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Vincent Allen
2026-05-21 08:40:24 -04:00
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42
section_1_word_export_scripts/counselling_interval_analysis.py Normal file
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# FILE: counselling_interval_analysis.py
# CREATED: 1/12/25
# AUTHOR: Vincent Allen
# CONTACT: valle276@live.kutztown.edu vincent@vtallen.com
# Calls the word document builder with the necessary functions and files extracted from the target image door, to create a final word document for the Neoserra counseling interval scorecard report.
import argparse
from pasbdc_word_library import WordDocumentBuilder, PageConfig
from section_1_word_library_module import counselling_interval_analysis
from shared_tools_module import ImageRegistry
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--images", required=True)
parser.add_argument("--reportname", required=False, help="The filename prefix identifying images for this report.", default="counselling-interval")
parser.add_argument("--output", required=True, help="The name to give the output file")
args = parser.parse_args()
registry = ImageRegistry(args.images, args.reportname)
builder = WordDocumentBuilder()
builder.create_document(
[
PageConfig(page_function=counselling_interval_analysis, add_page_break=False)
],
args.output,
section_number=2,
desk_review_section_number=1,
days_client_signup_to_client_start=registry.get("signuptostart", ""),
days_client_signup_to_first_counseling=registry.get("signuptocounselling", ""),
days_client_start_to_first_counseling=registry.get("starttocounselling", ""),
days_initial_to_followup_counseling=registry.get("initialtofollowup", ""),
days_training_to_counseling=registry.get("trainingtocounselling", "")
)
if __name__ == "__main__":
main()

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section_1_word_export_scripts/generate_naics_word.py Normal file
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# FILE: generate_naics_word.py
# CREATED: 1/12/25
# AUTHOR: Vincent Allen
# CONTACT: valle276@live.kutztown.edu vincent@vtallen.com
# Calls the word document builder with the necessary functions and files extracted from the target image door, to create a final word document for the NAICS census report.
import argparse
import os
# import the word library
from pasbdc_word_library import WordDocumentBuilder, PageConfig
# import the word page generators
from section_1_word_library_module import (
naics_penetration_page_one,
naics_penetration_page_two
)
from shared_tools_module import ImageRegistry
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--images", required=True)
parser.add_argument("--reportname", required=False, help="The filename prefix identifying images for this report.", default="naicsanalysis")
parser.add_argument("--output", required=True, help="The name to give the output file")
# Configuration arguments
parser.add_argument("--section", type=int, default=1, help="The section number for this report.")
parser.add_argument("--desk_review_section", type=int, default=1, help="The top-level desk review section number.")
args = parser.parse_args()
registry = ImageRegistry(args.images, args.reportname)
builder = WordDocumentBuilder()
builder.create_document(
[
PageConfig(page_function=naics_penetration_page_one, add_page_break=True),
PageConfig(page_function=naics_penetration_page_two, add_page_break=False)
],
args.output,
# Report Configuration
section_number=args.section,
desk_review_section_number=args.desk_review_section,
percent_missing_naics=0.0,
# naicsanalysis_naicsdescriptiontable_.png (Cat: naicsdescriptiontable, Var: "")
# naicsanalysis_pasbdccensuscomparisongraph_.png (Cat: pasbdccensuscomparisongraph, Var: "")
# naicsanalysis_county_heatmap_naics_.png (Cat: county_heatmap, Var: naics)
sector_table=registry.get("naicsdescriptiontable", ""),
penetration_graph=registry.get("pasbdccensuscomparisongraph", ""),
county_map=registry.get("countyheatmapnaics", "")
)
if __name__ == "__main__":
main()

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section_1_word_export_scripts/generate_trainings_analysis_word.py Normal file
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# FILE: generate_trainings_analysis_word.py
# CREATED: 1/12/25
# AUTHOR: Vincent Allen
# CONTACT: valle276@live.kutztown.edu vincent@vtallen.com
# Calls the word document builder with the necessary functions and files extracted from the target image door, to create a final word document for the trainings analysis report (including the center specific topic analysis as well).
import argparse
from functools import partial
# import the word library
from pasbdc_word_library import WordDocumentBuilder, PageConfig
# import the word page generators
from section_1_word_library_module import *
# import the variant naming map
from shared_tools_module import VARIANT_SUFFIX_MAP
# import the chart variants enum
from section_1_graph_library_module import ( # pyright:ignore
StatChartVariants
)
from shared_tools_module import ImageRegistry
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--images", required=True)
parser.add_argument("--reportname", required=False, help="The filename prefix identifying images for this report. Defaults to trainingsreport", default="trainingsreport")
parser.add_argument("--centerchartcategorybase", required=False, type=str, default="topicanalysis",
help="The chart category to use for the center specific graphs to find the chart images with ImageRegistry. The center name will be appended to the end of this value and should be the second part of the filename.")
