falcon | magic web data plane API and microservices framework | REST library

 by   falconry Python Version: 3.1.1rc1 License: Apache-2.0

kandi X-RAY | falcon Summary

falcon is a Python library typically used in Web Services, REST, Framework applications. falcon has build file available, it has a Permissive License and it has high support. However falcon has 11 bugs and it has 7 vulnerabilities. You can install using 'pip install falcon' or download it from GitHub, PyPI.
The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.
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                      kandi-support Support

                        summary
                        falcon has a highly active ecosystem.
                        summary
                        It has 9036 star(s) with 897 fork(s). There are 267 watchers for this library.
                        summary
                        There were 5 major release(s) in the last 6 months.
                        summary
                        There are 156 open issues and 820 have been closed. On average issues are closed in 674 days. There are 8 open pull requests and 0 closed requests.
                        summary
                        It has a positive sentiment in the developer community.
                        summary
                        The latest version of falcon is 3.1.1rc1
                        falcon Support
                          Best in #REST
                            Average in #REST
                            falcon Support
                              Best in #REST
                                Average in #REST

                                  kandi-Quality Quality

                                    summary
                                    falcon has 11 bugs (0 blocker, 0 critical, 10 major, 1 minor) and 451 code smells.
                                    falcon Quality
                                      Best in #REST
                                        Average in #REST
                                        falcon Quality
                                          Best in #REST
                                            Average in #REST

                                              kandi-Security Security

                                                summary
                                                falcon has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
                                                summary
                                                falcon code analysis shows 7 unresolved vulnerabilities (7 blocker, 0 critical, 0 major, 0 minor).
                                                summary
                                                There are 125 security hotspots that need review.
                                                falcon Security
                                                  Best in #REST
                                                    Average in #REST
                                                    falcon Security
                                                      Best in #REST
                                                        Average in #REST

                                                          kandi-License License

                                                            summary
                                                            falcon is licensed under the Apache-2.0 License. This license is Permissive.
                                                            summary
                                                            Permissive licenses have the least restrictions, and you can use them in most projects.
                                                            falcon License
                                                              Best in #REST
                                                                Average in #REST
                                                                falcon License
                                                                  Best in #REST
                                                                    Average in #REST

                                                                      kandi-Reuse Reuse

                                                                        summary
                                                                        falcon releases are available to install and integrate.
                                                                        summary
                                                                        Deployable package is available in PyPI.
                                                                        summary
                                                                        Build file is available. You can build the component from source.
                                                                        summary
                                                                        falcon saves you 12929 person hours of effort in developing the same functionality from scratch.
                                                                        summary
                                                                        It has 26008 lines of code, 2726 functions and 222 files.
                                                                        summary
                                                                        It has medium code complexity. Code complexity directly impacts maintainability of the code.
                                                                        falcon Reuse
                                                                          Best in #REST
                                                                            Average in #REST
                                                                            falcon Reuse
                                                                              Best in #REST
                                                                                Average in #REST
                                                                                  Top functions reviewed by kandi - BETA
                                                                                  kandi has reviewed falcon and discovered the below as its top functions. This is intended to give you an instant insight into falcon implemented functionality, and help decide if they suit your requirements.
                                                                                  • Register an error handler
                                                                                    • Determines if we should wrap non - coroutines
                                                                                    • Check if a function is a python function
                                                                                    • Wrap non - coroutine functions
                                                                                  • Create a WS_ACESS event
                                                                                    • Translate a webSocket error into an error message
                                                                                    • Send a message
                                                                                    • Pump messages from the websocket
                                                                                  • Validate Range header
                                                                                  • Create a resolver function
                                                                                  • Receive a message from the server
                                                                                  • Creates a property property
                                                                                  • Inspect a compiled router
                                                                                  • Profile a VM
                                                                                  • Profile a benchmark
                                                                                  • The access route
                                                                                  • Find wheels and source dist
                                                                                  • Return a string representation of the middleware tree
                                                                                  • Create a function to encode uri
                                                                                  • Add a sink
                                                                                  • Creates a function to run before the given action
                                                                                  • Add a static route
                                                                                  • Default serialize error handler
                                                                                  • Decode a URI
                                                                                  • Creates a function that will be called after the given action
                                                                                  • Run the benchmarks
                                                                                  Get all kandi verified functions for this library.
                                                                                  Get all kandi verified functions for this library.

                                                                                  falcon Key Features

                                                                                  The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.

                                                                                  falcon Examples and Code Snippets

                                                                                  copy iconCopy
                                                                                  
                                                                                                                      $ cat plugin.test.json { "exporter_urls": [ "http://127.0.0.1:9121/metrics" ], "append_tags": ["region=bj", "dept=cloud"], "endpoint": "127.0.0.100", "ignore_metrics_prefix": ["go_"], "metric_prefix": "", "metric_type": {}, "default_mapping_metric_type": "COUNTER", "timeout": 500 }
                                                                                  cat plugin.test.json | ./prometheus-exporter-collector -b falcon -s 60 | curl -X POST -d @- http://127.0.0.1:1988/v1/push
                                                                                  Parse multipart/form-data requests in Falcon,Example
                                                                                  Pythondot imgLines of Code : 11dot imgLicense : Permissive (MIT)
                                                                                  copy iconCopy
                                                                                  
                                                                                                                      # Say you have a form with those fields: # - title => a string # - image => an image file def on_post(req, resp, **kwargs): title = req.get_param('title') image = req.get_param('image') # Read image as binary raw = image.file.read() # Retrieve filename filename = image.filename
                                                                                  FALCON-Phase ,Running the test dataset :horse_racing:
                                                                                  Cdot imgLines of Code : 10dot imgLicense : Non-SPDX (NOASSERTION)
                                                                                  copy iconCopy
                                                                                  
                                                                                                                      000000F 000000F_002 000000F 000000F_003 000001F 000001F_001 000001F 000001F_002 000001F 000001F_003
                                                                                  module load snakemake module load bwa/0.7.17 module load bedtools/2.27.1 module load samtools/1.7 module load mummer/4.0.0
                                                                                  Getting next value of groupby after explode with pandas
                                                                                  Pythondot imgLines of Code : 12dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
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                                                                                  exp_g = df['Emails'].explode().groupby(level=0)
                                                                                  df['Emails_final1'] = exp_g.first()
                                                                                  msk = df['Emails_final1'].notna()
                                                                                  df['Emails_final1'] = df['Emails_final1'].fillna(df['Emails 2'])
                                                                                  df['Emails_final2'] = exp_g.nth(1)
                                                                                  df['Emails_final2'] = df['Emails_final2'].mask(lambda x: ((x == df['Emails_final1']) | x.isna()) & msk, df['Emails 2'])
                                                                                  
                                                                                          Emails_final1  Emails_final2
                                                                                  falcon  jjj@gmail.com   jp@gmail.com
                                                                                  dog     www@gmail.com  zzz@gmail.com
                                                                                  cat     ccc@gmail.com           None
                                                                                  
