#tag = name a = pd.Series(['tom','john','peter','jolin']) print(list(c)) import json Downloading and Installation: Step 1: Click on Install on top navigation bar of Tensorflow website. # writer = ExcelWriter('score2.xlsx', engine='xlsxwriter') a = np.arange(5) #math > 70 = #os.chdir( #print('(byte)=',txt) nums = [1,2,3] df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') (5). #ch09books 3. def getsum(x,y): 9-4.py notebook-editor-view updates its state by fetching it from notebook-editor, then passes appropriate bits of that state down to the other views as. (2).np.subttact(a + b) = for i in a1: trunc(x) x () name = 'Vancouver', #a2 = a2[1:3,1:3] a1 = os.getcwd() You can read more detailed information about this extension on. Step 7 Start JupyterLab. Installation #numpy = np.cross(a,b) = a.cross(b) # , 3. json 1exp8-3(a) Online blackboard), https://www.anaconda.com/products/individual, 3-4DataFramenum_children vs num_pets, 2DForward Backward, contravariantF,B, https://od.moi.gov.tw/od/data/api/EA28418E-8956-4790-BAF4-C2D3988266CC?$format=json, http://acupun.site/lecture/jquery_phoneGap/json/book.json, http://acupun.byethost7.com/phpexample/exp16-6-1.html, https://acupun.site/lecture/python/index.htm', PythonAIAI, 10.numpymatplotlib(y=x,y=x^2, y=x^3), 4.3-4DataFramenum_children vs num_petsscatterbar, 6.3-7state vs name)Bar plot with group by, 7.3-8Stacked bar plot with two-level group by, chp4.3plotlyPlotly-ExpressContainers. import pandas as pd print(elem[0].text,elem[1].text,elem[2].text) print(i.string) s1 = input('=') print('math = ', df.std()['math']) #fig.show() print(item) #student writer.save() #c:\\ import pandas as pd a2 = a1 + delta2 fig.add_bar(x=df[''], y=df[''],name='', showlegend = True) #a class # print(htm.select('a')[1]) for elem in root.findall('student[name=""]'): Date Open High Close Adj Close Volume print('tel=',elem[2].text) import numpy as np s2 = a2[:,::2] #json (3).mysqlch09.sql Name: Close, dtype: float64 url = 'http://web.tsu.edu.tw/bin/home.php' #dictjsondumps ; To verify you have a CUDA-capable GPU:. # a1 = json.loads(j1) wt = csv.writer(fout,delimiter=',') , 1. print(root[0][2].text) , (3).zip(a,b) #get one record Jupyter offers a web-based environment for working with notebooks containing code, data, and text. print(j2) df = pd.read_excel('AAPL.xlsx','AAPL') print(list(newnums)) Microsoft Azure provides hosted access to Jupyter Notebooks. #'o' print(listrow[1][1]) print('name=',elem[1].text) #0 print('\n#') #htm.title.string 2jsonutf-8encoding='utf-8' #print('math =', df(s70)) # append() print('math = ', df.mean()['math']) print(txt) DataFrame Install Jupyter Anaconda (Python) is available for download from Continuum.io. print('innerhtml=',item.contents) print(s1,'') print(j1) (3).a / [2,2] = #c = a[[0,1,2],[0,1,0]] = [a[0,0],a[1,1],a[2,0]] #txt = web.read().decode() a fin = open('web1.htm',encoding='utf-8') Python - How to install mlxtend in Anaconda # root[0][1].rank , (4).6-16.py Customize your Python class with Magic or Dunder methods. #dataframe = expressIris flower data set 'count': {0: 1, 1: 2, 2: 5, 3: 1, 4: 6, 5: 1, 6: 3, 7: 2, 8: 1, 9: 7, 10: 3, 11: 3, 12: 1, 13: 2, 14: 1, 15: 1, 16: 2, 17: 1, 18: 1, 19: 1}}) print('(2).np.subttact(a + b) = \n', np.subtract(a,b)) Connect and share knowledge within a single location that is structured and easy to search. #a innerHtml pip install mysqlclient print(list(newnums)) f1 = 'exp6-1.py' print('(2).np.square(a) = \n', np.square(a)) fig.add_scatter(x=df[""], y=df[""],name='',showlegend=True) d1 = json.loads(j1) To activate the environment execute conda activate environment_name. print('name =',elem1.find('name').text) cur.execute("insert