Checking Concept Drift in SNARIMAX model #1097

XaviMartiCamarasa · 2022-11-24T08:40:20Z

XaviMartiCamarasa
Nov 24, 2022

Hi, I'm trying/playing/struggling in Time Series Forecasting, trying SNARIMAX model and thinking how to include Concept Drift checking.

import calendar
 import math
 import datetime as dt
 from river import compose
 from river import linear_model
 from river import optim
 from river import preprocessing
 horizon = 6
 def get_month_distances(x):
     return {
         calendar.month_name[month]: math.exp(-(x['month'].month - month) ** 2)
         for month in range(1, 13)
     }

 def get_ordinal_date(x):
     return {'ordinal_date': x['month'].toordinal()}

 extract_features = compose.TransformerUnion(
     get_ordinal_date,
     get_month_distances
 )
 future = [
    {'month': dt.date(year=1961, month=m, day=1)}
        for m in range(1, horizon + 1)
 ]
 model = (
     extract_features |
     time_series.SNARIMAX(
         p=1,
         d=0,
         q=0,
         m=12,
         sp=3,
         sq=6,
         regressor=(
             preprocessing.StandardScaler() |
             linear_model.LinearRegression(
                 intercept_init=110,
                 optimizer=optim.SGD(0.01),
                 intercept_lr=0.3
             )
         )
     )
 )
 #metrica=metrics.MAE()
 for x, y in datasets.AirlinePassengers():
     print("y",y)
     print ("X",x)
     model = model.learn_one(x, y) #<<<<<How could I check here if a concept drift occurs and restart de model
     a=model.forecast(6)
     
     print ("a",a)

Many thanks!

Answered by MaxHalford

Nov 24, 2022

That's a $100k question! We have a drift module to check for concept drift on univariate data. But we don't good examples of using concept drift + model restarting in conjunction. We have all the pieces of the puzzle, but the puzzle hasn't been assembled yet. For instance, there is a model.clone() method which is handy for this.

Small tip: you can highlight your Python code properly if you use py instead of just

View full answer

MaxHalford · 2022-11-24T09:48:07Z

MaxHalford
Nov 24, 2022
Maintainer

That's a $100k question! We have a drift module to check for concept drift on univariate data. But we don't good examples of using concept drift + model restarting in conjunction. We have all the pieces of the puzzle, but the puzzle hasn't been assembled yet. For instance, there is a model.clone() method which is handy for this.

Small tip: you can highlight your Python code properly if you use py instead of just

12 replies

XaviMartiCamarasa Nov 25, 2022
Author

Morning Max.
What is.. exactly Rust?

XaviMartiCamarasa Nov 25, 2022
Author

How could I get the new version of River with the fix?

MaxHalford Nov 25, 2022
Maintainer

It's a compiled programming language. Installation instructions are here.

XaviMartiCamarasa Nov 25, 2022
Author

But...what is the relation between RUST and upgrading river from git?

MaxHalford Nov 25, 2022
Maintainer

River has some Rust code in it. So when you install it from git (via pip), you need Rust to compiles these pieces of code. If you try without Rust, it will ask you to install Rust.

XaviMartiCamarasa · 2022-11-24T19:18:05Z

XaviMartiCamarasa
Nov 24, 2022
Author

Your job is more important Max. Many thanks!

…

On Thu, Nov 24, 2022 at 8:15 PM Max Halford ***@***.***> wrote: Checking now. Sorry but I also have a paying job to do :) — Reply to this email directly, view it on GitHub <#1097 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HEL7EUPVQLZIU574RLFTWJ65EJANCNFSM6AAAAAASKADCRQ> . You are receiving this because you authored the thread.Message ID: ***@***.***>

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0 replies

XaviMartiCamarasa · 2022-11-24T19:54:13Z

XaviMartiCamarasa
Nov 24, 2022
Author

Let me explain what I'm trying to do. (perhaps it is better)
My idea is testing two SNARIMAX Models (with two different horizons) agains a baseline forecaster (Holtwinters as you told me).
At same time, I'd like to check if Concept Drift appears, then reset the model and keep "training" with the new fresh data.