                                                                                  How to merge pandas dataframes with different column names
                                                                                  Pythondot imgLines of Code : 20dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                  df2.columns = df2.columns.str[0]
                                                                                  df3.columns = df3.columns.str[0]
                                                                                  out = pd.concat([df1, df2, df3])
                                                                                  
                                                                                  out = pd.concat([df1, df2.rename(columns=lambda x:x[0]), df3.rename(columns=lambda x:x[0])])
                                                                                  
                                                                                        A    B    C    D
                                                                                  0    A0   B0   C0   D0
                                                                                  1    A1   B1   C1   D1
                                                                                  2    A2   B2   C2   D2
                                                                                  3    A3   B3   C3   D3
                                                                                  4    A4   B4   C4   D4
                                                                                  5    A5   B5   C5   D5
                                                                                  6    A6   B6   C6   D6
                                                                                  7    A7   B7   C7   D7
                                                                                  8    A8   B8   C8   D8
                                                                                  9    A9   B9   C9   D9
                                                                                  10  A10  B10  C10  D10
                                                                                  11  A11  B11  C11  D11
                                                                                  
                                                                                  How to merge pandas dataframes with different column names
                                                                                  Pythondot imgLines of Code : 16dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                  out = pd.DataFrame(np.concatenate([df1.values,df2.values,df3.values]),columns=df1.columns)
                                                                                  Out[346]: 
                                                                                        A    B    C    D
                                                                                  0    A0   B0   C0   D0
                                                                                  1    A1   B1   C1   D1
                                                                                  2    A2   B2   C2   D2
                                                                                  3    A3   B3   C3   D3
                                                                                  4    A4   B4   C4   D4
                                                                                  5    A5   B5   C5   D5
                                                                                  6    A6   B6   C6   D6
                                                                                  7    A7   B7   C7   D7
                                                                                  8    A8   B8   C8   D8
                                                                                  9    A9   B9   C9   D9
                                                                                  10  A10  B10  C10  D10
                                                                                  11  A11  B11  C11  D11
                                                                                  
                                                                                  Formatting Phone number with +1 with pandas.Series.replace
                                                                                  Pythondot imgLines of Code : 8dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                  df['Contact phone number'] = '+' + df['Contact phone number'].dropna().astype(str).str.extract(r'(\d)(\d{3})(\d{3})(\d{3})').apply(list, axis=1).str.join('-')
                                                                                  
                                                                                  >>> df
                                                                                         Company phone number Contact phone number  num_specimen_seen
                                                                                  falcon      +1-541-296-2271       +1-511-296-227                 10
                                                                                  dog         +1-542-296-2271                  NaN                  2
                                                                                  cat         +1-543-296-2271       +1-531-296-227                  3
                                                                                  
                                                                                  Formatting Phone number with +1 with pandas.Series.replace
                                                                                  Pythondot imgLines of Code : 7dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                   df['Contact phone number'] = df['Contact phone number'].str.replace(r'^(\d)(\d{3})(\d{3})(\d+)$', r'+1-\1-\2-\3-\4', regex=True)
                                                                                  
                                                                                  >>> df['Contact phone number']
                                                                                  falcon    +1-1-511-296-2271
                                                                                  dog                    None
                                                                                  cat       +1-1-531-296-2271
                                                                                  
                                                                                  Why does np.select not allow me to put in index above total length into choicelist?
                                                                                  Pythondot imgLines of Code : 7dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                  df['Emails'] = df['Emails'].explode().groupby(level=0).first()
                                                                                  
                                                                                  >>> df
                                                                                                 Emails  num_wings  num_specimen_seen
                                                                                  falcon    j@gmail.com          2                 10
                                                                                  dog     jzp@gmail.com          0                  2
                                                                                  
                                                                                  How can I group by index with index +1 in Pandas
                                                                                  Pythondot imgLines of Code : 2dot imgLicense : Strong Copyleft (CC BY-SA 4.0)
                                                                                  copy iconCopy
                                                                                  df['index'].diff().ne(1).cumsum()
                                                                                  
                                                                                  Community Discussions

                                                                                  Trending Discussions on falcon

                                                                                  Is there a way to show only the top 2/nth of a query after "group by" country? - bigquery SQL
                                                                                  chevron right
                                                                                  Store values in multidimensional array from BufferedReader
                                                                                  chevron right
                                                                                  C++ error: expected class member or base class name ...int e, int f, string pa, string direct, string distrib) : public Video
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                                                                                  How can I find the smallest difference between values within a group
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                                                                                  "If-element" does not react when calling included template
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                                                                                  Working through duplicates along rows in DataFrame and deleting all except the last one in Python Pandas
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                                                                                  Cannot interpret 'CategoricalDtype'
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                                                                                  To send mail Embedded with image in Lambda function using nodeJS
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                                                                                  create new column that telling the values why they are not selected on pandas?
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                                                                                  For loops output all the same value
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                                                                                  QUESTION

                                                                                  Is there a way to show only the top 2/nth of a query after "group by" country? - bigquery SQL
                                                                                  Asked 2021-Jun-10 at 03:57

                                                                                  I am doing a query on Google Big query, I have joined the 2 tables and created a new column "total gmv" using "SUM" to represent the total revenue, now I wanted to show only the top 2 vendors , GROUP BY country in my query.

                                                                                  I manage to show total_gmv group by COUNTRY and vendor_name, but I would like to filter to show top 2 vendors for each country only.

                                                                                  Code I used

                                                                                  SELECT Ord.country_name, vn.vendor_name, round(sum(Ord.gmv_local),2) as total_gmv FROM ORDERS as Ord
                                                                                  left join `primeval-falcon-306603.foodpanda_BI_Exercise.Vendors` as vn
                                                                                  ON Ord.vendor_id = vn.id
                                                                                  GROUP BY Ord.country_name, vn.vendor_name
                                                                                  ORDER BY Ord.country_name, total_gmv desc
                                                                                  
                                                                                  country_name vendor_name total_gmv Singapore A House 1583.25 Singapore B House 1236.35 Singapore C House 1153.27 Singapore D House 596.21 Hong Kong H House 1888.75 Hong Kong K House 755.78 Bangkok BB House 936.12

                                                                                  Is there a way to show only the top 2 vendors per country?

                                                                                  My target table should look like this, showing top 2 only

                                                                                  I am using Google bigquery and it seems the "TOP 2" function doesn't work?