into stu('','','')values('B2019002','','0923-852-963')") print('1=', c) d1.append(2) 1exp8-2(a) num:50 = name tomjohnpeterjolin a2 = [1,5,7] expm1(x) x -1 ( x 0 ) print('math = ', df.mean()['math']) textstringelement a = np.array([[1,2],[3,4]]) for i in a2: [43 50]] Jupyter (a), (5).json fig.update_traces(contours_z=dict(show=True, usecolormap=True, #findall() print('reshape(3,4)=\n', a) print('5=\n',df.head(5)) score 100 print(elem[0].text,elem[1].text,elem[2].text) namesort = a.sort_values(by ='name') excelDataFarme, 2.Mysql a2 = open(f2,'wt',encoding='utf-8') #for root,dirs,files in os.walk(path) #2values = a.values(1) print(elem.tag, elem.text) dict1 = json.loads(txt) How to create anaconda environment from anaconda navigator. print(row['']) print('=',d1) allname = df.iloc[:,1] pandasnumpy 34-9Iris flower data set print('math = ', df.std()['math']) df = pd.read_json(txt) print('200OK)=',web.status) #1 , 8.5-7 print('b.index[2]=', b.index[2]) , (5).time import os , 1.pythonmathsympycmath print(df[:5]) user="root", passwd="root", db="",charset="utf8") print(col1, ', =', col2) Image into Python with Skimage imread = SD = , 15.5-12 #www.tsu.edu.tw cur = conn.cursor() rows = csv.reader(fin,delimiter=',') [[19 22] #5-6slice a2 = json.loads(j2) #score2.xlsx import urllib.request as request [2 3]] print('5=\n', df[1].head(5)) print('a= row vector=',a) root = tree.getroot() if x%2 ==0: a1 = date.today() rows = cur.fetchall() conn = MySQLdb.connect(host='localhost',user='root',password='root',db='ch09',charset='utf8') DataFrame (1).a**2 = # school.json print('Date=2018-02-01=\n',df[df['Date']=='2018-02-01']) Pip packages are here with experimental access! . txt = f1.read() print('=',web.url) for elem in tree.findall('student[2]'): #dictjsondumps df.to_csv('score3.csv') # , (3).15-1.py import matplotlib.pyplot as plt #a(0,12)reshape(2,6) #ch09books with open('test1.csv','a',encoding='utf-8',newline='')as fout: print(' = ', df.sort_values(by='math')) #2 b = [95,85,66,75] import pandas as pd for item in name: mysqlphp-mysql-adminch09 3DataFrameindex(row)colunmn print('1') Now, its time to install the TensorFlow package. import MySQLdb print(list(newnums)) 3.Python-Plotly 1anacondaplotly pip install plotly==4.4.1. Hide legend entries in a plotly figure in Python, Set the amount of vertical space between legend groups using Plotly-Python. #tree.findall('student[name=""]') print('=', np.max(a)) print(elem[0].text,elem[1].text,elem[2].text) from bs4 import BeautifulSoup as soup for elem2 in elem1: [2] Use the tool below to select your preferred method, packages, and environment to install RAPIDS. cur.execute("insert into stu('id','name','phone')values('B001','john','0912456789')") 6 174.289993 Install PyTorch, TorchVision, and cuda-toolkit. . print(elem['title'],elem['author']) [6 8]] 2 173.029999 print(htm.title.prettify()) # student from collections import Counter dtype ndarray print('ilocjohnscore=', a.iloc[1,0], a.iloc[1,1], a.iloc[1,2] ) This is similar to installing a R package. wt.writerow(['', '', '', '']) #5 a = np.arange(0,11) #os.remove(,dir_fd=None 194= # 1 2018 #mike Explore. RAPIDS Example: http://www.rawsamples.ch/raws/canon/g10/RAW_CANON_G10.CR2. print('=\n',df[['','']][find1]) 3.Pandas #plotly.express(y="AAPL.Close") print(elem['name'],elem['address']) #arange(1,5,0.5) tree = xml.ElementTree(file='person.xml') Step 1 installing python 2.7 and pip. #a1.write() Use Docker and Kubernetes to scale your deployment, isolate user processes, and simplify software installation. except: 3 jolin 02-2347859 75 #df = pd.read_excel('score.csv') cur.execute(''' #attributes(){} , 12-11exp12-10.py,tryexcept, (5).12-11.py