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Insert a dict into a sql table

i wanted to insert some data into my sql but having trouble because there is alot of columns so i would have to write alot of parameters after VALUE. I have a table with all attributes from the json file and a player_id which i add myself
#Gamelogs for players and Teams
import requests
import json
import psycopg2
# Connect to your postgres DB
conn = psycopg2.connect("dbname=NBA user=postgres password=********")
# Open a cursor to perform database operations
cur = conn.cursor()
cur.execute('CREATE TABLE player_logs("player_id" int,"GameId" int,"Date" int,"Team" VARCHAR(10),"Opponent" VARCHAR(10),"Minutes" int,"Arc3Assists" int,"Arc3FGA" int,"Arc3Frequency" int,"AssistPoints" int,"Assists" int,"AtRimAssists" int,"AtRimFG3AFrequency" int,"Avg2ptShotDistance" int,"Avg3ptShotDistance" int,"BadPassOutOfBoundsTurnovers" int,"BadPassSteals" int,"BadPassTurnovers" int,"Corner3FGA" int,"Corner3Frequency" int,"DeadBallTurnovers" int,"DefArc3ReboundPct" int,"DefFGReboundPct" int,"DefPoss" int,"DefRebounds" int,"DefThreePtReboundPct" int,"DefThreePtRebounds" int,"EfgPct" int,"FG2A" int,"FG2M" int,"FG3A" int,"FG3APct" int,"FTA" int,"Fg2Pct" int,"FirstChancePoints" int,"Fouls" int,"FoulsDrawn" int,"FtPoints" int,"LiveBallTurnoverPct" int,"LiveBallTurnovers" int,"LongMidRangeAccuracy" int,"LongMidRangeAssists" int,"LongMidRangeFGA" int,"LongMidRangeFGM" int,"LongMidRangeFrequency" int,"Loose Ball Fouls" int,"LostBallTurnovers" int,"NonHeaveArc3FGA" int,"OffFGReboundPct" int,"OffPoss" int,"OffRebounds" int,"OffShortMidRangeReboundPct" int,"OffTwoPtReboundPct" int,"OffTwoPtRebounds" int,"OnDefRtg" int,"OnOffRtg" int,"PenaltyArc3FGA" int,"PenaltyArc3Frequency" int,"PenaltyDefPoss" int,"PenaltyEfgPct" int,"PenaltyFG2A" int,"PenaltyFG2M" int,"PenaltyFG3A" int,"PenaltyFg2Pct" int,"PenaltyOffPoss" int,"PenaltyOffPossExcludingTakeFouls" int,"PenaltyOffPossPct" int,"PenaltyPoints" int,"PenaltyPointsExcludingTakeFouls" int,"PenaltyPointsPct" int,"PenaltyShotQualityAvg" int,"PenaltyTsPct" int,"PenaltyTurnovers" int,"Period2Fouls2Minutes" int,"Period3Fouls3Minutes" int,"PlusMinus" int,"Points" int,"PtsUnassisted2s" int,"Rebounds" int,"SecondChanceOffPoss" int,"SelfOReb" int,"SelfORebPct" int,"ShootingFouls" int,"ShootingFoulsDrawnPct" int,"ShortMidRangeAccuracy" int,"ShortMidRangeAssists" int,"ShortMidRangeFGA" int,"ShortMidRangeFGM" int,"ShortMidRangeFrequency" int,"ShortMidRangeOffReboundedPct" int,"ShotQualityAvg" int,"Steals" int,"ThreePtAssists" int,"TotalPoss" int,"TsPct" int,"Turnovers" int,"TwoPtAssists" int,"TwoPtShootingFoulsDrawn" int,"TwoPtShootingFoulsDrawnPct" int,"UnblockedLongMidRangeAccuracy" int,"UnblockedShortMidRangeAccuracy" int,"Usage" int,"Arc3Accuracy" int,"Arc3FGM" int,"Arc3PctAssisted" int,"Assisted2sPct" int,"Assisted3sPct" int,"AtRimAccuracy" int,"AtRimFGA" int,"AtRimFGM" int,"AtRimFrequency" int,"AtRimOffReboundedPct" int,"AtRimPctBlocked" int,"Blocked2s" int,"BlockedShortMidRange" int,"Blocks" int,"BlocksRecoveredPct" int,"Corner3Assists" int,"DefAtRimReboundPct" int,"DefLongMidRangeReboundPct" int,"DefShortMidRangeReboundPct" int,"DefTwoPtReboundPct" int,"DefTwoPtRebounds" int,"FG2APctBlocked" int,"FG3M" int,"Fg2aBlocked" int,"Fg3Pct" int,"LongMidRangeOffReboundedPct" int,"LostBallSteals" int,"NonHeaveArc3Accuracy" int,"NonHeaveArc3FGM" int,"NonHeaveFg3Pct" int,"NonPutbacksAssisted2sPct" int,"NonShootingFoulsDrawn" int,"NonShootingPenaltyNonTakeFoulsDrawn" int,"OffLongMidRangeReboundPct" int,"Offensive Fouls Drawn" int,"PenaltyArc3Accuracy" int,"PenaltyArc3FGM" int,"PenaltyAtRimAccuracy" int,"PenaltyAtRimFGA" int,"PenaltyAtRimFGM" int,"PenaltyAtRimFrequency" int,"PenaltyFG3M" int,"PenaltyFg3Pct" int,"PenaltyFtPoints" int,"PtsAssisted2s" int,"PtsAssisted3s" int,"PtsPutbacks" int,"PtsUnassisted3s" int,"RecoveredBlocks" int,"SecondChanceArc3FGA" int,"SecondChanceArc3Frequency" int,"SecondChanceEfgPct" int,"SecondChanceFG2A" int,"SecondChanceFG2M" int,"SecondChanceFG3A" int,"SecondChanceFg2Pct" int,"SecondChancePoints" int,"SecondChancePointsPct" int,"SecondChanceShotQualityAvg" int,"SecondChanceTsPct" int,"ShortMidRangePctAssisted" int,"ShortMidRangePctBlocked" int,"ThreePtShootingFoulsDrawn" int,"ThreePtShootingFoulsDrawnPct" int,"UnblockedArc3Accuracy" int,"UnblockedAtRimAccuracy" int,"OffArc3ReboundPct" int,"OffThreePtReboundPct" int,"OffThreePtRebounds" int,"Offensive