                                                                                  country_name vendor_name total_gmv Singapore A House 1583.25 Singapore B House 1236.35 Hong Kong H House 1888.75 Hong Kong K House 755.78 Bangkok BB House 936.12

                                                                                  ANSWER

                                                                                  Answered 2021-Jun-10 at 02:56

                                                                                  Use ROW_NUMBER:

                                                                                  WITH cte AS (
                                                                                      SELECT Ord.country_name, vn.vendor_name, ROUND(SUM(Ord.gmv_local), 2) AS total_gmv,
                                                                                             ROW_NUMBER() OVER (PARTITION BY Ord.country_name
                                                                                                                ORDER BY SUM(Ord.gmv_local) DESC) rn
                                                                                      FROM ORDERS AS Ord
                                                                                      LEFT JOIN `primeval-falcon-306603.foodpanda_BI_Exercise.Vendors` AS vn
                                                                                          ON Ord.vendor_id = vn.id
                                                                                      GROUP BY Ord.country_name, vn.vendor_name
                                                                                  )
                                                                                  
                                                                                  SELECT country_name, vendor_name, total_gmv
                                                                                  FROM cte
                                                                                  WHERE rn <= 2
                                                                                  ORDER BY country_name, total_gmv DESC;
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67913960

                                                                                  QUESTION

                                                                                  Store values in multidimensional array from BufferedReader
                                                                                  Asked 2021-Jun-08 at 17:05

                                                                                  I have an assignment for a car rental system which requires the program to read the from a CSV file, which contains each car and its specifications.

                                                                                  I will need to store the values into an array, as I will need to count how many cars are left after one is hired, as well as calculate the cost which is listed for each car.

                                                                                  1,Mazda CX-9,7,Automatic,Premium,150
                                                                                  2,VW Golf,5,Automatic,Standard,59
                                                                                  3,Toyota Corolla,5,Automatic ,Premium,55
                                                                                  4,VW Tiguan,7,Automatic,Premium,110
                                                                                  5,Ford Falcon,5,Manual,Standard,60
                                                                                  

                                                                                  So far I've only been able to use line.split(",") to assign each column into a 1 dimensions array, which would output each number in index [0], each make in index[1], etc.

                                                                                  If I try line.split("\n") it assigns the whole file as is in index[0].

                                                                                  Please let me know what the best way to go about this would be.

                                                                                  I have been able to output the cars as I'd like to in code that I have not included here. The main problem is how to store the values appropriately.

                                                                                  public static void main(String[] args) throws FileNotFoundException, IOException {
                                                                                      String path = "carlist.csv";
                                                                                      String line = "";
                                                                                      long lines = 0;
                                                                                  
                                                                                      BufferedReader br = new BufferedReader(new FileReader(path));
                                                                                      while ((line = br.readLine()) != null) {
                                                                                          lines++;
                                                                                          String[] menu = line.split(",");
                                                                                          System.out.println(menu[0]);
                                                                                      }
                                                                                  }
                                                                                  

                                                                                  ANSWER

                                                                                  Answered 2021-Jun-06 at 06:01

                                                                                  Splitting by comma, is the right way, you just need to store the the array returned from the split function into an ArrayList or an array of Strings array, like this:

                                                                                  public static void main(String[] args) throws FileNotFoundException, IOException {
                                                                                      String path = "carlist.csv";
                                                                                      String line = "";
                                                                                      long lines = 0;
                                                                                      
                                                                                      BufferedReader br = new BufferedReader(new FileReader(path));
                                                                                      ArrayList list = new ArrayList<>();   
                                                                                      while ((line = br.readLine()) != null) {
                                                                                          lines++;
                                                                                          list.add(line.split(","));     
                                                                                          System.out.println(menu[0]);
                                                                                  
                                                                                      }
                                                                                  }
                                                                                  

                                                                                  Or like this:

                                                                                  public static void main(String[] args) throws FileNotFoundException, IOException {
                                                                                      String path = "carlist.csv";
                                                                                      String line = "";
                                                                                      long lines = 0;
                                                                                      
                                                                                      BufferedReader br = new BufferedReader(new FileReader(path));
                                                                                      String[][] cars = new String[100][6];  
                                                                                      while ((line = br.readLine()) != null) {
                                                                                          cars[lines++] = line.split(",");     
                                                                                          System.out.println(menu[0]);
                                                                                  
                                                                                      }
                                                                                  }
                                                                                  

                                                                                  Here, I have taken 100 as the maximum number of records that will be in a CSV file, and 6 is the maximum length of the array, that will be obtained after splitting by comma. Both of these can be modified according to your use-case. Now, you can get any car and its specific elements like this cars[0][3], or like this list.get(0)[3], depending on which implementation you use.

                                                                                  Source https://stackoverflow.com/questions/67856062

                                                                                  QUESTION

                                                                                  C++ error: expected class member or base class name ...int e, int f, string pa, string direct, string distrib) : public Video
                                                                                  Asked 2021-May-30 at 17:11

                                                                                  We think we have an issue with our inheritance, but we don't know how to solve it. (We have Class OOP)

                                                                                  Console prints...

                                                                                  clang++-7 -pthread -std=c++17 -o main Pelicula.cpp Serie.cpp Video.cpp main.cpp
                                                                                  Pelicula.cpp:7:115: error: expected class member or base class name
                                                                                    ...int e, int f, string pa, string direct, string distrib) : public Video(a...
                                                                                                                                                 ^
                                                                                  1 error generated.
                                                                                  Serie.cpp:7:83: error: expected class member or base class name
                                                                                    ...b, string c, int d, int e, int f, int ab, int cd) : public Video(a,b,c,d...
                                                                                                                                           ^
                                                                                  1 error generated.
                                                                                  exit status 1
                                                                                  

                                                                                  Using this code:

                                                                                  main.cpp

                                                                                  #include 
                                                                                  #include "Video.h"
                                                                                  #include "Serie.h"
                                                                                  #include "Pelicula.h"
                                                                                  using namespace std;
                                                                                  
                                                                                  int main(){
                                                                                    
                                                                                    Video *catalogo[2];
                                                                                    catalogo[0]= new Serie("Serie Narrativa","Stranger Things","Fantastico",8,50,120,25,4);
                                                                                    //vector[1]= new Serie("Falcon & The Winter Soldier",6,1);
                                                                                    catalogo[0]->muestraDatos();
                                                                                  
                                                                                  
                                                                                    int sel;
                                                                                    cout<<"+++++++++++++++\n\n=== Bienvenido a La plataforma SAJ ===\n\nElija las opciones\n1)Consultar peliculas y series\n2)Calificar"<>sel;
                                                                                    switch(sel){
                                                                                      case 1:
                                                                                        cout<<"CONSULTAR TOTAL DE VIDEO"<getTipoVideo()==busqueda)
                                                                                            busqueda=i;
                                                                                        }
                                                                                        automotor[busqueda];
                                                                                        */
                                                                                      break;
                                                                                      case 2:
                                                                                        cout<<"Calificar video"<

                                                                                  Video.h

                                                                                  #ifndef VIDEO_H
                                                                                  #define VIDEO_H
                                                                                  
                                                                                  #include 
                                                                                  using namespace std;
                                                                                  
