diff --git a/README.md b/README.md
index 1197e53aa..a3f2fbcaa 100644
--- a/README.md
+++ b/README.md
@@ -298,7 +298,7 @@ $ ./configure --build=aarch64-unknown-linux-gnu
 ```
 
 This is caused by old ``config.guess`` file, so another way to solve this is
-to copy a newer version of config.guess into the underyling TA-Lib C library
+to copy a newer version of config.guess into the underlying TA-Lib C library
 sources:
 
 ```
diff --git a/talib/_abstract.pxi b/talib/_abstract.pxi
index 39a9792c1..b3c1e6c72 100644
--- a/talib/_abstract.pxi
+++ b/talib/_abstract.pxi
@@ -89,7 +89,7 @@ class Function(object):
     - set_function_args([input_arrays,] [param_args_andor_kwargs])
 
     Documentation for param_args_andor_kwargs can be seen by printing the
-    Function instance or programatically via the info, input_names and
+    Function instance or programmatically via the info, input_names and
     parameters properties.
 
     ----- result-returning functions -----
diff --git a/talib/_ta_lib.c b/talib/_ta_lib.c
index be3333c81..7c242f556 100644
--- a/talib/_ta_lib.c
+++ b/talib/_ta_lib.c
@@ -3614,7 +3614,7 @@ static const char __pyx_k_Function_has_an_unstable_period[] = "Function has an u
 static const char __pyx_k_Kaufman_Adaptive_Moving_Average[] = "Kaufman Adaptive Moving Average";
 static const char __pyx_k_Out_of_Range_Start_Index_TA_OUT[] = "Out-of-Range Start Index (TA_OUT_OF_RANGE_START_INDEX)";
 static const char __pyx_k_TA_RestoreCandleDefaultSettings[] = "TA_RestoreCandleDefaultSettings";
-static const char __pyx_k_This_is_a_pythonic_wrapper_arou[] = "\n    This is a pythonic wrapper around TALIB's abstract interface. It is\n    intended to simplify using individual TALIB functions by providing a\n    unified interface for setting/controlling input data, setting function\n    parameters and retrieving results. Input data consists of a ``dict`` of\n    ``numpy`` arrays (or a ``pandas.DataFrame`` or ``polars.DataFrame``), one\n    array for each of open, high, low, close and volume. This can be set with\n    the set_input_arrays() method. Which keyed array(s) are used as inputs when\n    calling the function is controlled using the input_names property.\n\n    This class gets initialized with a TALIB function name and optionally an\n    input_arrays object. It provides the following primary functions for\n    setting inputs and retrieving results:\n\n    ---- input_array/TA-function-parameter set-only functions -----\n    - set_input_arrays(input_arrays)\n    - set_function_args([input_arrays,] [param_args_andor_kwargs])\n\n    Documentation for param_args_andor_kwargs can be seen by printing the\n    Function instance or programatically via the info, input_names and\n    parameters properties.\n\n    ----- result-returning functions -----\n    - the outputs property wraps a method which ensures results are always valid\n    - run([input_arrays]) # calls set_input_arrays and returns self.outputs\n    - FunctionInstance([input_arrays,] [param_args_andor_kwargs]) # calls set_function_args and returns self.outputs\n    ";
+static const char __pyx_k_This_is_a_pythonic_wrapper_arou[] = "\n    This is a pythonic wrapper around TALIB's abstract interface. It is\n    intended to simplify using individual TALIB functions by providing a\n    unified interface for setting/controlling input data, setting function\n    parameters and retrieving results. Input data consists of a ``dict`` of\n    ``numpy`` arrays (or a ``pandas.DataFrame`` or ``polars.DataFrame``), one\n    array for each of open, high, low, close and volume. This can be set with\n    the set_input_arrays() method. Which keyed array(s) are used as inputs when\n    calling the function is controlled using the input_names property.\n\n    This class gets initialized with a TALIB function name and optionally an\n    input_arrays object. It provides the following primary functions for\n    setting inputs and retrieving results:\n\n    ---- input_array/TA-function-parameter set-only functions -----\n    - set_input_arrays(input_arrays)\n    - set_function_args([input_arrays,] [param_args_andor_kwargs])\n\n    Documentation for param_args_andor_kwargs can be seen by printing the\n    Function instance or programmatically via the info, input_names and\n    parameters properties.\n\n    ----- result-returning functions -----\n    - the outputs property wraps a method which ensures results are always valid\n    - run([input_arrays]) # calls set_input_arrays and returns self.outputs\n    - FunctionInstance([input_arrays,] [param_args_andor_kwargs]) # calls set_function_args and returns self.outputs\n    ";
 static const char __pyx_k_Values_represent_an_upper_limit[] = "Values represent an upper limit";
 static const char __pyx_k_integer_values_are_100_0_or_100[] = "integer (values are -100, 0 or 100)";
 static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import";