parser.add_argument("--output", required=True, help="The name to give the output file")
args = parser.parse_args()
# Parse the image paths in the selected dir and build the dictionary
registry = ImageRegistry(args.images, args.reportname)
builder = WordDocumentBuilder()
builder.create_document(
[
PageConfig(page_function=training_events_page_one, add_page_break=False),
PageConfig(page_function=attendee_bin_charts_page_maker, add_page_break=True),
PageConfig(page_function=event_count_attendee_count_page_maker, add_page_break=True),
PageConfig(page_function=primary_topic_analysis_page_maker, add_page_break=True),
PageConfig(page_function=attendee_counts_page_maker, add_page_break=False),
PageConfig(page_function=event_count_page_maker, add_page_break=True),
PageConfig(page_function=zero_attendee_events_page_maker, add_page_break=True),
],
args.output,
fiscal_year="FY25",
section_number=7,
desk_review_section_number=1,
center="Network Wide",
# Get the paths of all network wide graphs
total_trainings_count_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_COUNT]),
total_trainings_percent_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_PERCENT]),
total_trainings_no_first_count_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_COUNT]),
total_trainings_no_first_percent_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_PERCENT]),
total_trainings_no_first_no_pre_count_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_COUNT]),
total_trainings_no_first_no_pre_percent_chart=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_PERCENT]),
total_trainings_first_pre_only_count=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY]),
total_trainings_first_pre_only_percent=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY_PERCENT]),
total_trainings_ondemand_count=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_COUNT]),
total_trainings_ondemand_percent=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_PERCENT]),
total_trainings_ondemand_no_first_count=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_NO_FIRST_STEPS_COUNT]),
total_trainings_ondemand_no_first_percent=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_NO_FIRST_STEPS_PERCENT]),
total_trainings_ondemand_no_first_no_pre_count=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_NO_FIRST_STEPS_NO_PREPLANNING_COUNT]),
total_trainings_ondemand_no_first_no_pre_percent=registry.get("center-statistics", VARIANT_SUFFIX_MAP[StatChartVariants.ON_DEMAND_NO_FIRST_STEPS_NO_PREPLANNING_PERCENT]),
attendee_bin_chart_total_count=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_COUNT]),
attendee_bin_chart_total_percent=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_PERCENT]),
attendee_bin_chart_no_first_no_pre_total_count=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_COUNT]),
attendee_bin_chart_no_first_no_pre_total_percent=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_PERCENT]),
attendee_bin_chart_first_pre_total_count=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY]),
attendee_bin_chart_first_pre_total_percent=registry.get("attendee-bins", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY_PERCENT]),
primary_topic_pie_total=registry.get("topics-pie", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_PERCENT]),
primary_topic_pie_no_first_total=registry.get("topics-pie", VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_PERCENT]),
primary_topic_bar_small_topics_total=registry.get('training-topics', VARIANT_SUFFIX_MAP[StatChartVariants.SMALL_BARS_TRAININGS]),
primary_topic_bar_small_topics_percent=registry.get('training-topics', VARIANT_SUFFIX_MAP[StatChartVariants.SMALL_BARS_TRAININGS_PERCENT]),
attendee_counts_total=registry.get("center-attendees", VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_COUNT]),
attendee_counts_percent=registry.get('center-attendees', VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_PERCENT]),
attendee_counts_first_pre_count=registry.get('center-attendees', VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY]),
attendee_counts_first_pre_percent=registry.get('center-attendees', VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY_PERCENT]),
event_count_attendee_count_total=registry.get('attendee-ranges', VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_COUNT]),
event_count_attendee_count_first_pre_total=registry.get('attendee-ranges', VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY]),
event_counts_total=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_COUNT]),
event_counts_percent=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_PERCENT]),
event_counts_attended_total=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.TOTAL_ATTENDED]),
event_counts_attended_percent=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.PERCENT_ATTENDED]),
event_counts_no_first_total=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_COUNT]),
event_counts_no_first_percent=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_PERCENT]),
event_counts_no_first_attended_total=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_ATTENDED_COUNT]),
event_counts_no_first_attended_percent=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_STEPS_ATTENDED_PERCENT]),
event_counts_no_first_no_pre_total=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_COUNT]),
event_counts_no_first_no_pre_percent=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.NO_FIRST_NO_PREPLANNNG_PERCENT]),
event_counts_first_only=registry.get("event-counts", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_ONLY]),
event_counts_first_only_percent=registry.get("event-counts", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_ONLY_PERCENT]),
event_counts_first_pre_only=registry.get('event-counts', VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY]),
event_counts_first_pre_only_percent=registry.get("event-counts", VARIANT_SUFFIX_MAP[StatChartVariants.FIRST_AND_PREPLANNING_ONLY_PERCENT]),
)
if __name__ == "__main__":
main()

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section_1_word_export_scripts/make_nbs_funding_analysis.py Normal file
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# FILE: make_nbs_funding_analysis.py
# CREATED: 1/12/25
# AUTHOR: Vincent Allen
# CONTACT: valle276@live.kutztown.edu vincent@vtallen.com
# PURPOSE:
# Calls the word document builder with the necessary functions and files extracted from the target image door, to create a final word document for the milestone attribution report.