                                                                                  class Video{
                                                                                    public:
                                                                                    Video(string a, string b, string c, int d, int e, int f);
                                                                                    void calificaVideo();
                                                                                    virtual void muestraDatos(); //agrega virtual luego Herencia
                                                                                  
                                                                                    string getTipoVideo();
                                                                                    
                                                                                    private:
                                                                                    string tipoVideo;
                                                                                    string nombreVideo;
                                                                                    string genero;
                                                                                    int calif;
                                                                                    int anioLanz;
                                                                                    int duracion;
                                                                                  };
                                                                                  
                                                                                  #endif
                                                                                  

                                                                                  Video.cpp

                                                                                  #include 
                                                                                  #include "Video.h"
                                                                                  //#include "Serie.h"
                                                                                  //#include "Pelicula.h"
                                                                                  using namespace std;
                                                                                  
                                                                                  Video::Video(string a, string b, string c, int d, int e, int f){
                                                                                    tipoVideo=a;
                                                                                    nombreVideo=b;
                                                                                    genero=c;
                                                                                    if(d<0){d=0;}
                                                                                    else if(d>10){d=10;}
                                                                                    calif=d;
                                                                                    anioLanz=e;
                                                                                    duracion=f;
                                                                                  }
                                                                                  void Video::muestraDatos(){
                                                                                    cout<<"IMPRIMIR REGISTRO\nTipo de video: "<<<"\nTítulo: "<<<"\nGenero: "<<<"\nCalificacion: "<<<"\nAño de lanzamiento: "<<<"\nDuracion: "<<>d;
                                                                                    if(d<0){d=0;}
                                                                                    else if(d>10){d=10;}
                                                                                    calif=d;
                                                                                    cout<<<" - Guardado!"<

                                                                                  Serie.h

                                                                                  #ifndef SERIE_H
                                                                                  #define SERIE_H
                                                                                  
                                                                                  #include 
                                                                                  #include "Video.h"
                                                                                  using namespace std;
                                                                                  
                                                                                  class Serie : public Video{
                                                                                    public:
                                                                                    Serie(string, string, string, int, int, int, int, int);
                                                                                    void muestraDatos();
                                                                                    private:
                                                                                    int episod_portemp;
                                                                                    int temporadas;
                                                                                  };
                                                                                  
                                                                                  #endif
                                                                                  

                                                                                  Serie.cpp

                                                                                  #include 
                                                                                  #include "Serie.h"
                                                                                  //#include "Video.h"
                                                                                  
                                                                                  using namespace std;
                                                                                  
                                                                                  Serie::Serie(string a, string b, string c, int d, int e, int f, int ab, int cd) : public Video(a,b,c,d,e,f){
                                                                                    episod_portemp=ab;
                                                                                    temporadas=cd;
                                                                                  }
                                                                                  
                                                                                  void Serie::muestraDatos(){
                                                                                    Video::muestraDatos();
                                                                                    cout<<"Episodios por temporada: "<<

                                                                                  Pelicula.h

                                                                                  #ifndef PELICULA_H
                                                                                  #define PELICULA_H
                                                                                  
                                                                                  #include 
                                                                                  #include "Video.h"
                                                                                  using namespace std;
                                                                                  
                                                                                  
                                                                                  class Pelicula : public Video{
                                                                                    public:
                                                                                    Pelicula(string, string, string, int, int, int, string, string, string);
                                                                                    void muestraDatos();
                                                                                    private:
                                                                                    string pais;
                                                                                    string director;
                                                                                    string distribuidor;
                                                                                  };
                                                                                  
                                                                                  #endif
                                                                                  

                                                                                  Pelicula.cpp

                                                                                  #include 
                                                                                  #include "Pelicula.h"
                                                                                  //#include "Video.h"
                                                                                  
                                                                                  using namespace std;
                                                                                  
                                                                                  Pelicula::Pelicula(string a, string b, string c, int d, int e, int f, string pa, string direct, string distrib) : public Video(a,b,c,d,e,f){
                                                                                    pais=pa;
                                                                                    director=direct;
                                                                                    distribuidor=distrib;
                                                                                  }
                                                                                  void Pelicula::muestraDatos(){
                                                                                    Video::muestraDatos();
                                                                                    cout<<"Pais: "<<

                                                                                  Befora causing this problem, printed another problem where it was "re-declarating" class Video, idk if this could be related.

                                                                                  ANSWER

                                                                                  Answered 2021-May-30 at 15:43

                                                                                  You declare inheritance as public. You do not declare constructors the same way.

                                                                                  In other words:

                                                                                  Serie::Serie(string a, string b, string c, int d, int e, int f, int ab, int cd) :  Video(a,b,c,d,e,f) { ...
                                                                                  }
                                                                                  

                                                                                  Note: To avoid extraneous copies, use const std::string& as your default argument type.

                                                                                  Source https://stackoverflow.com/questions/67762923

                                                                                  QUESTION

                                                                                  How can I find the smallest difference between values within a group
                                                                                  Asked 2021-May-26 at 14:19

                                                                                  EXAMPLE DF

                                                                                  df = pd.DataFrame({'Animal': ['Falcon', 'Falcon', 'Falcon',
                                                                                                                'Parrot', 'Parrot', 'Parrot'],
                                                                                                     'Max Speed': [380., 370., 25., 24., 26., 29.]})
                                                                                  

                                                                                  DESIRED OUTPUT

                                                                                  2 (because the smallest difference is between 24 and 26 of Parrot)
                                                                                  

                                                                                  EVEN BETTER (so I can check)

                                                                                  'Parrot, 2'
                                                                                  

                                                                                  WHAT I WAS THINKING

                                                                                  'I need to sort by animal and max speed, and then a window function, but there must be a better solution...'

                                                                                  ANSWER

                                                                                  Answered 2021-May-26 at 14:06

                                                                                  We can check groupby with diff

                                                                                  df['new'] = df.sort_values('Max Speed').groupby('Animal')['Max Speed'].diff().abs()
                                                                                  out = df[df.new==df.new.min()]
                                                                                  Out[249]: 
                                                                                     Animal  Max Speed  new
                                                                                  4  Parrot       26.0  2.0
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67706413

                                                                                  QUESTION

                                                                                  "If-element" does not react when calling included template
                                                                                  Asked 2021-May-21 at 07:21

                                                                                  I am looking to build a simple logic to let user define which templates that should be called upon. The code illustrates a minimized example. The setup is very useful when having many templates, e.g. the output I am building is about 2.600 lines of XHTML code. Then it is very good being able to exclude several templates to focus on only some of the templates.

                                                                                  I have created above setup (previously) successfully having XML as source file and modularized code. I suspect it is my setup with having JSON as source file and the adaption of code that causes the problem.

                                                                                  Below code should allow the user to switch variable "build-with-books" from 0 to 1, and if set to 1, the "if" element should call the included template.

                                                                                  I am sure that there are many "smarter" way of solving my needs. Currently I am just looking to understand why my code does not follow the wanted logics of switching on/off the build of elements.