For testing purposes, I thinkiter_valuate method from time_series is enough. But how introduce there the idea of "checking concept drift"
If I'm not mistaken, this code checks the performance of the model and I could plot the measurements:

def get_month_distances(x):
    return {
        calendar.month_name[month]: math.exp(-(x['month'].month - month) ** 2)
        for month in range(1, 13)
    }

def get_ordinal_date(x):
    return {'ordinal_date': x['month'].toordinal()}

extract_features = compose.TransformerUnion(
    get_ordinal_date,
    get_month_distances
)
model_s = (
     extract_features |
     time_series.SNARIMAX(
         p=1,
         d=0,
         q=0,
         m=12,
         sp=3,
         sq=6,
         regressor=(
             preprocessing.StandardScaler() | #<<<<  Quitando el Scaler funcionar
             linear_model.LinearRegression(
                 intercept_init=110,
                 optimizer=optim.SGD(0.01),
                 intercept_lr=0.3
             )
         )
     )
 )
dataset = datasets.AirlinePassengers()
metricas = time_series.iter_evaluate(
     dataset=datasets.AirlinePassengers(),
     model=model_s,
     metric=metrics.MAE(),
     horizon=3)

for m in metricas:
       print(m)

Thanks in advance

4 replies

MaxHalford Nov 24, 2022
Maintainer

I'm not sure exactly what your question is, because you mention a few things. As I told you, there is currently no canonical way to combine a drift detection module with a predictive model. We simply haven't implemented that yet.

One thing to be aware of though, is that online machine learning models naturally forget the past. This is down to the way they learn. It's mechanical. Therefore, you usually don't have to worry too much about drift. Drift is usually more of an issue with batch models. But with online models, the more you learn, the more you forget the past. Does that make sense?

XaviMartiCamarasa Nov 24, 2022
Author

For Concept Drift the fastest you adapt to de Drift, the better the model will be,won't it?
Of course in the long term the model will adapt to the data, but if we do not handle the drift, the model will adapt later to the new data.
If I find a drift, I will clone the model being retrained from the "drift time"

that's my opinion

MaxHalford Nov 24, 2022
Maintainer

Right, but machine learning is not about opinions. I suggest you measure the performance of both approaches to be sure.

My "opinion" is that recreating a model from scratch is detrimental in that you lose all the information you had accumulated.

I think you should distinguish slow drift from brutal drift. If the drift is brutal, then yes you might want to start from scratch. But if the drift is gradual, then you might be ok just having your model learn.

XaviMartiCamarasa Nov 25, 2022
Author

Any idea of how to measure the performance of both approaches?

XaviMartiCamarasa · 2022-11-24T21:46:27Z

XaviMartiCamarasa
Nov 24, 2022
Author

Thanks for the advice.

…

On Thu, Nov 24, 2022 at 10:44 PM Max Halford ***@***.***> wrote: Right, but machine learning is not about opinions. I suggest you measure the performance of both approaches to be sure. My "opinion" is that recreating a model from scratch is detrimental in that you lose all the information you had accumulated. I think you should distinguish slow drift from brutal drift. If the drift is brutal, then yes you might want to start from scratch. But if the drift is gradual, then you might be ok just having your model learn. — Reply to this email directly, view it on GitHub <#1097 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HEL6FWXRERD55KLVYXZ3WJ7OUZANCNFSM6AAAAAASKADCRQ> . You are receiving this because you authored the thread.Message ID: ***@***.***>

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

0 replies

XaviMartiCamarasa · 2022-11-24T21:47:54Z

XaviMartiCamarasa
Nov 24, 2022
Author

Many many thanks Max for your support on this matter. On Thu, Nov 24, 2022 at 10:46 PM Jose Javier Marti Camarasa < ***@***.***> wrote:

