How to do validation for Two or more CSV file in python flask

-1

Please Before Dislike this Question ask me what you don't understand Hello Guys i have data generation program which will do lots of computation so i cannot paste my whole program here so only talking about my program All the computation of the program starts with reading the file so when i'm selecting multiple CSV file in web page in "choose file" option i need to validate the columns numbers(should be same) of the all csv file and columns headers name should also match.. program i have written is like this:

from flask import Flask, render_template

import os

import csv

import pandas as pd

import numpy as np

app = Flask(__name__)



APP_ROOT = os.path.dirname(os.path.abspath(__file__))

@app.route("/")

def index():

    print("Loading the root file")

    return render_template("upload.html")

@app.route("/upload", methods=['POST'])

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)



        if not os.path.isdir(target):

            os.mkdir(target)



    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)



            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            global tempFile

            tempFile = destination

            print("tempFile - " + tempFile)

    return redirect("/compute", )

def compute():

    readerForRowCheck = pd.read_csv(tempFile)

        for row in readerForRowCheck:

            if (len(row) != 8):

                return render_template("Incomplete.html")



            headerColumn1 = row[0];

            headerColumn2 = row[1];

            headerColumn3 = row[2];

            headerColumn4 = row[3];

            headerColumn5 = row[4];

            headerColumn6 = row[5];

            headerColumn7 = row[6];

            headerColumn8 = row[7];



            if (headerColumn1 != "Asset_Id") or (headerColumn2 != "Asset Family") 

                or (headerColumn3 != "Asset Name") or (headerColumn4 != "Location")or (headerColumn5 != "Asset Component") 

                or (headerColumn6 != "Keywords") or (headerColumn7 != "Conditions") or (headerColumn8 != "Parts") :

                    return render_template("incomplete.html")

.....................................so on to then it will go to perform other task

HTML program:

html

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="utf-8">

    <title> upload </title>

</head>

<body>

<div class="container">

    <h1>Large Data Generation</h1> 

<form id = "upload-form" action="{{ url_for('upload') }}" method="POST" enctype="multipart/form-data">

        <div id="file-selector">

            <p> 

                <strong>Source File: </strong>

                <input id="source_fileName" type="file" name="source_fileName" accept="csv/*" multiple />

            </p> 

        </div>

    <input type="submit" value="Generate Data" id="upload-button"  >

</form>

</div>

</body>

Note:**I have only given lines of code which important otherwise its contain lots of code **Here i'm getting that how should i validate the csv file on the columns numbers and name should be same i know my validation for reading csv file is not correct that why i'm here please Help me.....thanks

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

add a comment |

-1

from flask import Flask, render_template

import os

import csv

import pandas as pd

import numpy as np

app = Flask(__name__)



APP_ROOT = os.path.dirname(os.path.abspath(__file__))

@app.route("/")

def index():

    print("Loading the root file")

    return render_template("upload.html")

@app.route("/upload", methods=['POST'])

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)



        if not os.path.isdir(target):

            os.mkdir(target)



    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)



            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            global tempFile

            tempFile = destination

            print("tempFile - " + tempFile)

    return redirect("/compute", )

def compute():

    readerForRowCheck = pd.read_csv(tempFile)

        for row in readerForRowCheck:

            if (len(row) != 8):

                return render_template("Incomplete.html")



            headerColumn1 = row[0];

            headerColumn2 = row[1];

            headerColumn3 = row[2];

            headerColumn4 = row[3];

            headerColumn5 = row[4];

            headerColumn6 = row[5];

            headerColumn7 = row[6];

            headerColumn8 = row[7];



            if (headerColumn1 != "Asset_Id") or (headerColumn2 != "Asset Family") 

                or (headerColumn3 != "Asset Name") or (headerColumn4 != "Location")or (headerColumn5 != "Asset Component") 

                or (headerColumn6 != "Keywords") or (headerColumn7 != "Conditions") or (headerColumn8 != "Parts") :

                    return render_template("incomplete.html")

.....................................so on to then it will go to perform other task

HTML program:

html

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="utf-8">

    <title> upload </title>

</head>

<body>

<div class="container">

    <h1>Large Data Generation</h1> 

<form id = "upload-form" action="{{ url_for('upload') }}" method="POST" enctype="multipart/form-data">

        <div id="file-selector">

            <p> 

                <strong>Source File: </strong>

                <input id="source_fileName" type="file" name="source_fileName" accept="csv/*" multiple />