                                                                                  XSLT fiddle is down so I just paste my code below:

                                                                                  data:

                                                                                  
                                                                                  {
                                                                                    "books": {
                                                                                      "Wonderland": 43
                                                                                    },
                                                                                    "beverage": {
                                                                                      "Falcon": 12
                                                                                    }
                                                                                  }
                                                                                  
                                                                                  

                                                                                  principal.xsl:

                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                    
                                                                                  
                                                                                    
                                                                                    
                                                                                  
                                                                                    
                                                                                    
                                                                                  
                                                                                    
                                                                                    0
                                                                                  
                                                                                    
                                                                                    
                                                                                      Adventure
                                                                                    
                                                                                  
                                                                                    
                                                                                  
                                                                                    
                                                                                  
                                                                                        
                                                                                        
                                                                                          
                                                                                        
                                                                                  
                                                                                            
                                                                                        
                                                                                          
                                                                                        
                                                                                  
                                                                                    
                                                                                  
                                                                                  
                                                                                  

                                                                                  Supporting module: books.xsl

                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                  
                                                                                      {.}
                                                                                  
                                                                                  
                                                                                  
                                                                                  

                                                                                  Result:

                                                                                  
                                                                                  
                                                                                     43
                                                                                  
                                                                                  

                                                                                  Expected result if variable "build-with-books" set to 0

                                                                                  
                                                                                  
                                                                                  
                                                                                  

                                                                                  Expected result if variable "build-with-books" set to 1

                                                                                  
                                                                                  
                                                                                     43
                                                                                  
                                                                                  

                                                                                  ANSWER

                                                                                  Answered 2021-May-21 at 07:21

                                                                                  Start

                                                                                  Delete this part from principal.xsl: (call-template uses the current context and that is still your match on data)

                                                                                        
                                                                                    
                                                                                      
                                                                                    
                                                                                  

                                                                                  And remove the @name attribute from

                                                                                  
                                                                                  

                                                                                  Option: 1

                                                                                  Change match template in books.xls to look like this (it will use your global $build-with-books directly)

                                                                                    
                                                                                      {.}
                                                                                    
                                                                                  

                                                                                  Option: 2

                                                                                  Make use of xsl:next-match in your principal.xsl: (it will first use the template with a higher priority where it checkes that global $build-with-books)

                                                                                  Add this:

                                                                                    
                                                                                      
                                                                                        
                                                                                      
                                                                                    
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67627872

                                                                                  QUESTION

                                                                                  Working through duplicates along rows in DataFrame and deleting all except the last one in Python Pandas
                                                                                  Asked 2021-May-18 at 04:44

                                                                                  I am miserably stuck at Pandas Data Cleaning. I have made a very simple example to demonstrate my problem. For each row, I want to delete/alter the duplicate and keep the last one. Currently, my DataFrame is 'animals'. And I want it to be the DataFrame 'animals_clean'

                                                                                  Imagine this DataFrame. You can see duplicates along axis=0, e.g. 'cat' is repeated in row 0

                                                                                  list_of_animals = [['cat','dog','monkey','sparrow', 'cat'],['cow', 'eagle','rat', 'eagle', 'owl'],['deer', 'horse', 'goat', 'falcon', 'falcon']]
                                                                                  animals = pd.DataFrame(list_of_animals)
                                                                                  

                                                                                  How it looks:

                                                                                  This is the result I want. You can see the duplicates in each row is marked 'X' keeping the last one.

                                                                                  list_of_animals_clean = [['X','dog','monkey','sparrow', 'cat'],['cow', 'X','rat', 'eagle', 'owl'], ['deer', 'horse', 'goat', 'X', 'falcon']]
                                                                                  animals_clean = pd.DataFrame(list_of_animals_clean)
                                                                                  

                                                                                  Should look like:

                                                                                  ANSWER

                                                                                  Answered 2021-May-17 at 23:52

                                                                                  Try apply + mask + duplicated with keep='last':

                                                                                  import pandas as pd
                                                                                  
                                                                                  list_of_animals = [['cat', 'dog', 'monkey', 'sparrow', 'cat'],
                                                                                                     ['cow', 'eagle', 'rat', 'eagle', 'owl'],
                                                                                                     ['deer', 'horse', 'goat', 'falcon', 'falcon']]
                                                                                  animals = pd.DataFrame(list_of_animals)
                                                                                  
                                                                                  animals = animals.apply(
                                                                                      lambda s: s.mask(s.duplicated(keep='last'), 'x'),
                                                                                      axis=1
                                                                                  )
                                                                                  
                                                                                  print(animals)
                                                                                  

                                                                                  Output:

                                                                                        0      1       2        3       4
                                                                                  0     x    dog  monkey  sparrow     cat
                                                                                  1   cow      x     rat    eagle     owl
                                                                                  2  deer  horse    goat        x  falcon
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67578244

                                                                                  QUESTION

                                                                                  Cannot interpret 'CategoricalDtype'
                                                                                  Asked 2021-May-14 at 02:12

                                                                                  I would like to split variables into the different types. For example:

                                                                                  Tweets   ID    Registration Date   num_unique_words   photo_profile  range
                                                                                  object  int64  object              float64             int64         category       
                                                                                  

                                                                                  What I did is:

                                                                                  type_dct = {str(k): list(v) for k, v in df.groupby(df.dtypes, axis=1)} but I have got a TypeError:

                                                                                  TypeError: Cannot interpret 'CategoricalDtype(categories=['<5',
                                                                                   '>=5'], ordered=True)' as a data type
                                                                                  

                                                                                  range can take two values: '<5' and '>=5'.

                                                                                  I hope you can help to handle this error.

                                                                                  df = pd.DataFrame({'Tweets': ['Tweet 1 from user 1', 'Tweet 2 from user 1', 
                                                                                                                'Tweet 1 from user 3', 'Tweet 10 from user 1'], 
                                                                                                     'ID': [124, 124, 12, 124], 
                                                                                                     'Registration Date': ['2020-12-02', '2020-11-21', 
                                                                                                                           '2020-12-02', '2020-12-02'], 
                                                                                                     'num_unique_words': [41, 42, 12, 69], 
                                                                                                     'photo_profile': [1, 0, 1, 1], 
                                                                                                     'range': ['<5', '<5', '>=5', '<5']}, 
                                                                                                    index=['falcon', 'dog', 'spider', 'fish'])
                                                                                  

                                                                                  ANSWER

                                                                                  Answered 2021-May-14 at 02:12
                                                                                  Update:

                                                                                  That was surprisingly more complicated that I thought it would be, but here is a work around using list comprehension:

                                                                                  type_dct = {str(k): list(v) for k, v in df.groupby([i.name for i in df.dtypes], axis=1)}
                                                                                  

                                                                                  Output:

                                                                                  {'category': ['range'],
                                                                                   'int64': ['ID', 'num_unique_words', 'photo_profile'],
                                                                                   'object': ['Tweets', 'Registration Date']}
                                                                                  

                                                                                  pd.CategorialDtypes by itself doesn't work well in the groupby, we must use the name attribute of that object.

