feat: a little more math

.gitignore

@@ -1,2 +1,3 @@
 /venv
 /venv/*
+__pycache__/

Makefile

@@ -3,8 +3,15 @@ install:
 	pip install --upgrade pip
 	pip install -r requirements.txt
 
+save:
+	pip freeze > requirements.txt
+
 run:
 	python src/main.py
 
 test:
 	python -m pytest -v
+
+setenv:
+	python -m venv venv
+	source venv/bin/activate

requirements.txt

@@ -1,6 +1,13 @@
+iniconfig==2.1.0
+mpmath==1.3.0
 numpy==2.3.3
+packaging==25.0
 pandas==2.3.3
+pluggy==1.6.0
+Pygments==2.19.2
+pytest==8.4.2
 python-dateutil==2.9.0.post0
 pytz==2025.2
 six==1.17.0
+sympy==1.14.0
 tzdata==2025.2

src/main.py

@@ -1,4 +1,14 @@
-from modules.math import t_compound_interest, t_compound_interest_algorigthm, t_exponent
+from modules.math import (
+	t_calculate_e,
+	t_calculate_e_limit,
+	t_compound_interest,
+	t_compound_interest_algorigthm,
+	t_compound_interest_continious,
+	t_compound_interest_continious_exp,
+	t_exponent,
+	t_limit,
+	t_logarithm_natural,
+)
 from modules.strings import t_strings
 
 if __name__=="__main__":
@@ -6,3 +16,10 @@ if __name__=="__main__":
 	t_exponent(2,8)
 	print(t_compound_interest(100, 20 / 100, 2, 12))
 	print(t_compound_interest_algorigthm(100, 20 / 100, 2, 12))
+	print(t_compound_interest_continious(100, 20 / 100, 2))
+	print(t_compound_interest_continious_exp(100, 20 / 100, 2))
+	print(t_calculate_e(1000000000000))
+	print(t_logarithm_natural(10))
+	print(t_limit())
+	print(t_calculate_e_limit())
+	print(t_calculate_e_limit().evalf())

src/modules/math.py

@@ -1,5 +1,8 @@
 from cmath import log as complex_log  # used for complex numbers
-from math import log
+from math import e, exp, log
+
+# Sympy is powerful since it does not make aproximations, it keeps every primitive as it is, this means that it's slower but more precisse
+from sympy import limit, oo, symbols
 
 
 def t_summ():
@@ -24,3 +27,26 @@ def t_compound_interest_algorigthm(input, interest, span, periods):
 		for _ in range(0, periods):
 			result += result * (interest / periods)
 	return result
+
+def t_compound_interest_continious(input, interest, span):
+	return input * (e ** (interest * span))
+
+def t_compound_interest_continious_exp(input,interest, span):
+	return input * exp(interest * span)
+
+def t_calculate_e(precission):
+	return (1 + 1 / precission) ** precission
+
+def t_logarithm_natural(value):
+	return log(value) # The default base is e
+
+def t_limit():
+	x = symbols("x")
+	f = 1 / x
+	result = limit(f, x, oo)
+	return result
+
+def t_calculate_e_limit():
+	x = symbols("x")
+	f = (1 + 1 / x) ** x
+	return limit(f, x, oo)