Fouls" int,"Corner3Accuracy" int,"Corner3FGM" int,"ThreePtOffReboundedPct" int,"UnblockedCorner3Accuracy" int,"DefFTReboundPct" int,"FTDefRebounds" int,"Technical Free Throw Trips" int,"BlockedAtRim" int,"LostBallOutOfBoundsTurnovers" int,"OffAtRimReboundPct" int,"BlockedLongMidRange" int,"Charge Fouls Drawn" int,"LongMidRangePctAssisted" int,"NonShootingPenaltyNonTakeFouls" int,"SecondChanceTurnovers" int,"Travels" int,"SecondChanceAtRimFGA" int,"SecondChanceAtRimFrequency" int,"Clear Path Fouls" int,"DefCorner3ReboundPct" int,"HeaveAttempts" int,"LongMidRangePctBlocked" int,"2pt And 1 Free Throw Trips" int,"AtRimPctAssisted" int,"Period3Fouls4Minutes" int,"Period4Fouls4Minutes" int,"Charge Fouls" int,"Loose Ball Fouls Drawn" int,"PeriodOTFouls4Minutes" int,"SecondChanceAtRimAccuracy" int,"SecondChanceAtRimFGM" int,"PenaltyCorner3FGA" int,"PenaltyCorner3Frequency" int,"Corner3PctAssisted" int,"SecondChanceFtPoints" int,"OffCorner3ReboundPct" int,"SecondChanceArc3Accuracy" int,"SecondChanceArc3FGM" int,"SecondChanceFG3M" int,"SecondChanceFg3Pct" int,"3pt And 1 Free Throw Trips" int,"Defensive 3 Seconds Violations" int,"Period4Fouls5Minutes" int,"StepOutOfBoundsTurnovers" int,"Period1Fouls2Minutes"int)')
x = 'https://api.pbpstats.com/get-all-players-for-league/nba'
headers = {'user-agent': 'Chrome/88.0.4324.190'}
jsonData1 = requests.get(x, headers=headers).json() # Player id and name
EntityId = json.loads(json.dumps(jsonData1)[12:-1])
SeasonType = {'R':'Regular+Season','P':'Playoff+Season','A':'All'}
EntityType = {'P':'Player','T':'Team'}
Season = {
'2008-09',
'2009-10',
'2010-11',
'2011-12',
'2012-13',
'2013-14',
'2014-15',
'2015-16',
'2016-17',
'2017-18',
'2018-19',
'2019-20',
'2020-21'
}
def log (S:Season,ST:SeasonType,EI:EntityId,ET:EntityType):
url = 'https://api.pbpstats.com/get-game-logs/nba'
payload = {
'Season': S,
'SeasonType': ST,
'EntityId': EI,
'EntityType': ET
}
r = requests.get(url, headers=headers, params=payload).json()
if r == {'error': 'no results'} :
return()
else :
for c in r['multi_row_table_data']:
j = {'Player_id':EI}
c.update(j)
cur.execute('INSERT INTO player_log (Player_id,GameId,Date,Team,Opponent,Minutes,Arc3Assists,Arc3FGA,Arc3Frequency,AssistPoints,Assists,AtRimAssists,AtRimFG3AFrequency,Avg2ptShotDistance,Avg3ptShotDistance,BadPassOutOfBoundsTurnovers,BadPassSteals,BadPassTurnovers,Corner3FGA,Corner3Frequency,DeadBallTurnovers,DefArc3ReboundPct,DefFGReboundPct,DefPoss,DefRebounds,DefThreePtReboundPct,DefThreePtRebounds,EfgPct,FG2A,FG2M,FG3A,FG3APct,FTA,Fg2Pct,FirstChancePoints,Fouls,FoulsDrawn,FtPoints,LiveBallTurnoverPct,LiveBallTurnovers,LongMidRangeAccuracy,LongMidRangeAssists,LongMidRangeFGA,LongMidRangeFGM,LongMidRangeFrequency,Loose_Ball_Fouls,LostBallTurnovers,NonHeaveArc3FGA,OffFGReboundPct,OffPoss,OffRebounds,OffShortMidRangeReboundPct,OffTwoPtReboundPct,OffTwoPtRebounds,OnDefRtg,OnOffRtg,PenaltyArc3FGA,PenaltyArc3Frequency,PenaltyDefPoss,PenaltyEfgPct,PenaltyFG2A,PenaltyFG2M,PenaltyFG3A,PenaltyFg2Pct,PenaltyOffPoss,PenaltyOffPossExcludingTakeFouls,PenaltyOffPossPct,PenaltyPoints,PenaltyPointsExcludingTakeFouls,PenaltyPointsPct,PenaltyShotQualityAvg,PenaltyTsPct,PenaltyTurnovers,Period2Fouls2Minutes,Period3Fouls3Minutes,PlusMinus,Points,PtsUnassisted2s,Rebounds,SecondChanceOffPoss,SelfOReb,SelfORebPct,ShootingFouls,ShootingFoulsDrawnPct,ShortMidRangeAccuracy,ShortMidRangeAssists,ShortMidRangeFGA,ShortMidRangeFGM,ShortMidRangeFrequency,ShortMidRangeOffReboundedPct,ShotQualityAvg,Steals,ThreePtAssists,TotalPoss,TsPct,Turnovers,TwoPtAssists,TwoPtShootingFoulsDrawn,TwoPtShootingFoulsDrawnPct,UnblockedLongMidRangeAccuracy,UnblockedShortMidRangeAccuracy,Usage,Arc3Accuracy,Arc3FGM,Arc3PctAssisted,Assisted2sPct,Assisted3sPct,AtRimAccuracy,AtRimFGA,AtRimFGM,AtRimFrequency,AtRimOffReboundedPct,AtRimPctBlocked,Blocked2s,BlockedShortMidRange,Blocks,BlocksRecoveredPct,Corner3Assists,DefAtRimReboundPct,DefLongMidRangeReboundPct,DefShortMidRangeReboundPct,DefTwoPtReboundPct,DefTwoPtRebounds,FG2APctBlocked,FG3M,Fg2aBlocked,Fg3