                                                                                  Use pd.DataFrame.select_dtypes

                                                                                  Example from docs.

                                                                                  df = pd.DataFrame({'a': [1, 2] * 3,
                                                                                                     'b': [True, False] * 3,
                                                                                                     'c': [1.0, 2.0] * 3})
                                                                                  df
                                                                                          a      b  c
                                                                                  0       1   True  1.0
                                                                                  1       2  False  2.0
                                                                                  2       1   True  1.0
                                                                                  3       2  False  2.0
                                                                                  4       1   True  1.0
                                                                                  5       2  False  2.0
                                                                                  df.select_dtypes(include='bool')
                                                                                     b
                                                                                  0  True
                                                                                  1  False
                                                                                  2  True
                                                                                  3  False
                                                                                  4  True
                                                                                  5  False
                                                                                  df.select_dtypes(include=['float64'])
                                                                                     c
                                                                                  0  1.0
                                                                                  1  2.0
                                                                                  2  1.0
                                                                                  3  2.0
                                                                                  4  1.0
                                                                                  5  2.0
                                                                                  df.select_dtypes(exclude=['int64'])
                                                                                         b    c
                                                                                  0   True  1.0
                                                                                  1  False  2.0
                                                                                  2   True  1.0
                                                                                  3  False  2.0
                                                                                  4   True  1.0
                                                                                  5  False  2.0
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67525063

                                                                                  QUESTION

                                                                                  To send mail Embedded with image in Lambda function using nodeJS
                                                                                  Asked 2021-May-13 at 04:06

                                                                                  I have created lambda function in AWS which send mail to various recipients. I need to add company logo/banner at bottom of the mail. Below is the code

                                                                                  var nodemailer = require('nodemailer');
                                                                                  var transporter = nodemailer.createTransport({
                                                                                  host: 'xxxxxx.xxxx.com',
                                                                                  port:587,
                                                                                  secure : true
                                                                                  });
                                                                                  var text = 'xxxxxxxxxx ';
                                                                                  var mailOptions = {
                                                                                      from: 'donotreplyhere@xxxx.com',
                                                                                      to: 'skumar@xxx.com',
                                                                                      subject: 'Test subject',
                                                                                      html: text
                                                                                  };
                                                                                  exports.handler = async (event, context, callback) => {
                                                                                   return new Promise((resolve,reject)=>{
                                                                                  transporter.sendMail(mailOptions, function (error, info) {
                                                                                  if (error) {
                                                                                      console.log("Error " +error);
                                                                                     }   else {
                                                                                          console.log('Email sent: ' + info.response);
                                                                                       }
                                                                                      });
                                                                                  
                                                                                   });
                                                                                  }
                                                                                  

                                                                                  I am receiving the mail but image is not being displayed getting error : The linked image can't be displayed.

                                                                                  I also tried with s3 url by uploading images in s3 bucket but using its url like

                                                                                  ';
                                                                                  

                                                                                  But this didn't worked, may be because its not public and i can't make it public.

                                                                                  Any other way that i can use to accomplish this task.

                                                                                  Thank for looking

                                                                                  ANSWER

                                                                                  Answered 2021-May-13 at 04:06

                                                                                  Here are some of the options:

                                                                                  • If you can use CloudFront in-front of S3 and use the CloudFront URL for the static content, do so. Here is more information.
                                                                                  • You can also host the static content on any publicly accessible website e.g. on Github pages which is also a CDN for free.
                                                                                  • You can use Data URLs in place of the images. You must convert the images to the Base64 encoded version and use them directly in the HTML.
                                                                                  • You can use SVG as an image. You must convert your existing images to SVG and directly embed the contents in the HTML.

                                                                                  Source https://stackoverflow.com/questions/67193261

                                                                                  QUESTION

                                                                                  create new column that telling the values why they are not selected on pandas?
                                                                                  Asked 2021-May-03 at 00:45

                                                                                  Input

                                                                                  df=pd.DataFrame({'Name':['JOHN','ALLEN','BOB','NIKI','CHARLIE','CHANG'],
                                                                                                'Age':[35,42,63,29,47,51],
                                                                                                'Salary_in_1000':[100,93,78,120,64,115],
                                                                                               'FT_Team':['STEELERS','SEAHAWKS','FALCONS','FALCONS','PATRIOTS','STEELERS']})
                                                                                  
                                                                                  
                                                                                  n1=(df['Age']< 60)
                                                                                  n2=(df['Salary_in_1000']>=100) 
                                                                                  n3=(df['FT_Team'].str.startswith('S'))
                                                                                  

                                                                                  Using these conditions to select, it will return JOHN and CHANG.

                                                                                  Goal

                                                                                  I want to create dataframe where data is not selected and a new column which returns which conditions is not expected. For example,

                                                                                  * ALLEN: n1, n2
                                                                                  * BOB: n2,n3
                                                                                  * NIKI: n3
                                                                                  * CHANG: n2,n3
                                                                                  

                                                                                  The new column name is reason. The value is the condition variable and the type is string.

                                                                                  Try

                                                                                  I have to try each condition and record each variable violates which rules by hand.

                                                                                  ANSWER

                                                                                  Answered 2021-May-03 at 00:43

                                                                                  If you put the conditions into a dictionary, you can automatically assign() an arbitrary number of conditions as columns:

                                                                                  conditions = dict(
                                                                                      n1 = (df['Age'] < 60),
                                                                                      n2 = (df['Salary_in_1000'] >= 100),
                                                                                      n3 = (df['FT_Team'].str.startswith('S')),
                                                                                  )
                                                                                  df = df.assign(**{key: value for key, value in conditions.items()})
                                                                                  
                                                                                  #       Name  Age  Salary_in_1000   FT_Team     n1     n2     n3
                                                                                  # 0     JOHN   35             100  STEELERS   True   True   True
                                                                                  # 1    ALLEN   42              93  SEAHAWKS   True  False   True
                                                                                  # 2      BOB   63              78   FALCONS  False  False  False
                                                                                  # 3     NIKI   29             120   FALCONS   True   True  False
                                                                                  # 4  CHARLIE   47              64  PATRIOTS   True  False  False
                                                                                  # 5    CHANG   51             115  STEELERS   True   True   True
                                                                                  

                                                                                  Then create reason based on which of those conditions (last n columns) are False:

                                                                                  n = len(conditions)
                                                                                  df['reason'] = df.apply(lambda x: x[-n:].loc[x[-n:] == False].index.values, axis=1)
                                                                                  df = df.drop(columns=conditions.keys())
                                                                                  
                                                                                  #       Name  Age  Salary_in_1000   FT_Team        reason
                                                                                  # 0     JOHN   35             100  STEELERS            []
                                                                                  # 1    ALLEN   42              93  SEAHAWKS          [n2]
                                                                                  # 2      BOB   63              78   FALCONS  [n1, n2, n3]
                                                                                  # 3     NIKI   29             120   FALCONS          [n3]
                                                                                  # 4  CHARLIE   47              64  PATRIOTS      [n2, n3]
                                                                                  # 5    CHANG   51             115  STEELERS            []
                                                                                  

                                                                                  Source https://stackoverflow.com/questions/67362002

                                                                                  QUESTION

                                                                                  For loops output all the same value
                                                                                  Asked 2021-Apr-26 at 03:12

                                                                                  So I have a json list and use two input request.args.get('sport') and request.args.get('team') to find those values in my list. If the value is found I want to output more info on the team and sport.

