Merge branch 'master' of bitbucket.org:panleicim/appointment_tool

src/utils/contacts/check_contact_name.py

@@ -0,0 +1,7 @@
+from src.utils.excel_reader import read_contacts
+
+_contact_list = read_contacts(file_name="/Users/panlei/Desktop/yahoo_aol_valid_23.xlsx")
+# print(_contact_list)
+for _contact in _contact_list:
+    if _contact.last_name is None or _contact.first_name is None:
+        print(_contact.mail)

src/utils/contacts/generate_random_passport_id.py

@@ -57,7 +57,7 @@ def generate_titre_sejour_number(size=10) -> list:
 if __name__ == '__main__':
     # for i in range(1,200):
     #     print(get_random_id_number())
-    # for i in range(1, 501):
-    #     print(get_random_passport_id_number())
-    for id in generate_titre_sejour_number(3200):
-        print(id)
+    for i in range(1, 101):
+        print(get_random_passport_id_number())
+    # for id in generate_titre_sejour_number(3200):
+    #     print(id)

src/utils/export_registered_users.py

@@ -0,0 +1,63 @@
+import xlsxwriter
+
+from src.db.mongo_manager import MONGO_STORE_MANAGER
+from src.utils.excel_reader import read_contacts
+
+
+class ExportedUser:
+    def __init__(self, last_name, first_name, password, mail, phone):
+        self.last_name = last_name
+        self.first_name = first_name
+        self.password = password
+        self.mail = mail
+        self.phone = phone
+
+
+def export_registered_users() -> list:
+    _user_list = MONGO_STORE_MANAGER.get_all_registered_users()
+    print(len(_user_list))
+    return _user_list
+    # for _user in _user_list:
+    #     print(_user)
+
+
+def read_contacts_to_check():
+    _contact_list = read_contacts(file_name="/Users/panlei/Desktop/check_names.xlsx")
+    return _contact_list
+
+
+def write_to_excel(_to_export_list):
+    row = 0
+    col = 0
+    # Create a workbook and add a worksheet.
+    workbook = xlsxwriter.Workbook('check_names_of_contacts_{}.xlsx'.format(len(_to_export_list)))
+    header_data = ['Nom/姓', 'Prénom/名', 'phone/电话', 'mail/邮箱', 'mot de pass/密码']
+    worksheet = workbook.add_worksheet()
+    header_format = workbook.add_format({'bold': True})
+
+    for col_num, data in enumerate(header_data):
+        worksheet.write(row, col_num, data, header_format)
+    row = row + 1
+    for info in _to_export_list:
+        info.phone = info.phone
+        # Iterate over the data and write it out row by row.
+        worksheet.write(row, col, info.last_name)
+        worksheet.write(row, col + 1, info.first_name)
+        worksheet.write(row, col + 2, "0"+info.phone)
+        worksheet.write(row, col + 3, info.mail)
+        worksheet.write(row, col + 4, info.password)
+        row += 1
+    workbook.close()
+
+
+if __name__ == '__main__':
+    _user_list = export_registered_users()
+    contact_list = read_contacts_to_check()
+    _to_export = []
+    for _user in _user_list:
+        for contact in contact_list:
+            if _user.mail == contact.mail:
+                _export_user = ExportedUser(contact.last_name, contact.first_name, _user.password, contact.mail,
+                                            contact.phone)
+                _to_export.append(_export_user)
+    write_to_excel(_to_export)

src/utils/generate_graphe_from_excel.py

@@ -0,0 +1,76 @@
+import colorsys
+import json
+import random
+
+import numpy as np
+import pandas
+import matplotlib.patches as mpatches
+from matplotlib import pyplot as plt
+
+from src.pojo.ReserveResultPojo import ReserveResultPojo
+
+
+def read_reserve_pojo_from_excel(file_path: str):
+    print("read file " + file_path)
+    contact_list_in_json = pandas.read_excel(file_path)
+    # .to_json(orient='records'))
+    plot_bargraph_with_groupings(contact_list_in_json, "source_from", "source_from", "分布", "型号", "数量")
+    # contact_dict_list = json.loads(contact_list_in_json)
+    # contact_list = []
+    # for contact_dict in contact_dict_list:
+    #     last_name = contact_dict['last_name']
+    #     first_name = contact_dict['first_name']
+    #     phone_number = contact_dict['phone']
+    #     source_from = contact_dict['source_from']
+    #     contact = ReserveResultPojo()
+    #     contact.lastName = last_name
+    #     contact.firstName = first_name
+    #     contact.phone = phone_number
+    #     contact.source_from = source_from
+    #     contact_list.append(contact)
+    # return contact_list
+
+
+def plot_bargraph_with_groupings(df, groupby, colourby, title, xlabel, ylabel):
+    """
+    Plots a dataframe showing the frequency of datapoints grouped by one column and coloured by another.
+    df : dataframe
+    groupby: the column to groupby
+    colourby: the column to color by
+    title: the graph title
+    xlabel: the x label,
+    ylabel: the y label
+    """
+    randHSVcolors = [(np.random.rand(), 1, 1) for i in range(len(df[colourby].unique()))]
+    # Convert HSV list to RGB
+    randRGBcolors = []
+    for HSVcolor in randHSVcolors:
+        randRGBcolors.append(colorsys.hsv_to_rgb(HSVcolor[0], HSVcolor[1], HSVcolor[2]))
+    # Makes a mapping from the unique colourby column items to a random color.
+    ind_col_map = {x: y for x, y in zip(df[colourby].unique(),
+                                        randRGBcolors)}
+
+    # Find when the indicies of the soon to be bar graphs colors.
+    unique_comb = df[[groupby, colourby]].drop_duplicates()
+    name_ind_map = {x: y for x, y in zip(unique_comb[groupby], unique_comb[colourby])}
+    values_counts = df[groupby].value_counts()
+    c = values_counts.index.map(lambda x: ind_col_map[name_ind_map[x]])
+
+    # Makes the bargraph.
+    ax = df[groupby].value_counts().plot(kind='bar',
+                                         # figsize=FIG_SIZE,
+                                         title=title,
+                                         color=[c.values])
+    # Makes a legend using the ind_col_map
+    legend_list = []
+    for key in ind_col_map.keys():
+        legend_list.append(mpatches.Patch(color=ind_col_map[key], label=key))
+
+    # display the graph.
+    plt.legend(handles=legend_list)
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+
+
+if __name__ == '__main__':
+    read_reserve_pojo_from_excel("/Users/panlei/2023_10_27.xlsx")