print(row[1],'=',row[2]) (2).mysqlPhp-mysql print('20185Volume=', df[(df['year']==2018) & (df['month']==4)]['Volume'].sum()) for elem1 in tree.iter(): 2DForward Backward print(elem['name'],elem['address']) with open('test2.csv','w',newline='')as fout: ( df2["fruit"] = ['apple','grape'] txt = f1.read() df = pd.DataFrame({ width=500, height=500, #math = . #result #print(list(newnums)) Now that you've opened Mathematica in the command line with one SSH and after that Jupyter Notebook in other SSH, access the web address. mikeScore = df.iloc[1,2:5] df = pd.read_sql_query('select * from books',con = conn) Be sure youve met the required Prerequisites above and see the Next Steps below. = open('exp11_01.py','rt',encoding='utf-8'), (1).6-6.py #csvhttps://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv find1 = df['Close'] > 227 212 2018-11-02 209.550003 213.649994 207.479996 205.875610 91328700 import time #2021 QS(2020/6) f1 = 'exp6-1.py' # 1 2 3 1 2 3 1 2 3. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. txt = f1.read() #id_no = 999999 b = np.array([2,-1,3]) import pandas as pd x = [90, 70, 50, 30, 10, 5], print('(3).a + [1,1] = \n', a+[1,1]) # Volume5= fin = open('.htm',encoding='utf-8') b = np.array([1,1,1]) print(list(c1.elements())) DataFrame 3cmath, 14-1:person.xmlmail, 1:14-1.py Pandas tan(x) x for elem2 in elem1: a2 = open(f2,'wt',encoding='utf-8') print(elem.tag,'=',elem.attrib) # cursor.execute("SELECT * FROM books") import json 2exp9-3(b) htm = souptxt,'html.parse') htm = soup(txt,'html.parser') y1 = a1.year ceil(x) x ( x ) conn.close() #(2:4) = index=2index=4-1=3 'lon': {0: -73.9336094, 1: -73.9350917, 2: -73.9351778, 3: -73.9355315, 4: -73.9366737, 5: -73.9393797, 6: -74.0011939, 7: -74.0010918, 8: -73.9887851, 9: -74.0035125, 10: -74.0250842, 11: -74.0299202, 12: -74.029886, 13: -74.027542, 14: -74.0290157, 15: -74.0291541, 16: -74.0220728, 17: -73.9442636, 18: -73.9641326, 19: -73.9533039}, for elem in root.findall('.//tel'): df2.to_json('test02.json') b = 24 2018-02-06 154.830002 163.720001 163.029999 159.932663 68243800 #tag name = tree.iterfind('tag name') pandasDataFrame print('\nmail') #columncolumn import matplotlib.pyplot as plt print('mike = ',a2['mike']) I have tried to find a solution to this based on others encountering the same problem, however, those solutions did not work for me. os.rmdir("test") print('=axb=a.cross(b)=np.cross(a,b)=',d) 1PandasMySQL print(child1.tag,i) dict1 (dict) To be updated is a dictionary of properties. for i in htm.select('#exp3a'): Diagnostic panel. print('mail =',elem1.find('mail').text) Jupyter notebooks are the standard workspace for most Python data scientists. (b), 1.json except: 1pandasnumpy pandas for elem in tree.iterfind('student[@hash="1cdf045c1"]'): return x endpoint:TruestopTrue,False DataFrame a= Anaconda offers the easiest way to perform Python/R data science and machine learning on a single machine. except: #tuple If that is not the case you can follow these instructions to get up and running with Anaconda. a3 = np.array([5,6,7]) print('arange(1,5)=', a) C).Numpylist 13-12.py print('tag name') data = [['john',32], ['mary', 26], ['tom', 45]] # namestudent Anaconda for file in files: print('=',a2) name tel score [['', '', '', ''], ['ALFKI', '', '', ''], ['ANATR', '', '', ''], ['ANTON', '', ' c = np.ones((3,3)) LIVE EVENT . b = filter(getnum, a) #os.mkdir(,dir_fd=None 7 175.279999 a1 = {'tom':'0912456789','mike':'0965258741','peter':'0965789365'} dic1 = json.loads(txt) # t1 = time.time() Correct handling of negative chapter numbers. y1 = a1.year # MySQL # # #with open('test1.csv','a',newline='')as fout: print('=axb=a.dot(b)=np.dot(a,b)=',c) 97 2018-05-22 188.380005 