…

Thanks for the advice. On Thu, Nov 24, 2022 at 10:44 PM Max Halford ***@***.***> wrote: > Right, but machine learning is not about opinions. I suggest you measure > the performance of both approaches to be sure. > > My "opinion" is that recreating a model from scratch is detrimental in > that you lose all the information you had accumulated. > > I think you should distinguish slow drift from brutal drift. If the drift > is brutal, then yes you might want to start from scratch. But if the drift > is gradual, then you might be ok just having your model learn. > > — > Reply to this email directly, view it on GitHub > <#1097 (reply in thread)>, > or unsubscribe > <https://github.com/notifications/unsubscribe-auth/A37HEL6FWXRERD55KLVYXZ3WJ7OUZANCNFSM6AAAAAASKADCRQ> > . > You are receiving this because you authored the thread.Message ID: > ***@***.***> >

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

0 replies

MaxHalford · 2022-11-24T22:08:39Z

MaxHalford
Nov 24, 2022
Maintainer

No worries @XaviMartiCamarasa, and good luck to you! You're in uncharted waters, so it's normal that you may find it difficult :)

0 replies

XaviMartiCamarasa · 2022-11-25T09:42:34Z

XaviMartiCamarasa
Nov 25, 2022
Author

Thanks, I'll check it out.

…

On Fri, Nov 25, 2022 at 10:28 AM Max Halford ***@***.***> wrote: River has some Rust code in it. So when you install it from git (via pip), you need Rust to compiles these pieces of code. If you try without Rust, it will ask you to install Rust. — Reply to this email directly, view it on GitHub <#1097 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HEL7574ZWCWGF24AYYZ3WKCBB7ANCNFSM6AAAAAASKADCRQ> . You are receiving this because you were mentioned.Message ID: ***@***.***>

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

0 replies

XaviMartiCamarasa · 2022-11-25T18:13:37Z

XaviMartiCamarasa
Nov 25, 2022
Author

Hi @MaxHalford , still facing the same issue.
What I did:

Download and install Rust.
pip install --> !pip install git+https://github.com/online-ml/river --upgrade
Restart the kernel
run the code again. Did I anything wrong?

Kind Regards

3 replies

MaxHalford Nov 25, 2022
Maintainer

I have no idea @XaviMartiCamarasa, it's working fine for me. It's difficult for me to debug these kind of issues. However, it does seem like you are not using the new code (I can see that via the error message). So I guess your Python environment has not picked up the fact you installed the latest development version.

XaviMartiCamarasa Nov 26, 2022
Author

Many thanks @MaxHalford , anyway!
Which is the las commit ingithub? to check what I cloned.

Kind Regards

MaxHalford Nov 26, 2022
Maintainer

You can see the latest commit ID yourself if you go to the main branch on the River repo.

XaviMartiCamarasa · 2022-11-26T10:42:13Z

XaviMartiCamarasa
Nov 26, 2022
Author

I'll do. Enjoy the weekend Max!

…

On Sat, Nov 26, 2022 at 11:19 AM Max Halford ***@***.***> wrote: You can see the latest commit ID yourself if you go to the main branch on the River repo. — Reply to this email directly, view it on GitHub <#1097 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HEL74BVF3AVKGN2L7QPTWKHP4BANCNFSM6AAAAAASKADCRQ> . You are receiving this because you were mentioned.Message ID: ***@***.***>

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

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Checking Concept Drift in SNARIMAX model #1097

XaviMartiCamarasa Nov 24, 2022

Replies: 9 comments · 19 replies

MaxHalford Nov 24, 2022 Maintainer

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XaviMartiCamarasa
Nov 24, 2022

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MaxHalford
Nov 24, 2022
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XaviMartiCamarasa Nov 25, 2022
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MaxHalford Nov 25, 2022
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XaviMartiCamarasa Nov 25, 2022
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MaxHalford Nov 25, 2022
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XaviMartiCamarasa
Nov 24, 2022
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XaviMartiCamarasa
Nov 24, 2022
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MaxHalford Nov 24, 2022
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XaviMartiCamarasa Nov 24, 2022
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XaviMartiCamarasa Nov 25, 2022
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XaviMartiCamarasa
Nov 24, 2022
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MaxHalford
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