Pct,LongMidRangeOffReboundedPct,LostBallSteals,NonHeaveArc3Accuracy,NonHeaveArc3FGM,NonHeaveFg3Pct,NonPutbacksAssisted2sPct,NonShootingFoulsDrawn,NonShootingPenaltyNonTakeFoulsDrawn,OffLongMidRangeReboundPct,Offensive_Fouls_Drawn,PenaltyArc3Accuracy,PenaltyArc3FGM,PenaltyAtRimAccuracy,PenaltyAtRimFGA,PenaltyAtRimFGM,PenaltyAtRimFrequency,PenaltyFG3M,PenaltyFg3Pct,PenaltyFtPoints,PtsAssisted2s,PtsAssisted3s,PtsPutbacks,PtsUnassisted3s,RecoveredBlocks,SecondChanceArc3FGA,SecondChanceArc3Frequency,SecondChanceEfgPct,SecondChanceFG2A,SecondChanceFG2M,SecondChanceFG3A,SecondChanceFg2Pct,SecondChancePoints,SecondChancePointsPct,SecondChanceShotQualityAvg,SecondChanceTsPct,ShortMidRangePctAssisted,ShortMidRangePctBlocked,ThreePtShootingFoulsDrawn,ThreePtShootingFoulsDrawnPct,UnblockedArc3Accuracy,UnblockedAtRimAccuracy,OffArc3ReboundPct,OffThreePtReboundPct,OffThreePtRebounds,Offensive_Fouls,Corner3Accuracy,Corner3FGM,ThreePtOffReboundedPct,UnblockedCorner3Accuracy,DefFTReboundPct,FTDefRebounds,Technical_Free_Throw_Trips,BlockedAtRim,LostBallOutOfBoundsTurnovers,OffAtRimReboundPct,BlockedLongMidRange,Charge_Fouls_Drawn,LongMidRangePctAssisted,NonShootingPenaltyNonTakeFouls,SecondChanceTurnovers,Travels,SecondChanceAtRimFGA,SecondChanceAtRimFrequency,Clear_Path_Fouls,DefCorner3ReboundPct,HeaveAttempts,LongMidRangePctBlocked,"2pt_And_1_Free_Throw_Trips",AtRimPctAssisted,Period3Fouls4Minutes,Period4Fouls4Minutes,Charge_Fouls,Loose_Ball_Fouls_Drawn,PeriodOTFouls4Minutes,SecondChanceAtRimAccuracy,SecondChanceAtRimFGM,PenaltyCorner3FGA,PenaltyCorner3Frequency,Corner3PctAssisted,SecondChanceFtPoints,OffCorner3ReboundPct,SecondChanceArc3Accuracy,SecondChanceArc3FGM,SecondChanceFG3M,SecondChanceFg3Pct,"3pt_And_1_Free_Throw_Trips",Defensive_3_Seconds_Violations,Period4Fouls5Minutes,StepOutOfBoundsTurnovers,Period1Fouls2Minutes) VALUES',
c)
return()
y=log('2020-21','Regular+Season','101108','Player')
conn.commit()
conn.close()
cur.close()
So was wondering if i could insert the data so it matched with the key and the column name. So the table and dict isnt order the same way either if it makes a difference.

This is fairly simple to do by adopting two helper libraries: pandas and preql.
You can use pandas to load the json into a single dataframe, and then use preql to import it into the database.
Here is runnable code demonstrating how to do it:
import requests
import pandas as pd
from preql import Preql
headers = {'user-agent': 'Chrome/88.0.4324.190'}
def log(S,ST,EI,ET):
url = 'https://api.pbpstats.com/get-game-logs/nba'
payload = {
'Season': S,
'SeasonType': ST,
'EntityId': EI,
'EntityType': ET
}
r = requests.get(url, headers=headers, params=payload).json()
if r == {'error': 'no results'} :
return
else:
return [{'Player_id':EI, **d} for d in r['multi_row_table_data']]
rows=log('2020-21','Regular+Season','101108','Player')
df = pd.DataFrame.from_dict(rows)
print("Dataframe shape:", df.shape) # (50, 218)
p = Preql() # For postgres use: p = Preql("postgres://user:pass#server")
p.import_pandas(my_table=df)
print('SQL columns:', p('count(columns(my_table))')) # 219 - includes id
print('SQL rows:', p('count(my_table)')) # 50
Note that this code example is currently using Python's built-in Sqlite, but you can easily make it work with postgres by providing Preql with the postgres URL, as the comment shows.
Install them with pip install pandas preql-lang

Might not be the best solution, but I wrote a small function that just converts to SQL statement.
def insert_into_table_query(table, data):
col_names = list(data.keys())
task = tuple(data.values())
col_str = ', '.join(str(item) for item in col_names)
col_str = '(' + col_str + ')'
value_str = ', '.join('%s' for item in task)
value_str = '(' + value_str + ');'
sql = 'INSERT INTO {tn} '.format(tn=table) + col_str + ' VALUES ' + value_str
return (sql, task)

Scraping Asxp page with beautiful soup

enter image description hereI am trying to scrape this page using Beautiful Soup, I 1st tried to find any API/Json behind the page which I couldn't find. And then I was trying a BS and HTML parser, but I can't get anywhere with it.
I am not able to do so coz the page is calling a function with onclick GetFiiStatistics('F-INDEX FUTURES').