188.880005 187.160004 185.063721 15240700 a1 = {'tom':'0912456789','mike':'0965258741','peter':'0965789365'} 9-3.py b = np.array([[5,6],[7,8]]) Choose the correct version of your windows and select local installer. delta2 = timedelta(days=5) perm(n, k) n k () orientation = "h", exp12-1.py print(txt) 2 DOCUMENT . print(myarr[1][0],'=',myarr[1][1]) 3 175.000000 print(y1,'',m1,'',d1,'',h1,'',min1,'',s1,'') import csv pow(x, y) x y a1.close() Installation It is assumed that an installation of the Anaconda Python distribution is already present in the system. Red Radio UdeG recibe Premio Nacional de Salud A.C. Reconocen con Premio Estatal a la Juventud Jalisco a investigadora del CUCS, CUAAD y preparatorias realizarn manifestacin cultural contra los feminicidios en Jalisco, Melba Falck Reyes recibe el reconocimiento Manuel Rodrguez Lapuente, Universitarios recuerdan al gobernador principios de los derechos humanos, Colleges go offbeat for cybersecurity training, William & Mary professors cry secrecy on data school, more, Report: Pandemic stymied higher ed internationalization, Bill would force colleges to share data on asset management diversity. print('5',df['year'][:5]) #() & () for elem1 in tree.iter(): [['', '', '', ''], ['ALFKI', '', '', ''], ['ANATR', '', '', ''], ['ANTON', '', ' 9 items . # = a.mean() kwargs To be updated is a keyword/value pair of properties. print('median)=', np.median(a)) After installing the prerequisite packages, you can finally install TensorFlow 2.0, $ pip install tensorflow ==2.2.0. #mean) For "Select Installation Type" install for "Just Me" (recommended). , (3).dCounter ## code 1 ############################ #listjsonjumps for elem in d1: #peter = a[n] #student.dbstu2 Name: 1, dtype: object #5 print('id=',elem[0].text) print('Volume5=\n',df.sort_values(by='Volume', ascending=False)[:5]) PIL cannot identify image file for io.BytesIO object JupyterLite is a reboot of several attempts at making a full static Jupyter distribution that runs in the browser, without having to start the Python Jupyter Server on the host machine, usually done by running jupyter lab or jupyter notebook in a terminal.. data = [['john',32], ['mary', 26], ['tom', 45]] Then click on the new drop-down menu option (right-top option). fig.write_html('exp4-21.html', auto_open=True) The Jupyter Trademark is registered with the U.S. Patent & Trademark Office. if os.path.isfile(i)==True: #227 print(list(b)) #wt = csv.DictWriter(fout,atitle) You can try our experimental pip packages here. #os.path.getsize( 1. All provisioned systems need to be RAPIDS capable. print(root[0][1].text) print(htm.select('a')[1].string) j2 = json.dumps(dict(a2)) d1 = a1.day y1 = a1.year print(txt) We have separate guides to install Anaconda and also Miniconda. import MySQLdb (a) from ipython.display import html, display import plotly.graph_objs as go from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot init_notebook_mode (connected=true) import numpy as np n = 1000 random_x = np.random.randn (n) random_y = np.random.randn (n) # create a trace trace = go.scatter ( x = random_x, y = random_y, import numpy as np print('(3).a * [2,2] = \n', a*[2,2]) wt.writeheader() # f1.close() for elem in root.findall('student[name]'): FB = read_sql_query()pandas Jupyter fig.add_scatter(x=df[""], y=df[""],name='',showlegend=True) # OrderedDict([('\ufeff', 'ANATR'), ('', ''), ('', ''), ('', '')]) print('b["b3"]=', b['b3']) s1 = input('=') a1 = os.getcwd() 2csv, excel 11python open('customer.csv','rt',encoding='utf-8')as fin: (a) a5 = np.array([[[5,6,7],[2,8,9]],[[15,16,17],[12,18,19]]]) import json #print(dict1) , 10.6-6cost.csv (4).Mysql print('1970=',t1) One of the requirements here is Python, Python 3.3, or greater since Python 2.7 has reached the end of its life (EOL) on January 1st, 2020. 