            </p> 

        </div>

    <input type="submit" value="Generate Data" id="upload-button"  >

</form>

</div>

</body>

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

add a comment |

-1

from flask import Flask, render_template

import os

import csv

import pandas as pd

import numpy as np

app = Flask(__name__)



APP_ROOT = os.path.dirname(os.path.abspath(__file__))

@app.route("/")

def index():

    print("Loading the root file")

    return render_template("upload.html")

@app.route("/upload", methods=['POST'])

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)



        if not os.path.isdir(target):

            os.mkdir(target)



    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)



            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            global tempFile

            tempFile = destination

            print("tempFile - " + tempFile)

    return redirect("/compute", )

def compute():

    readerForRowCheck = pd.read_csv(tempFile)

        for row in readerForRowCheck:

            if (len(row) != 8):

                return render_template("Incomplete.html")



            headerColumn1 = row[0];

            headerColumn2 = row[1];

            headerColumn3 = row[2];

            headerColumn4 = row[3];

            headerColumn5 = row[4];

            headerColumn6 = row[5];

            headerColumn7 = row[6];

            headerColumn8 = row[7];



            if (headerColumn1 != "Asset_Id") or (headerColumn2 != "Asset Family") 

                or (headerColumn3 != "Asset Name") or (headerColumn4 != "Location")or (headerColumn5 != "Asset Component") 

                or (headerColumn6 != "Keywords") or (headerColumn7 != "Conditions") or (headerColumn8 != "Parts") :

                    return render_template("incomplete.html")

.....................................so on to then it will go to perform other task

HTML program:

html

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="utf-8">

    <title> upload </title>

</head>

<body>

<div class="container">

    <h1>Large Data Generation</h1> 

<form id = "upload-form" action="{{ url_for('upload') }}" method="POST" enctype="multipart/form-data">

        <div id="file-selector">

            <p> 

                <strong>Source File: </strong>

                <input id="source_fileName" type="file" name="source_fileName" accept="csv/*" multiple />

            </p> 

        </div>

    <input type="submit" value="Generate Data" id="upload-button"  >

</form>

</div>

</body>

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

from flask import Flask, render_template

import os

import csv

import pandas as pd

import numpy as np

app = Flask(__name__)



APP_ROOT = os.path.dirname(os.path.abspath(__file__))

@app.route("/")

def index():

    print("Loading the root file")

    return render_template("upload.html")

@app.route("/upload", methods=['POST'])

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)



        if not os.path.isdir(target):

            os.mkdir(target)



    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)



            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            global tempFile

            tempFile = destination

            print("tempFile - " + tempFile)

    return redirect("/compute", )

def compute():

    readerForRowCheck = pd.read_csv(tempFile)

        for row in readerForRowCheck:

            if (len(row) != 8):

                return render_template("Incomplete.html")



            headerColumn1 = row[0];

            headerColumn2 = row[1];

            headerColumn3 = row[2];

            headerColumn4 = row[3];

            headerColumn5 = row[4];

            headerColumn6 = row[5];

            headerColumn7 = row[6];

            headerColumn8 = row[7];



            if (headerColumn1 != "Asset_Id") or (headerColumn2 != "Asset Family") 

                or (headerColumn3 != "Asset Name") or (headerColumn4 != "Location")or (headerColumn5 != "Asset Component") 

                or (headerColumn6 != "Keywords") or (headerColumn7 != "Conditions") or (headerColumn8 != "Parts") :

                    return render_template("incomplete.html")

.....................................so on to then it will go to perform other task

HTML program:

html

<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="utf-8">

    <title> upload </title>

</head>

<body>

<div class="container">

    <h1>Large Data Generation</h1> 

<form id = "upload-form" action="{{ url_for('upload') }}" method="POST" enctype="multipart/form-data">

        <div id="file-selector">

            <p> 

                <strong>Source File: </strong>

                <input id="source_fileName" type="file" name="source_fileName" accept="csv/*" multiple />

            </p> 

        </div>

    <input type="submit" value="Generate Data" id="upload-button"  >

</form>

</div>

</body>

python csv flask

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

edited Dec 29 '18 at 12:00

asked Dec 29 '18 at 6:27

rahul singh

1048

asked Dec 29 '18 at 6:27

rahul singh

1048

asked Dec 29 '18 at 6:27

rahul singh

1048

add a comment |

1 Answer
1

active

oldest

votes

I You are having multiple files then you need to create instance of dataframe for each file
Upload function will look like this:

