pip install khquizgen
If using from commandline prefix with -m flag and use the built-in inputs and oputputs path.
If you want to use different input/output dirs you will need to make a settings.toml file and set INCLUDES_FOR_DYNACONF=path\to\settings.toml
Or you can set envars directly: set DYNACONF_OUTPUT=path\to\output\dir and set DYNACONF_INPUT=path\to\input\dir and maybe logs set DYNACONF_LOGS=path\to\logs\dir
If you are importing it you can set a settings.toml and set os.environs['INCLUDES_FOR_DYNACONF'] or each of the individual settings like above in your script before import. It is important that you set the envar before importing khquizgen, otherwise it will use its PACKAGEDIR instead of your settings.
- Takes your notes and intelligently generate random Multiple-Choice sets formatted in a spreadsheet ready to upload straight to Kahoot.
- Notes should follow the Root-Trunk-Branch-Leaf schema. An example can be found in the source input folder.
- Roots are your overarching topics. When the script randomly generates questions, it first randomly selects a root, and then attempts to make a question, answer, and four multiple choices from within that Root.
- Trunks are your specific subtopic. If your Root was Vehicles your Trunks could be Car, Train, Airplane
- Branches are the defining characteristics of your Trunk. These should be generalizeable to all of the Trunks for the widest spread of useable questions, but they do not -need- to be. If your Trunk was Car your branches could be Speed, Mass, Fuel
- Leaves are the values for each branch. You can have multiple leaves by separating them with a comma. If Car was your trunk, and Mass is your branch, a leaf could be 2 tons
- The code first randomly selects a Root and makes a set from all of the available Trunks.
roots = [Vehicles, Dinosaurs, France]root = Vehicles - It randomly selects a Trunk from this set and then makes a set from all of the avaiable branches.
Vehicles:[Car, Plane, Train]trunk = Car - It randomly selects a Branch, and its Leaf. If there are multiple leaves, it will select one randomly.
Car:[Mass, Speed, Fuel]branch = Mass - Branch and Trunk are parsed together and become a potential question.
trunk = Car branch = MassQ1 = "Car Mass" - Your leaf is also a potential question.
Q2 = "2 Tons" - Coin toss decides which question remains as the question, the other becomes the answer.
coin = rand.choice[1,2] = 1question, answer = Q1, Q2 if coin == 1 else Q2, Q1 - Code then loops through steps 2-5, references the coin toss, and discards the corresponding option.
potQ1 = Train Speed potQ2 = 200mphpotA = potQ2 if coin ==1 else potQ1 - It compares the new potential answer against the original answer using Jaro-Winkler Similarity formula. If the potential answer scores 0.45 or less, or 1.0 (identical), the answer is discarded and the cycle begins again. In this case, 200mph would be discarded, and the cycle starts again.
- After four suitable multiple choices are found, the cycle begins at step 1.
- This loop cycles until 100 questions are formed, since that is the limit imposed by Kahoot.
Diagnostic::: Diabetes:: A1C: >6.5% Fasting Glucose: >126mg/dL 2hr Glucose Tolerance: >200mg/dL Hyperglycemia or crisis: >200mg/dL Pre-Diabetes:: A1C: 5.7-6.5% Fasting Glucose: 100-125mg/dL 2hr Glucose Tolerance: 140-199mg/dL Normal:: A1C: 4.5-5.6% Fasting Glucose: <100mg/dL 2hr Glucose Tolerance: <140mg/dL Meals::: Normal:: Preprandial Glucose: 70-99mg/dL Postprandial Glucose: <140mg/dL A1C: 4.5-5.6% Diabetic Goal:: Preprandial Glucose: 80-130mg/dL Postprandial Glucose: <180mg/dL A1C: <7% Drugs::: Metformin:: MOA: Decrease heaptic glucose by inhibiting gluconeogenesis Use case: Always unless contraindicated by kidney disease Efficacy: High efficacy Advantage: Promote weight loss, hyperglycemic, affordable Disadvantage: GI side effects, lactic acidosis, increased risk in PT with CKD, requires adequate GF, vitamin B12 deficiency Sulfonylurea:: MOA: Close K+-ATP channel and force Beta-cell insulin release Use case: Cost is primary concern Efficacy: High efficacy Advantage: Affordable Disadvantage: Hypoglycemia, weight gain, waning efficacy Meglinitide:: MOA: Close K+-ATP channel and force Beta-cell insulin release Use case: SUR hypoglycemia are concerns Efficacy: Low efficacy Advantage: Short half-lfe, reduced hypoglycemia Disadvantage: Frequent administration, hypoglycemia, weight gain TZD:: MOA: Improve insulin sensitivity by increaseing GLUT4 translocation in muscle and adipocytes Use case: Cost or hypoglycemia main concerns Efficacy: High efficacy Advantage: Affordable, anti-hyperglycemic, decrease ectopic lipids, decrease inflammatory cytokines from adipose cells, increase adiponectin, decrease lipolysis Disadvantage: weight gain, increased fluid retention (edema), increased risk of heart failure, anemia GLP-1 Agonist:: MOA: Enhance glucose-stimulated insulin secretion and paracrine effect on glucagon Use case: Cardiovasccular risk or hypoglycemia are main concerns Efficacy: High efficacy Advantage: Anti-hyperglycemic, weight loss, decreases risk for cardiovascular disease, increases satiety Disadvantage: GI side effects, expensive, increased risk for pancreatitis, increased risk for thyroid cancer DPP-4 Inhibitor:: MOA: Prolongs lifespan of endogenous incretins Use case: Hypoglycemia is main concern Efficacy: Low efficacy Advantage: Anti-hyperglycemic, well-tolerated, oral administration Disadvantage: Expensive SGLT-2 Inhibitor:: MOA: Blocks reabsorption of glucose in kidneys Use case: Weight management, cardiovascular risk, or hypoglycemia are main concerns` Efficacy: Low efficacy Advantage: Anti-hyperglycemic, decreases risk of cardiovascular disease, decreases risk of heart failure, slows progression of diabetic nephropathy, weight loss Disadvantage: Increased risk of UTI, increased risk of osmotic diuresis, increased risk of ketoacidosis in T2D, not effective if eGFR <30ml/min $$$$