# Creates both the NBS and funding report.
import argparse
from pasbdc_word_library import WordDocumentBuilder, PageConfig
from section_1_word_library_module import (
capital_acquisition_analysis_page,
new_business_start_analysis_page
)
from shared_tools_module import ImageRegistry
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--images", required=True)
parser.add_argument("--output", required=True, help="The name to give the output file")
# Added report name parameters with defaults matching the provided file list
parser.add_argument("--funding_reportname", required=False, default="fundinganalysis",
help="The filename prefix identifying funding images. Defaults to fundinganalysis")
parser.add_argument("--nbs_reportname", required=False, default="nbsanalysis",
help="The filename prefix identifying NBS images. Defaults to nbsanalysis")
args = parser.parse_args()
# Initialize registries using the arguments
funding_registry = ImageRegistry(args.images, args.funding_reportname)
nbs_registry = ImageRegistry(args.images, args.nbs_reportname)
builder = WordDocumentBuilder()
builder.create_document(
[
PageConfig(page_function=capital_acquisition_analysis_page, add_page_break=True),
PageConfig(page_function=new_business_start_analysis_page, add_page_break=False)
],
args.output,
# Report Configuration
section_number=5,
desk_review_section_number=1,
# Funding Chart Paths
funding_overview_graph=funding_registry.get("fundingattributionnetworkwide", ""),
funding_attribution_chart=funding_registry.get("fundingattributionrate", ""),
funding_attribution_potential_chart=funding_registry.get("theoreticalfundingattributionrate", ""),
# NBS Chart Paths
nbs_overview_graph=nbs_registry.get("nbsattributionnetworkwide", ""),
nbs_attribution_chart=nbs_registry.get("nbsattributionrate", ""),
nbs_attribution_potential_chart=nbs_registry.get("theoreticalnbsattributionrate", ""),
)
if __name__ == "__main__":
main()

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section_1_word_export_scripts/satisfaction_survey_word.py Normal file
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# FILE: satisfaction_survey_report_controller.py
# CREATED: 2/2/26
# AUTHOR: Vincent Allen
# CONTACT: valle276@live.kutztown.edu vincent@vtallen.com
# PURPOSE:
# Controller script that generates a satisfaction survey report Word document.
# Uses ImageRegistry to discover survey graph images and calls the
# satisfaction_survey_analysis_word functions to create the formatted report.
# Custom modules
from section_1_word_library_module import client_survey_analysis_page_one
from pasbdc_word_library import WordDocumentBuilder, PageConfig
from shared_tools_module import ImageRegistry
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--images", type=str, required=True, help="The path to the folder contining the images for this report.")
parser.add_argument("--output", type=str, required=True, help="The .docx file to save the final report to. Must end in .docx")
parser.add_argument("--sectionnumber", type=int, required=False, default=10, help="The subsection that this report represents of the desk reviews. Defaults to 10")
parser.add_argument("--deskreviewsectionnumber", type=int, required=False, default=1, help="The parent section that this report is a part of. Defaults to 1.")
args = parser.parse_args()
# Initialize the image registry
registry = ImageRegistry(
image_folder=args.images,
report_name="satisfactionsurvey"
)
# Retrieve image paths using the registry
responses_count_chart = registry.get("surveyresponsecounts", "")
recommendation_chart = registry.get("surveyaveragescore", "")
per_client_chart = registry.get("surveyresponsesperclient", "")
nps_chart = registry.get("surveynpsscore", "")
# Create document builder
builder = WordDocumentBuilder()
# Generate the document
builder.create_document(
[
PageConfig(page_function=client_survey_analysis_page_one, add_page_break=False)
],
args.output,
# Report Configuration
responses_count_chart=responses_count_chart,
recommendation_chart=recommendation_chart,
per_client_chart=per_client_chart,
nps_chart=nps_chart,
section_number=args.sectionnumber,
desk_review_section_number=args.deskreviewsectionnumber
)
print("Satisfaction survey report created successfully!")