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)

        if not os.path.isdir(target):

            os.mkdir(target)

    abs_path_files=

    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)

            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            tempFile = os.path.abspath(destination)

            abs_path_files.append(tempfile)

            print("tempFile - " + tempFile)

    return redirect(url_for("compute", files_list=abs_path_files))

Compute Function will look like this:

def compute(files_list):

    dataFrames=

    for f in files_list:

        dataFrame=pd.read_csv(f)

        dataFrames.append(dataFrame)

    col_in_files = set([",".join(list(f.column.values)) for f in dataFrames])

    if len(col_in_files)==1:

       #then process your data here

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

I You are having multiple files then you need to create instance of dataframe for each file
Upload function will look like this:

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)

        if not os.path.isdir(target):

            os.mkdir(target)

    abs_path_files=

    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)

            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            tempFile = os.path.abspath(destination)

            abs_path_files.append(tempfile)

            print("tempFile - " + tempFile)

    return redirect(url_for("compute", files_list=abs_path_files))

Compute Function will look like this:

def compute(files_list):

    dataFrames=

    for f in files_list:

        dataFrame=pd.read_csv(f)

        dataFrames.append(dataFrame)

    col_in_files = set([",".join(list(f.column.values)) for f in dataFrames])

    if len(col_in_files)==1:

       #then process your data here

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

add a comment |

I You are having multiple files then you need to create instance of dataframe for each file
Upload function will look like this:

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)

        if not os.path.isdir(target):

            os.mkdir(target)

    abs_path_files=

    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)

            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            tempFile = os.path.abspath(destination)

            abs_path_files.append(tempfile)

            print("tempFile - " + tempFile)

    return redirect(url_for("compute", files_list=abs_path_files))

Compute Function will look like this:

def compute(files_list):

    dataFrames=

    for f in files_list:

        dataFrame=pd.read_csv(f)

        dataFrames.append(dataFrame)

    col_in_files = set([",".join(list(f.column.values)) for f in dataFrames])

    if len(col_in_files)==1:

       #then process your data here

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

add a comment |

I You are having multiple files then you need to create instance of dataframe for each file
Upload function will look like this:

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)

        if not os.path.isdir(target):

            os.mkdir(target)

    abs_path_files=

    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)

            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            tempFile = os.path.abspath(destination)

            abs_path_files.append(tempfile)

            print("tempFile - " + tempFile)

    return redirect(url_for("compute", files_list=abs_path_files))

Compute Function will look like this:

def compute(files_list):

    dataFrames=

    for f in files_list:

        dataFrame=pd.read_csv(f)

        dataFrames.append(dataFrame)

    col_in_files = set([",".join(list(f.column.values)) for f in dataFrames])

    if len(col_in_files)==1:

       #then process your data here

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

I You are having multiple files then you need to create instance of dataframe for each file
Upload function will look like this:

def upload():

    target = os.path.join(APP_ROOT, 'input/')

        print("target-",target)

        if not os.path.isdir(target):

            os.mkdir(target)

    abs_path_files=

    for file in request.files.getlist("source_fileName"):

            print("file-",file)

            filename = file.filename

            print("filename-",filename)

            destination = "/".join([target, filename])

            print("destination-",destination)

            file.save(destination)

            print("file>",file)

            tempFile = os.path.abspath(destination)

            abs_path_files.append(tempfile)

            print("tempFile - " + tempFile)

    return redirect(url_for("compute", files_list=abs_path_files))

Compute Function will look like this:

def compute(files_list):

    dataFrames=

    for f in files_list:

        dataFrame=pd.read_csv(f)

        dataFrames.append(dataFrame)

    col_in_files = set([",".join(list(f.column.values)) for f in dataFrames])

    if len(col_in_files)==1:

       #then process your data here

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

edited Dec 29 '18 at 11:24

answered Dec 29 '18 at 7:36

Gaurav

18010

answered Dec 29 '18 at 7:36

Gaurav

18010

answered Dec 29 '18 at 7:36

Gaurav

18010

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

add a comment |

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

Comments are not for extended discussion; this conversation has been moved to chat.

– Yvette Colomb♦
Dec 29 '18 at 23:52

add a comment |

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