/tyrelsouza/Dropbox (Addgene)/Addgene Shared/Dev/Attribution Report/Output/")
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app.run()
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app.save()
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170
main.py
170
main.py
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import os
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import json
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import pandas as pd
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import dropbox
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from dateutil.relativedelta import relativedelta
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DROPBOX = False
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local_dropbox_path = "/Users/tyrelsouza/Dropbox (Addgene)/"
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SF_DATE = "Date"
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DP_DATE = "Date Received"
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class AttributionReport(object):
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def __init__(self, credentials_file, months=6, footer_length=None):
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self.months = months
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self.footer_length = footer_length
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self.PI_COLUMN = "PI_Name"
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self.ORG_COLUMN = "Org Name"
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with open(credentials_file, "r") as cred_f:
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creds = json.loads(cred_f.read())
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self.app_key = creds['app_key']
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self.app_secret = creds['app_secret']
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if not creds.get("access_token", None):
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self.authorize()
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else:
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self.access_token = creds['access_token']
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self.user_id = creds['user_id']
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def authorize(self):
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flow = dropbox.client.DropboxOAuth2FlowNoRedirect(self.app_key, self.app_secret)
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authorize_url = flow.start()
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print '1. Go to: ' + authorize_url
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print '2. Click "Allow" (you might have to log in first)'
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print '3. Copy the authorization code.'
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code = raw_input("Enter the authorization code here: ").strip()
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access_token, user_id = flow.finish(code)
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self.access_token = access_token
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self.user_id = user_id
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creds = {"app_key": self.app_key,
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"app_secret": self.app_secret,
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"access_token": self.access_token,
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"user_id": self.user_id}
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# Save so we don't have to do this again.
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with open("credentials.json", "w") as f:
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f.write(json.dumps(creds))
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def _open_file_frame(self, filename, date_cols):
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if DROPBOX:
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client = dropbox.client.DropboxClient(self.access_token)
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f = client.get_file(filename)
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else:
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f = os.path.normpath(local_dropbox_path + filename)
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if filename[-4:] == ".csv":
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df = pd.read_csv(f, parse_dates=date_cols, encoding='utf-8')
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else:
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df = pd.read_excel(f, parse_dates=date_cols, encoding='utf-8')
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return df
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def get_dataframes(self):
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"""
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This gets the Salesforce and the Deposit dataframes.
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Then it does some cleanup of the columns
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"""
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salesforce_data_name = '/Addgene Shared/Dev/Attribution Report/salesforce_report.xlsx'
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salesforce_df = self._open_file_frame(salesforce_data_name, date_cols=[4, 5])
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if self.footer_length:
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length_with_footer = len(salesforce_df.index)
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salesforce_df = salesforce_df.head(length_with_footer - self.footer_length)
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deposit_data_name = 'Addgene Shared/Dev/Attribution Report/deposit_data.csv'
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deposit_df = self._open_file_frame(deposit_data_name, date_cols=[7, 8])
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# Clean up Salesforce
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salesforce_df['Account Description'].fillna('', inplace=True)
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salesforce_df.sort(SF_DATE, ascending=1)
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salesforce_df["Full Name"] = salesforce_df["First Name"].map(unicode) + " " + salesforce_df["Last Name"]
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del salesforce_df["First Name"]
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del salesforce_df["Last Name"]
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# Cleanup Deposit Data
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deposit_df['Org Name'].fillna('', inplace=True)
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deposit_df.sort(DP_DATE, ascending=1)
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deposit_df['PI_Name'].astype(unicode)
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return salesforce_df, deposit_df
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def get_filtered(self, filtered_df, sf_row, pi_name, pi_org, kind):
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if kind == "PI":
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filter_column = self.PI_COLUMN
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filter_value = pi_name
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elif kind == "ORG":
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filter_column = self.ORG_COLUMN
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filter_value = pi_org
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name_match = filtered_df[filtered_df[filter_column] == filter_value]
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output = []
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if not name_match.empty:
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for _, row in name_match.iterrows():
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data = {
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"Addgene Assigned": sf_row['Assigned'],
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"Plasmid ID": row['Plasmid ID'],
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"Deposit ID": row['Deposit ID'],
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"Institute": row['Org Name'],
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"PI Name": row['PI_Name'],
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"Date Received": row[DP_DATE],
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"Original Date": sf_row[SF_DATE],
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"Original ORG": pi_org,
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"Original PI": pi_name,
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}
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output.append(data)
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return output
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def get_attribution_dataframes(self):
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salesforce, dep = self.get_dataframes()
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name_matches = []
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org_matches = []
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# Iterate through the Salesforce report as the master document
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for index, sf_row in salesforce.iterrows():
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# Get a start date and an end date for filtering.
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start_date = sf_row[SF_DATE]
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end_date = start_date + relativedelta(months=self.months)
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start = dep[DP_DATE].searchsorted(start_date)[0]
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end = dep[DP_DATE].searchsorted(end_date)[0]
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# Filter the deposit data to grab only things within that timeframe.
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filtered_df = dep.ix[start:end]
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# Variables for short names, and not having to type index a lot.
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pi_name = unicode(sf_row['Full Name'])
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pi_org = sf_row['Account Name']
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# Get matches by the PI's name
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by_name = self.get_filtered(filtered_df,
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sf_row,
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pi_name,
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pi_org,
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kind="PI")
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name_matches.extend(by_name)
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# Get matches by the organization name
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by_org = self.get_filtered(filtered_df,
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sf_row,
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pi_name,
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pi_org,
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kind="ORG")
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org_matches.extend(by_org)
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return pd.DataFrame(name_matches), pd.DataFrame(org_matches)
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def run(self):
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name_df, org_df = self.get_attribution_dataframes()
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name_df.to_excelv("names.xls")
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org_df.to_excel("orgs.xls")
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if __name__ == '__main__':
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report = AttributionReport(credentials_file="credentials.json",
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months=6,
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footer_length=6)
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report.run()
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@ -1,4 +1,4 @@
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dropbox
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pandas
|
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xlrd
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python-dateutil
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XlsxWriter==0.7.3
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pandas==0.16.2
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python-dateutil==2.4.2
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xlrd==0.9.4
|
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|
|
25
utils.py
Normal file
25
utils.py
Normal file
|
@ -0,0 +1,25 @@
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|||
__author__ = 'tyrelsouza'
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import os
|
||||
import json
|
||||
|
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|
||||
def get_dropbox_dir():
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"""
|
||||
Windows and Mac get dropox dir for Business or fallback to personal
|
||||
"""
|
||||
if os.name == "nt":
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||||
dropbox_file = os.path.join(os.getenv('APPDATA'), 'Dropbox', 'info.json')
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||||
else:
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dropbox_file = os.path.expanduser("~/.dropbox/info.json")
|
||||
|
||||
with open(dropbox_file) as dbf:
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dbconfig = json.loads(dbf.read())
|
||||
|
||||
if "business" in dbconfig:
|
||||
dropbox_dir = dbconfig['business']['path']
|
||||
elif "personal" in dbconfig:
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||||
dropbox_dir = dbconfig['personal']['path']
|
||||
else:
|
||||
dropbox_dir = os.path.expanduser("~")
|
||||
|
||||
return dropbox_dir
|
Loading…
Reference in New Issue
Block a user