                                                                                  This is what I tried to do:

                                                                                  for a_team in scores_list['scores']:
                                                                                      if a_team['sport'].lower() == request.args.get('sport').lower() \
                                                                                              and a_team['team'].lower() == request.args.get('team').lower():
                                                                                          teams_list = []
                                                                                          for a_team['team'] in scores_list['scores']:
                                                                                              teams_list.append("{} ({}) ({}) {} ({}) - ({}) {}".format(a_team['full_name'], a_team['date'],
                                                                                                                                                        a_team['sport'], a_team['home_name'],
                                                                                                                                                        a_team['home_score'], a_team['away_score'],
                                                                                                                                                        a_team['away_name']))
                                                                                  

                                                                                  The problem is that this way is outputting the same set of values over. I want to output all different games with the the team from request.args.get('team'). I am new to python and I have searched everyone but couldn't find an answer.

                                                                                  Below is a sample of my json file:

                                                                                   {
                                                                                    "scores": [
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "packers",
                                                                                        "full_name": "Green Bay Packers",
                                                                                        "week": "15-2020",
                                                                                        "boxscore": "202012190gnb",
                                                                                        "away_name": "Carolina Panthers",
                                                                                        "away_abbr": "car",
                                                                                        "away_score": 16,
                                                                                        "home_name": "Green Bay Packers",
                                                                                        "home_abbr": "gnb",
                                                                                        "home_score": 24,
                                                                                        "winning_name": "Green Bay Packers",
                                                                                        "winning_abbr": "gnb",
                                                                                        "losing_name": "Carolina Panthers",
                                                                                        "losing_abbr": "car"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "packers",
                                                                                        "full_name": "Green Bay Packers",
                                                                                        "week": "19-2020",
                                                                                        "boxscore": "202101160gnb",
                                                                                        "away_name": "Los Angeles Rams",
                                                                                        "away_abbr": "ram",
                                                                                        "away_score": 18,
                                                                                        "home_name": "Green Bay Packers",
                                                                                        "home_abbr": "gnb",
                                                                                        "home_score": 32,
                                                                                        "winning_name": "Green Bay Packers",
                                                                                        "winning_abbr": "gnb",
                                                                                        "losing_name": "Los Angeles Rams",
                                                                                        "losing_abbr": "ram"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "packers",
                                                                                        "full_name": "Green Bay Packers",
                                                                                        "week": "20-2020",
                                                                                        "boxscore": "202101240gnb",
                                                                                        "away_name": "Tampa Bay Buccaneers",
                                                                                        "away_abbr": "tam",
                                                                                        "away_score": 31,
                                                                                        "home_name": "Green Bay Packers",
                                                                                        "home_abbr": "gnb",
                                                                                        "home_score": 26,
                                                                                        "winning_name": "Tampa Bay Buccaneers",
                                                                                        "winning_abbr": "tam",
                                                                                        "losing_name": "Green Bay Packers",
                                                                                        "losing_abbr": "gnb"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "chiefs",
                                                                                        "full_name": "Kansas City Chiefs",
                                                                                        "week": "16-2020",
                                                                                        "boxscore": "202012270kan",
                                                                                        "away_name": "Atlanta Falcons",
                                                                                        "away_abbr": "atl",
                                                                                        "away_score": 14,
                                                                                        "home_name": "Kansas City Chiefs",
                                                                                        "home_abbr": "kan",
                                                                                        "home_score": 17,
                                                                                        "winning_name": "Kansas City Chiefs",
                                                                                        "winning_abbr": "kan",
                                                                                        "losing_name": "Atlanta Falcons",
                                                                                        "losing_abbr": "atl"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "chiefs",
                                                                                        "full_name": "Kansas City Chiefs",
                                                                                        "week": "17-2020",
                                                                                        "boxscore": "202101030kan",
                                                                                        "away_name": "Los Angeles Chargers",
                                                                                        "away_abbr": "sdg",
                                                                                        "away_score": 38,
                                                                                        "home_name": "Kansas City Chiefs",
                                                                                        "home_abbr": "kan",
                                                                                        "home_score": 21,
                                                                                        "winning_name": "Los Angeles Chargers",
                                                                                        "winning_abbr": "sdg",
                                                                                        "losing_name": "Kansas City Chiefs",
                                                                                        "losing_abbr": "kan"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "chiefs",
                                                                                        "full_name": "Kansas City Chiefs",
                                                                                        "week": "19-2020",
                                                                                        "boxscore": "202101170kan",
                                                                                        "away_name": "Cleveland Browns",
                                                                                        "away_abbr": "cle",
                                                                                        "away_score": 17,
                                                                                        "home_name": "Kansas City Chiefs",
                                                                                        "home_abbr": "kan",
                                                                                        "home_score": 22,
                                                                                        "winning_name": "Kansas City Chiefs",
                                                                                        "winning_abbr": "kan",
                                                                                        "losing_name": "Cleveland Browns",
                                                                                        "losing_abbr": "cle"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "chiefs",
                                                                                        "full_name": "Kansas City Chiefs",
                                                                                        "week": "19-2020",
                                                                                        "boxscore": "202101240kan",
                                                                                        "away_name": "Buffalo Bills",
                                                                                        "away_abbr": "buf",
                                                                                        "away_score": 24,
                                                                                        "home_name": "Kansas City Chiefs",
                                                                                        "home_abbr": "kan",
                                                                                        "home_score": 38,
                                                                                        "winning_name": "Kansas City Chiefs",
                                                                                        "winning_abbr": "kan",
                                                                                        "losing_name": "Buffalo Bills",
                                                                                        "losing_abbr": "buf"
                                                                                      },
                                                                                      {
                                                                                        "sport": "football",
                                                                                        "team": "buccaneers",
                                                                                        "full_name": "Tampa Bay Buccaneers",
                                                                                        "week": "21-2020",
                                                                                        "boxscore": "202102070tam",
                                                                                        "away_name": "Kansas City Chiefs",
                                                                                        "away_abbr": "kan",
                                                                                        "away_score": 9,
                                                                                        "home_name": "Tampa Bay Buccaneers",
                                                                                        "home_abbr": "tam",
                                                                                        "home_score": 31,
                                                                                        "winning_name": "Tampa Bay Buccaneers",
                                                                                        "winning_abbr": "tam",
                                                                                        "losing_name": "Kansas City Chiefs",
                                                                                        "losing_abbr": "kan"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "giants",
                                                                                        "full_name": "San Francisco Giants",
                                                                                        "date": "7-23-2020",
                                                                                        "boxscore": "LAN/LAN202007230",
                                                                                        "away_name": "San Francisco Giants",
                                                                                        "away_abbr": "SFG",
                                                                                        "away_score": 1,
                                                                                        "home_name": "Los Angeles Dodgers",
                                                                                        "home_abbr": "LAD",
                                                                                        "home_score": 8,
                                                                                        "winning_name": "Los Angeles Dodgers",
                                                                                        "winning_abbr": "LAD",
                                                                                        "losing_name": "San Francisco Giants",
                                                                                        "losing_abbr": "SFG"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "giants",
                                                                                        "full_name": "San Francisco Giants",
                                                                                        "date": "7-24-2020",
                                                                                        "boxscore": "LAN/LAN202007240",
                                                                                        "away_name": "San Francisco Giants",
                                                                                        "away_abbr": "SFG",
                                                                                        "away_score": 1,
                                                                                        "home_name": "Los Angeles Dodgers",
                                                                                        "home_abbr": "LAD",
                                                                                        "home_score": 9,
                                                                                        "winning_name": "Los Angeles Dodgers",
                                                                                        "winning_abbr": "LAD",
                                                                                        "losing_name": "San Francisco Giants",
                                                                                        "losing_abbr": "SFG"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "giants",
                                                                                        "full_name": "San Francisco Giants",
                                                                                        "date": "7-25-2020",
                                                                                        "boxscore": "LAN/LAN202007250",
                                                                                        "away_name": "San Francisco Giants",
                                                                                        "away_abbr": "SFG",
                                                                                        "away_score": 5,
                                                                                        "home_name": "Los Angeles Dodgers",
                                                                                        "home_abbr": "LAD",
                                                                                        "home_score": 4,
                                                                                        "winning_name": "San Francisco Giants",
                                                                                        "winning_abbr": "SFG",
                                                                                        "losing_name": "Los Angeles Dodgers",
                                                                                        "losing_abbr": "LAD"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "giants",
                                                                                        "full_name": "San Francisco Giants",
                                                                                        "date": "8-5-2020",
                                                                                        "boxscore": "COL/COL202008050",
                                                                                        "away_name": "San Francisco Giants",
                                                                                        "away_abbr": "SFG",
                                                                                        "away_score": 4,
                                                                                        "home_name": "Colorado Rockies",
                                                                                        "home_abbr": "COL",
                                                                                        "home_score": 3,
                                                                                        "winning_name": "San Francisco Giants",
                                                                                        "winning_abbr": "SFG",
                                                                                        "losing_name": "Colorado Rockies",
                                                                                        "losing_abbr": "COL"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "giants",
                                                                                        "full_name": "San Francisco Giants",
                                                                                        "date": "8-6-2020",
                                                                                        "boxscore": "COL/COL202008060",
                                                                                        "away_name": "San Francisco Giants",
                                                                                        "away_abbr": "SFG",
                                                                                        "away_score": 4,
                                                                                        "home_name": "Colorado Rockies",
                                                                                        "home_abbr": "COL",
                                                                                        "home_score": 6,
                                                                                        "winning_name": "Colorado Rockies",
                                                                                        "winning_abbr": "COL",
                                                                                        "losing_name": "San Francisco Giants",
                                                                                        "losing_abbr": "SFG"
                                                                                      },
                                                                                      {
                                                                                        "sport": "baseball",
                                                                                        "team": "rays",
                                                                                        "full_name": "Tampa Bay Rays",
                                                                                        "date": "10-27-2020",
                                                                                        "boxscore": "LAN/LAN202010270",
                                                                                        "away_name": "Tampa Bay Rays",
                                                                                        "away_abbr": "TBR",
                                                                                        "away_score": 1,
                                                                                        "home_name": "Los Angeles Dodgers",
                                                                                        "home_abbr": "LAD",
                                                                                        "home_score": 3,
                                                                                        "winning_name": "Los Angeles Dodgers",
                                                                                        "winning_abbr": "LAD",
                                                                                        "losing_name": "Tampa Bay Rays",
                                                                                        "losing_abbr": "TBR"
                                                                                      }
                                                                                    ]
                                                                                  }
                                                                                  