How can I go about scraping pages like these?
webpage:
https://www.motilaloswal.com/markets/derivative-market/FII-Statistics.aspx

The data is loaded via Javascript from their API. Unfortunately, I don't know, how INPUT, CATAGORY and FLAG values are computed:
import json
import requests
import pandas as pd
from bs4 import BeautifulSoup
api_url = 'https://www.motilaloswal.com/ControllerBeta/APIRequest.aspx'
data = {
'INPUT':'3yDBtksOiDjLLYaySd5NYgCcFnUOx8Jh2c8SRJvEhAs=',
'CATAGORY':'Q668CVoAKYOr7whA+PW25A==',
'FLAG':'VrTQQDRa72uSLVOyZO5Nqg=='
}
json_data = json.loads(requests.post(api_url, data=data).json())
# uncomment this to print all data:
# print(json.dumps(json_data, indent=4))
df = pd.DataFrame(json_data)
print(df)
Prints:
IndexType Date BuyContracts BuyValue SellContracts SellValue Net_BuySellValue OIContracts_eod OIValue_eod
0 INDEX FUTURES 2020-07-14T00:00:00 67037 4403.320 88350 6048.750 -1645.430 123985 8799.15
1 INDEX FUTURES 2020-07-13T00:00:00 53612 3644.000 61174 4142.300 -498.300 105126 7803.56
2 INDEX FUTURES 2020-07-10T00:00:00 62735 4313.250 83916 5923.270 -1610.020 113346 8369.47
3 INDEX FUTURES 2020-07-09T00:00:00 67222 4773.340 51094 3442.520 1330.820 119977 8971.28
4 INDEX FUTURES 2020-07-08T00:00:00 83367 5661.640 69042 4659.280 1002.360 106027 7686.32
.. ... ... ... ... ... ... ... ... ...
495 INDEX FUTURES 2018-07-05T00:00:00 28566 2585.923 21393 1881.601 704.322 243417 19847.72
496 INDEX FUTURES 2018-07-04T00:00:00 21339 1875.184 26507 2425.003 -549.819 245786 20201.28
497 INDEX FUTURES 2018-07-03T00:00:00 30019 2610.728 28837 2563.647 47.081 237564 19322.63
498 INDEX FUTURES 2018-07-02T00:00:00 24976 2191.751 29501 2541.589 -349.838 226100 18203.48
499 INDEX FUTURES 2018-06-29T00:00:00 45399 3814.480 27297 2371.817 1442.663 227041 18387.33
[500 rows x 9 columns]
EDIT: To scrape other tabs, change the data= parameter in request:
import json
import requests
import pandas as pd
from bs4 import BeautifulSoup
api_url = 'https://www.motilaloswal.com/ControllerBeta/APIRequest.aspx'
data_future = {
'INPUT':'3yDBtksOiDjLLYaySd5NYgCcFnUOx8Jh2c8SRJvEhAs=',
'CATAGORY':'Q668CVoAKYOr7whA+PW25A==',
'FLAG':'VrTQQDRa72uSLVOyZO5Nqg=='
}
data_option = {
'INPUT': '3yDBtksOiDjLLYaySd5NYmcoKC8x7z5PFO880mjcQ2U=',
'CATAGORY': 'Q668CVoAKYOr7whA+PW25A==',
'FLAG': "VrTQQDRa72uSLVOyZO5Nqg=="
}
data_stock_future = {
'INPUT': '7F5jZM46TTOICwT1N6AfqkP7gWI2CpTGCWmll4bhYow=',
'CATAGORY': 'Q668CVoAKYOr7whA+PW25A==',
'FLAG': 'VrTQQDRa72uSLVOyZO5Nqg=='
}
data_stock_option = {
'INPUT': '7F5jZM46TTOICwT1N6Afqv1N6pCh+1OrTfhSwG6Azes=',
'CATAGORY': 'Q668CVoAKYOr7whA+PW25A==',
'FLAG': 'VrTQQDRa72uSLVOyZO5Nqg=='
}
json_data = json.loads(requests.post(api_url, data=data_stock_option).json()) # <-- change data= to data_stock_future or data_option ...
# uncomment this to print all data:
# print(json.dumps(json_data, indent=4))
df = pd.DataFrame(json_data)
print(df)
Prints:
IndexType Date BuyContracts BuyValue SellContracts SellValue Net_BuySellValue OIContracts_eod OIValue_eod
0 STOCK OPTIONS 2020-07-14T00:00:00 52546 4349.020 54139 4525.850 -176.830 115998 7661.010
1 STOCK OPTIONS 2020-07-13T00:00:00 50604 4242.330 52221 4413.040 -170.710 110663 7329.990
2 STOCK OPTIONS 2020-07-10T00:00:00 82502 6218.200 82608 6219.420 -1.220 109680 7232.900
3 STOCK OPTIONS 2020-07-09T00:00:00 64743 4725.430 64613 4714.460 10.970 104780 6945.740
4 STOCK OPTIONS 2020-07-08T00:00:00 75481 5201.770 75713 5220.580 -18.810 100200 6584.390
.. ... ... ... ... ... ... ... ... ...
495 STOCK OPTIONS 2018-07-05T00:00:00 94696 6728.086 93256 6617.059 111.027 66773 4471.483
496 STOCK OPTIONS 2018-07-04T00:00:00 68719 4762.333 69376 4794.350 -32.017 59195 4005.045
497 STOCK OPTIONS 2018-07-03T00:00:00 64283 4351.226 64982 4347.153 4.073 53028 3581.946
498 STOCK OPTIONS 2018-07-02T00:00:00 74479 4913.606 74730 4897.239 16.367 44627 3024.131
499 STOCK OPTIONS 2018-06-29T00:00:00 69730 4694.675 68447 4645.350 49.325 35486 2421.744
[500 rows x 9 columns]

requests and bs4 cannot read the whole html

I am trying to get all the href in the list in this website:https://nihongonosensei.net/?page_id=10246.
The website is very simple and clean. After reviewing the source, I found nothing dynamic.
However, if I do
import requests
url = 'https://nihongonosensei.net/?page_id=10246'
r = requests.get(url)
r.text
r.text only contains around 20000 characters information. More than half of the html is missing.
I tried to copy the whole HTML from "view page source" and directly load to Beautifulsoup:
from bs4 import BeautifulSoup
html = '' # too long to copy. Here is the link: view-source:https://nihongonosensei.net/?page_id=10246
soup = BeautifulSoup(html, 'html.parser')
Still only around 20000 characters are retained and the top half of the html is missing.
Here is my question:
Is there any character restrictions with requests and BeautifulSoup?
If so, how can I remove the limitation?
If not, why I cannot get the full html?
Thanks a lot!
