# add_shared_dict_value
**Descripción**
Añade un valor a una clave del diccionario interno compartido. Esta función es utilizada por todos los procesos paralelos.
**Parámetros**
**Nombre**
**Tipo**
**Requerido**
**Descripción**
key
str
Si
La clave en el diccionario compartido
value
None
SI
El valor a añadir a la clave
**Return**
**Tipo**
None
**Versión**
- 1.0.0
**Ejemplo**
```
import pandoraPlugintools as pt
# Define a function to be executed by parallel processes
def process_data(item):
# Process the data and add a value to the shared dictionary
result = item * 2
pt.add_shared_dict_value(key=str(item), value=result)
# List of items to process
data_list = [1, 2, 3, 4, 5]
# Create a shared dictionary and lock for synchronization
shared_dict = multiprocessing.Manager().dict()
shared_dict_lock = multiprocessing.Manager().Lock()
# Set the shared dictionary and lock in the module
pt._SHARED_DICT = shared_dict
pt._SHARED_DICT_LOCK = shared_dict_lock
# Number of parallel processes to use
num_processes = 2
# Run the function for each item using parallel processes
success = pt.run_parallel(num_processes=num_processes, function=process_data, data_list=data_list, print_errors=True)
if success:
print("All processes executed successfully.")
else:
print("Errors occurred during process execution.")
In this example, the process_data function processes each item and adds a value to the shared dictionary using the add_shared_dict_value function. The run_parallel function is used to execute the process_data function in parallel processes for the given list of items. The shared dictionary and lock are created using the multiprocessing.Manager() and then assigned to the corresponding module variables _SHARED_DICT and _SHARED_DICT_LOCK in the pandoraPluginTools module.
```