                                                                                  ANSWER

                                                                                  Answered 2021-Apr-25 at 17:58
                                                                                          for team in scores_list['scores']:
                                                                                              teams_list.append("{} ({}) ({}) {} ({}) - ({}) {}".format(team['full_name'], team['date'],
                                                                                                                                                        team['sport'], team['home_name'],
                                                                                                                                                        team['home_score'], team['away_score'],
                                                                                                                                                        team['away_name']))
                                                                                  

                                                                                  You're iterating over scores_list['scores'] at two locations in your source code:

                                                                                  for a_team in scores_list['scores']:
                                                                                              # ^^^^^^^^^^^^^^^^^^^^^ here
                                                                                      if a_team['sport'].lower() == request.args.get('sport').lower() \
                                                                                              and a_team['team'].lower() == request.args.get('team').lower():
                                                                                          teams_list = []
                                                                                          for a_team['team'] in scores_list['scores']:
                                                                                                              # ^^^^^^^^^^^^^^^^^^^^^ and here
                                                                                              teams_list.append("{} ({}) ({}) {} ({}) - ({}) {}".format(a_team['full_name'], a_team['date'],
                                                                                                                                                        a_team['sport'], a_team['home_name'],
                                                                                                                                                        a_team['home_score'], a_team['away_score'],
                                                                                                                                                        a_team['away_name']))
                                                                                  

                                                                                  This is probably not what you want. When the if is true you already have an a_team in your hand you're interested in and you can just use it:

                                                                                  for a_team in scores_list['scores']:
                                                                                      if a_team['sport'].lower() == request.args.get('sport').lower() \
                                                                                              and a_team['team'].lower() == request.args.get('team').lower():
                                                                                          teams_list = []
                                                                                          teams_list.append("{} ({}) ({}) {} ({}) - ({}) {}".format(a_team['full_name'], a_team['date'],
                                                                                                                                                    a_team['sport'], a_team['home_name'],
                                                                                                                                                    a_team['home_score'], a_team['away_score'],
                                                                                                                                                    a_team['away_name']))
                                                                                  

                                                                                  Now you just need to figure out where you want to put teams_list = []. Probably before the for-loop starts.

                                                                                  Source https://stackoverflow.com/questions/67256025

                                                                                  Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                                                                                  Vulnerabilities

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                                                                                  Install falcon

                                                                                  You can install using 'pip install falcon' or download it from GitHub, PyPI.
                                                                                  You can use falcon like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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