Rachel

import requests
from bs4 import BeautifulSoup
r = requests.get("https://nihongonosensei.net/?page_id=10246")
soup = BeautifulSoup(r.text, 'html.parser')
for item in soup.findAll("a", href=True):
item = item.get("href")
if item.startswith("http"):
print(item)
output:
https://nihongonosensei.net/
http://nihongonosensei.net/?p=3547
http://nihongonosensei.net/?p=3563
http://nihongonosensei.net/?p=3568
http://nihongonosensei.net/?p=3600
http://nihongonosensei.net/?p=3614
http://nihongonosensei.net/?p=3618
http://nihongonosensei.net/?p=3622
http://nihongonosensei.net/?p=3626
http://nihongonosensei.net/?p=3633
http://nihongonosensei.net/?p=3695
http://nihongonosensei.net/?p=3697
http://nihongonosensei.net/?p=3702
http://nihongonosensei.net/?p=3707
http://nihongonosensei.net/?p=3710
http://nihongonosensei.net/?p=3712
http://nihongonosensei.net/?p=3714
http://nihongonosensei.net/?p=3719
http://nihongonosensei.net/?p=3722
http://nihongonosensei.net/?p=3726
http://nihongonosensei.net/?p=3730
http://nihongonosensei.net/?p=3733
http://nihongonosensei.net/?p=3735
http://nihongonosensei.net/?p=5236
http://nihongonosensei.net/?p=5238
http://nihongonosensei.net/?p=5240
http://nihongonosensei.net/?p=5244
http://nihongonosensei.net/?p=5618
http://nihongonosensei.net/?p=5620
http://nihongonosensei.net/?p=5961
http://nihongonosensei.net/?p=5965
http://nihongonosensei.net/?p=5967
http://nihongonosensei.net/?p=5970
http://nihongonosensei.net/?p=5972
http://nihongonosensei.net/?p=6772
http://nihongonosensei.net/?p=7977
http://nihongonosensei.net/?p=7979
http://nihongonosensei.net/?p=7983
http://nihongonosensei.net/?p=7985
http://nihongonosensei.net/?p=7987
http://nihongonosensei.net/?p=8869
http://nihongonosensei.net/?p=8891
http://nihongonosensei.net/?p=9192
http://nihongonosensei.net/?p=9197
http://nihongonosensei.net/?p=9198
http://nihongonosensei.net/?p=9199
http://nihongonosensei.net/?p=9219
http://nihongonosensei.net/?p=9221
http://nihongonosensei.net/?p=9223
http://nihongonosensei.net/?p=9249
http://nihongonosensei.net/?p=9280
http://nihongonosensei.net/?p=9320
http://nihongonosensei.net/?p=9322
http://nihongonosensei.net/?p=9324
http://nihongonosensei.net/?p=9327
http://nihongonosensei.net/?p=9329
http://nihongonosensei.net/?p=9353
http://nihongonosensei.net/?p=9359
http://nihongonosensei.net/?p=9360
http://nihongonosensei.net/?p=13973
http://nihongonosensei.net/?p=13972
http://nihongonosensei.net/?p=13974
http://nihongonosensei.net/?p=11851
http://nihongonosensei.net/?p=11858
http://nihongonosensei.net/?p=12202
http://nihongonosensei.net/?p=12999
http://nihongonosensei.net/?p=13112
http://nihongonosensei.net/?p=13364
http://nihongonosensei.net/?p=13494
http://nihongonosensei.net/?p=14887
http://nihongonosensei.net/?p=14889
http://nihongonosensei.net/?p=14915
http://nihongonosensei.net/?p=14918
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Trying to grab just the first href in each table row

I'm trying to grab just the first href in each row in an HTML table. Using find_all on the soup object doesn't work because there are multiple tables so I used soup.select() to isolate just that table and work from there but it doesn't seem to be working.
Tried using find_all on the soup object alone, tried looping through the table rows with find() but it said that it returns 'NoneType'.
I Would like to be able to store a list that starts [/players/a/abrinal01.html, "/players/a/acyqu01.html, etc]
url = 'https://www.basketball-reference.com/leagues/NBA_2019_per_game.html'
res = requests.get(url)
res.raise_for_status()
soup = bs4.BeautifulSoup(res.text, 'html.parser')
table = soup.find("table", { "id" : "per_game_stats" })

You can access the desired data by anchoring the parsing from the outer div wrapper with the id of all_per_game_stats:
import requests
from bs4 import BeautifulSoup as soup
d = soup(requests.get('https://www.basketball-reference.com/leagues/NBA_2019_per_game.html').text, 'html.parser')
data = [b.td.a['href'] for b in d.find('div', {'id':'all_per_game_stats'}).table.find_all('tr') if b.td]
Output:
['/players/a/abrinal01.html', '/players/a/acyqu01.html', '/players/a/adamsja01.html', '/players/a/adamsst01.html', '/players/a/adebaba01.html', '/players/a/adelde01.html', '/players/a/akoonde01.html', '/players/a/aldrila01.html', '/players/a/alkinra01.html', '/players/a/allengr01.html', '/players/a/allenja01.html', '/players/a/allenka01.html', '/players/a/aminual01.html', '/players/a/anderju01.html', '/players/a/anderky01.html', '/players/a/anderry01.html', '/players/a/anderry01.html', '/players/a/anderry01.html', '/players/a/anigbik01.html', '/players/a/antetgi01.html', '/players/a/antetko01.html', '/players/a/anthoca01.html', '/players/a/anunoog01.html', '/players/a/arcidry01.html', '/players/a/arizatr01.html', '/players/a/arizatr01.html', '/players/a/arizatr01.html', '/players/a/augusdj01.html', '/players/a/aytonde01.html', '/players/b/bacondw01.html', '/players/b/baglema01.html', '/players/b/bakerro01.html', '/players/b/bakerro01.html', '/players/b/bakerro01.html', '/players/b/baldwwa01.html', '/players/b/balllo01.html', '/players/b/bambamo01.html', '/players/b/bareajo01.html', '/players/b/barneha02.html', '/players/b/barneha02.html', '/players/b/barneha02.html', '/players/b/bartowi01.html', '/players/b/bateske01.html', '/players/b/batumni01.html', '/players/b/bayleje01.html', '/players/b/baynear01.html', '/players/b/bazemke01.html', '/players/b/bealbr01.html', '/players/b/beaslma01.html', '/players/b/beaslmi01.html', '/players/b/belinma01.html', '/players/b/belljo01.html', '/players/b/bembrde01.html', '/players/b/bendedr01.html', '/players/b/bertada02.html', '/players/b/bertada01.html', '/players/b/beverpa01.html', '/players/b/birchkh01.html', '/players/b/biyombi01.html', '/players/b/bjeline01.html', '/players/b/blakean01.html', '/players/b/bledser01.html', '/players/b/blossja01.html', '/players/b/bogdabo01.html', '/players/b/bogdabo02.html', '/players/b/bogutan01.html', '/players/b/boldejo01.html', '/players/b/bongais01.html', '/players/b/bookede01.html', '/players/b/bouchch01.html', '/players/b/bradlav01.html', '/players/b/bradlav01.html', '/players/b/bradlav01.html', '/players/b/bradlto01.html', '/players/b/breweco01.html', '/players/b/breweco01.html', '/players/b/breweco01.html', '/players/b/bridgmi01.html', '/players/b/bridgmi02.html', '/players/b/briscis01.html', '/players/b/broekry01.html', '/players/b/brogdma01.html', '/players/b/brookdi01.html', '/players/b/brookma01.html', '/players/b/brownbr01.html', '/players/b/brownja02.html', '/players/b/brownlo01.html', '/players/b/brownst02.html', '/players/b/browntr01.html', '/players/b/brunsja01.html', '/players/b/bryanth01.html', '/players/b/bullore01.html', '/players/b/bullore01.html', '/players/b/bullore01.html', '/players/b/burketr01.html', '/players/b/burketr01.html', '/players/b/burketr01.html', '/players/b/burksal01.html', '/players/b/burksal01.html', '/players/b/burksal01.html', '/players/b/burksal01.html', '/players/b/burtode02.html', '/players/b/butleji01.html', '/players/b/butleji01.html', '/players/b/butleji01.html', '/players/c/cabocbr01.html', '/players/c/caldejo01.html', '/players/c/caldwke01.html', '/players/c/canaais01.html', '/players/c/canaais01.html', '/players/c/canaais01.html', '/players/c/canaais01.html', '/players/c/capelca01.html', '/players/c/carrode01.html', '/players/c/carteje01.html', '/players/c/cartevi01.html', '/players/c/cartewe01.html', '/players/c/cartemi01.html', '/players/c/cartemi01.html', '/players/c/cartemi01.html', '/players/c/carusal01.html', '/players/c/casspom01.html', '/players/c/caulewi01.html', '/players/c/caupatr01.html', '/players/c/cavanty01.html', '/players/c/chandty01.html', '/players/c/chandty01.html', '/players/c/chandty01.html', '/players/c/chandwi01.html', '/players/c/chandwi01.html', '/players/c/chandwi01.html', '/players/c/chealjo01.html', '/players/c/chiozch01.html', '/players/c/chrisma01.html', '/players/c/chrisma01.html', '/players/c/chrisma01.html', '/players/c/clarkga01.html', '/players/c/clarkia01.html', '/players/c/clarkjo01.html', '/players/c/collijo01.html', '/players/c/colliza01.html', '/players/c/collida01.html', '/players/c/colsobo01.html', '/players/c/conlemi01.html', '/players/c/connapa01.html', '/players/c/cookqu01.html', '/players/c/couside01.html', '/players/c/covinro01.html', '/players/c/covinro01.html', '/players/c/covinro01.html', '/players/c/crabbal01.html', '/players/c/craigto01.html', '/players/c/crawfja01.html', '/players/c/creekmi01.html', '/players/c/creekmi01.html', '/players/c/creekmi01.html', '/players/c/crowdja01.html', '/players/c/cunnida01.html', '/players/c/curryse01.html', '/players/c/curryst01.html', '/players/d/danietr01.html', '/players/d/davisan02.html', '/players/d/davisde01.html', '/players/d/davised01.html', '/players/d/davisty01.html', '/players/d/dedmode01.html', '/players/d/dekkesa01.html', '/players/d/dekkesa01.html', '/players/d/dekkesa01.html', '/players/d/delgaan01.html', '/players/d/dellama01.html', '/players/d/dellama01.html', '/players/d/dellama01.html', '/players/d/denglu01.html', '/players/d/derozde01.html', '/players/d/derrima01.html', '/players/d/diallch01.html', '/players/d/diallha01.html', '/players/d/dienggo01.html', '/players/d/dinwisp01.html', '/players/d/divindo01.html', '/players/d/doncilu01.html', '/players/d/dorsety01.html', '/players/d/dorsety01.html', '/players/d/dorsety01.html', '/players/d/dotsoda01.html', '/players/d/doziepj01.html', '/players/d/dragigo01.html', '/players/d/drumman01.html', '/players/d/dudleja01.html', '/players/d/dunnkr01.html', '/players/d/duranke01.html', '/players/d/duvaltr01.html', '/players/e/edwarvi01.html', '/players/e/ellenhe01.html', '/players/e/ellenhe01.html', '/players/e/ellenhe01.html', '/players/e/ellinwa01.html', '/players/e/ellinwa01.html', '/players/e/ellinwa01.html', '/players/e/embiijo01.html', '/players/e/ennisja01.html', '/players/e/ennisja01.html', '/players/e/ennisja01.html', '/players/e/eubandr01.html', '/players/e/evansja02.html', '/players/e/evansja01.html', '/players/e/evansja01.html', '/players/e/evansja01.html', '/players/e/evansty01.html', '/players/e/exumda01.html', '/players/f/farieke01.html', '/players/f/farieke01.html', '/players/f/farieke01.html', '/players/f/favorde01.html', '/players/f/feliccr01.html', '/players/f/feltora01.html', '/players/f/fergute01.html', '/players/f/ferreyo01.html', '/players/f/finnedo01.html', '/players/f/forbebr01.html', '/players/f/fournev01.html', '/players/f/foxde01.html', '/players/f/frazime01.html', '/players/f/fraziti01.html', '/players/f/fraziti01.html', '/players/f/fraziti01.html', '/players/f/fredeji01.html', '/players/f/fryech01.html', '/players/f/fultzma01.html', '/players/g/gallida01.html', '/players/g/gallola01.html', '/players/g/garrebi01.html', '/players/g/gasolma01.html', '/players/g/gasolma01.html', '/players/g/gasolma01.html', '/players/g/gasolpa01.html', '/players/g/gasolpa01.html', '/players/g/gasolpa01.html', '/players/g/gayru01.html', '/players/g/georgpa01.html', '/players/g/gibsota01.html', '/players/g/gilesha01.html', '/players/g/gilgesh01.html', '/players/g/goberru01.html', '/players/g/goodwbr01.html', '/players/g/gordoaa01.html', '/players/g/gordoer01.html', '/players/g/gortama01.html', '/players/g/grahade01.html', '/players/g/grahatr01.html', '/players/g/grantje01.html', '/players/g/grantje02.html', '/players/g/grantdo01.html', '/players/g/greenda02.html', '/players/g/greendr01.html', '/players/g/greenge01.html', '/players/g/greenja01.html', '/players/g/greenja01.html', '/players/g/greenja01.html', '/players/g/greenje02.html', '/players/g/griffbl01.html', '/players/h/hamilda02.html', '/players/h/hannadu01.html', '/players/h/hardati02.html', '/players/h/hardati02.html', '/players/h/hardati02.html', '/players/h/hardeja01.html', '/players/h/harklma01.html', '/players/h/harremo01.html', '/players/h/harride01.html', '/players/h/harriga01.html', '/players/h/harrijo01.html', '/players/h/harrito02.html', '/players/h/harrito02.html', '/players/h/harrito02.html', '/players/h/harrian01.html', '/players/h/harrian01.html', '/players/h/harrian01.html', '/players/h/harrian01.html', '/players/h/harrish01.html', '/players/h/hartjo01.html', '/players/h/harteis01.html', '/players/h/hasleud01.html', '/players/h/haywago01.html', '/players/h/hensojo01.html', '/players/h/hernaju01.html', '/players/h/hernawi01.html', '/players/h/hezonma01.html', '/players/h/hicksis01.html', '/players/h/hieldbu01.html', '/players/h/highsha01.html', '/players/h/hilarne01.html', '/players/h/hillge01.html', '/players/h/hillge01.html', '/players/h/hillge01.html', '/players/h/hillso01.html', '/players/h/holidaa01.html', '/players/h/holidjr01.html', '/players/h/holidju01.html', '/players/h/holidju01.html', '/players/h/holidju01.html', '/players/h/hollajo02.html', '/players/h/holliro01.html', '/players/h/holmeri01.html', '/players/h/hoodro01.html', '/players/h/hoodro01.html', '/players/h/hoodro01.html', '/players/h/horfoal01.html', '/players/h/houseda01.html', '/players/h/howardw01.html', '/players/h/huertke01.html', '/players/h/humphis01.html', '/players/h/hunterj01.html', '/players/h/hutchch01.html', '/players/i/ibakase01.html', '/players/i/iguodan01.html', '/players/i/ilyaser01.html', '/players/i/inglejo01.html', '/players/i/ingraan01.html', '/players/i/ingrabr01.html', '/players/i/irvinky01.html', '/players/i/isaacjo01.html', '/players/i/iwundwe01.html', '/players/j/jacksde01.html', '/players/j/jacksfr01.html', '/players/j/jacksja02.html', '/players/j/jacksjo02.html', '/players/j/jacksju01.html', '/players/j/jacksju01.html', '/players/j/jacksju01.html', '/players/j/jacksre01.html', '/players/j/jamesle01.html', '/players/j/jeffeam01.html', '/players/j/jenkijo01.html', '/players/j/jenkijo01.html', '/players/j/jenkijo01.html', '/players/j/jerebjo01.html', '/players/j/johnsal02.html', '/players/j/johnsam01.html', '/players/j/johnsbj01.html', '/players/j/johnsbj01.html', '/players/j/johnsbj01.html', '/players/j/johnsja01.html', '/players/j/johnsst04.html', '/players/j/johnsst04.html', '/players/j/johnsst04.html', '/players/j/johnsty01.html', '/players/j/johnsty01.html', '/players/j/johnsty01.html', '/players/j/johnswe01.html', '/players/j/johnswe01.html', '/players/j/johnswe01.html', '/players/j/jokicni01.html', '/players/j/jonesda03.html', '/players/j/jonesde02.html', '/players/j/jonesja04.html', '/players/j/jonesje01.html', '/players/j/joneste01.html', '/players/j/jonesty01.html', '/players/j/jordade01.html', '/players/j/jordade01.html', '/players/j/jordade01.html', '/players/j/josepco01.html', '/players/k/kaminfr01.html', '/players/k/kanteen01.html', '/players/k/kanteen01.html', '/players/k/kanteen01.html', '/players/k/kennalu01.html', '/players/k/kiddgmi01.html', '/players/k/kingge03.html', '/players/k/klebima01.html', '/players/k/knighbr03.html', '/players/k/knighbr03.html', '/players/k/knighbr03.html', '/players/k/knoxke01.html', '/players/k/korkmfu01.html', '/players/k/kornelu01.html', '/players/k/korveky01.html', '/players/k/korveky01.html', '/players/k/korveky01.html', '/players/k/koufoko01.html', '/players/k/kurucro01.html', '/players/k/kuzmaky01.html', '/players/l/labissk01.html', '/players/l/labissk01.html', '/players/l/labissk01.html', '/players/l/lambje01.html', '/players/l/lavinza01.html', '/players/l/laymaja01.html', '/players/l/leaftj01.html', '/players/l/leeco01.html', '/players/l/leeco01.html', '/players/l/leeco01.html', '/players/l/leeda03.html', '/players/l/lemonwa01.html', '/players/l/lenal01.html', '/players/l/leonaka01.html', '/players/l/leoname01.html', '/players/l/leuerjo01.html', '/players/l/leverca01.html', '/players/l/lillada01.html', '/players/l/linje01.html', '/players/l/linje01.html', '/players/l/linje01.html', '/players/l/livinsh01.html', '/players/l/loftoza01.html', '/players/l/looneke01.html', '/players/l/lopezbr01.html', '/players/l/lopezro01.html', '/players/l/loveke01.html', '/players/l/lowryky01.html', '/players/l/loydjo01.html', '/players/l/lucaska01.html', '/players/l/luwawti01.html', '/players/l/luwawti01.html', '/players/l/luwawti01.html', '/players/l/lydonty01.html', '/players/l/lylestr01.html', '/players/m/machasc01.html', '/players/m/macksh01.html', '/players/m/macksh01.html', '/players/m/macksh01.html', '/players/m/maconda01.html', '/players/m/macurjp01.html', '/players/m/mahinia01.html', '/players/m/makerth01.html', '/players/m/makerth01.html', '/players/m/makerth01.html', '/players/m/marjabo01.html', '/players/m/marjabo01.html', '/players/m/marjabo01.html', '/players/m/markkla01.html', '/players/m/martija01.html', '/players/m/masonfr01.html', '/players/m/matenya01.html', '/players/m/matthwe02.html', '/players/m/matthwe02.html', '/players/m/matthwe02.html', '/players/m/matthwe02.html', '/players/m/mbahalu01.html', '/players/m/mccalta01.html', '/players/m/mccawpa01.html', 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I would use a set comprehension to remove duplicates and also I think nth-of-type to select the appropriate column reads more cleanly. Using bs4 4.7.1
import requests
from bs4 import BeautifulSoup as bs
soup = bs(requests.get('https://www.basketball-reference.com/leagues/NBA_2019_per_game.html').text, 'html.parser')
links = {i['href'] for i in soup.select('#per_game_stats td:nth-of-type(1) a')}
print(links)
You could also use the following css selector:
[csk] > a

Extracting data with BeautifulSoup and output to CSV

As mentioned in the previous questions, I am using Beautiful soup with python to retrieve weather data from a website.
Here's how the website looks like:
<channel>
<title>2 Hour Forecast</title>
<source>Meteorological Services Singapore</source>
<description>2 Hour Forecast</description>
<item>
<title>Nowcast Table</title>
<category>Singapore Weather Conditions</category>
<forecastIssue date="18-07-2016" time="03:30 PM"/>
<validTime>3.30 pm to 5.30 pm</validTime>
<weatherForecast>
<area forecast="TL" lat="1.37500000" lon="103.83900000" name="Ang Mo Kio"/>
<area forecast="SH" lat="1.32100000" lon="103.92400000" name="Bedok"/>
<area forecast="TL" lat="1.35077200" lon="103.83900000" name="Bishan"/>
<area forecast="CL" lat="1.30400000" lon="103.70100000" name="Boon Lay"/>
<area forecast="CL" lat="1.35300000" lon="103.75400000" name="Bukit Batok"/>
<area forecast="CL" lat="1.27700000" lon="103.81900000" name="Bukit Merah"/>`
<channel>
I managed to retrieve the information I need using these codes :
import requests
from bs4 import BeautifulSoup
import urllib3
#getting the ValidTime
r = requests.get('http://www.nea.gov.sg/api/WebAPI/?
dataset=2hr_nowcast&keyref=781CF461BB6606AD907750DFD1D07667C6E7C5141804F45D')
soup = BeautifulSoup(r.content, "xml")
time = soup.find('validTime').string
print "validTime: " + time
#getting the date
for currentdate in soup.find_all('item'):
element = currentdate.find('forecastIssue')
print "date: " + element['date']
#getting the time
for currentdate in soup.find_all('item'):
element = currentdate.find('forecastIssue')
print "time: " + element['time']
for area in soup.find('weatherForecast').find_all('area'):
area_attrs_li = [area.attrs for area in soup.find('weatherForecast').find_all('area')]
print area_attrs_li
Here are my results :
{'lat': u'1.34039000', 'lon': u'103.70500000', 'name': u'Jurong West',
'forecast': u'LR'}, {'lat': u'1.31200000', 'lon': u'103.86200000', 'name':
u'Kallang', 'forecast': u'LR'},
How do I remove u' from the result? I tried using the method I found while googling but it doesn't seem to work
I'm not strong in Python and have been stuck at this for quite a while.
EDIT : I tried doing this :
f = open("C:\\scripts\\nea.csv" , 'wt')
try:
for area in area_attrs_li:
writer = csv.writer(f)
writer.writerow( (time, element['date'], element['time'], area_attrs_li))
finally:
f.close()
print open("C:/scripts/nea.csv", 'rt').read()
It worked however, I would like to split the area apart as the records are duplicates in the CSV :
Thank you.

EDIT 1 -Topic:
You're missing escape characters:
C:\scripts>python neaweather.py
File "neaweather.py", line 30
writer.writerow( ('time', 'element['date']', 'element['time']', 'area_attrs_li') )
writer.writerow( ('time', 'element[\'date\']', 'element[\'time\']', 'area_attrs_li')
^
SyntaxError: invalid syntax
EDIT 2:
if you want to insert values:
writer.writerow( (time, element['date'], element['time'], area_attrs_li) )
EDIT 3:
to split the result to different lines:
for area in area_attrs_li:
writer.writerow( (time, element['date'], element['time'], area)
EDIT 4:
The splitting is not correct at all, but it shall give a better understanding of how to parse and split data to change it for your needs.
to split the area element again as you show in your image, you can parse it
for area in area_attrs_li:
# cut off the characters you don't need
area = area.replace('[','')
area = area.replace(']','')
area = area.replace('{','')
area = area.replace('}','')
# remove other characters
area = area.replace("u'","\"").replace("'","\"")
# split the string into a list
areaList = area.split(",")
# create your own csv-seperator
ownRowElement = ';'.join(areaList)
writer.writerow( (time, element['date'], element['time'], ownRowElement)
Offtopic:
This works for me:
import csv
import json
x="""[
{'lat': u'1.34039000', 'lon': u'103.70500000', 'name': u'Jurong West','forecast': u'LR'}
]"""
jsontxt = json.loads(x.replace("u'","\"").replace("'","\""))
f = csv.writer(open("test.csv", "w+"))
# Write CSV Header, If you dont need that, remove this line
f.writerow(['lat', 'lon', 'name', 'forecast'])
for jsontext in jsontxt:
f.writerow([jsontext["lat"],
jsontext["lon"],
jsontext["name"],
jsontext["forecast"],
])