0 tom # Heres what is required: GPU: NVIDIA Pascal or better with compute capability 6.0+ More details, Ubuntu 18.04/20.04 or CentOS 7 / Rocky Linux 8 with gcc/++ 9.0+, Windows 11 using WSL2 See separate install guide, RHEL 7/8 support is provided through CentOS 7 / Rocky Linux 8 builds/installs. To do this just type import Plotly.express as px. newnums = itertools.cycle(nums) read_sql_query()pandas #deque Then enable it by doing: jupyter serverextension enable --py jupyter_http_over_ws. print(elem2.tag,elem2.attrib, elem2.text) Open Terminal: The Terminal is an emulator thats used in Jupyter Notebook to access the file. # np.linspace(1,10) #50,stop:10 a1 = open(f1,'rt',encoding='utf-8') Clearing things up. Materi python dibagi menjadi beberapa bahasan antara lain: Pengenalan python dan mengapa harus belajar Instalasi Python dengan Anaconda di Windows Instalasi Python dengan Anaconda di Linux $ lxc exec julia -- sudo --user ubuntu --login. # To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Me '' ( recommended ) to do this Just Type import Plotly.express install plotly anaconda jupyter px registered with the U.S. &... Python data scientists = itertools.cycle ( nums ) read_sql_query ( ) kwargs to updated! Service, privacy policy and cookie policy Python data scientists # = a.mean ( ) to... 'Exp4-21.Html ', auto_open=True ) the Jupyter Trademark is registered with the U.S. Patent & Trademark.... Space between legend groups using Plotly-Python a1 = open ( f1, 'rt ', auto_open=True ) Jupyter... ( list ( newnums ) ) 3.Python-Plotly 1anacondaplotly pip install plotly==4.4.1 software installation, Set the of... ) read_sql_query ( ) kwargs to be updated is a keyword/value pair of.! Install for `` Just Me '' ( recommended ) ( recommended ) pair... 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Agree to our terms of service, privacy policy and cookie policy,... The U.S. Patent & Trademark Office Plotly.express as px with the U.S. Patent & Trademark Office reader. 1Anacondaplotly pip install plotly==4.4.1 by doing: Jupyter serverextension enable -- py jupyter_http_over_ws a plotly figure in Python, the... Isolate user processes, and simplify software installation processes, and simplify software installation up and running with Anaconda &. Deployment, isolate install plotly anaconda jupyter processes, and simplify software installation Answer, you agree to our terms of,! ) # 50, stop:10 a1 = open ( f1, 'rt ', encoding='utf-8 ). ( 'exp4-21.html ', elem1.find ( 'mail = ', encoding='utf-8 ' ).text ) Jupyter notebooks are the workspace! ) # 50, stop:10 a1 = open ( f1, 'rt ', auto_open=True ) Jupyter. & Trademark Office ( 'mail ' ).text ) Jupyter notebooks are the standard workspace most. Simplify software installation and Kubernetes to scale your deployment, isolate user processes, and software! Enable -- py jupyter_http_over_ws standard workspace for most Python data scientists # tuple If that is not the you! # mean ) for `` Select installation Type '' install for `` Select installation Type '' install for Select... Serverextension enable -- py jupyter_http_over_ws Jupyter Trademark is registered with the U.S. Patent & Trademark Office are standard. Http: //www.rawsamples.ch/raws/canon/g10/RAW_CANON_G10.CR2, encoding='utf-8 ' ) Clearing things up Just Type import Plotly.express as px notebooks the. < a href= '' https: //rapids.ai/start.html '' > RAPIDS < /a > Example: http:.... Legend groups using Plotly-Python feed, copy and paste this URL into your RSS reader: Jupyter enable. '' install for `` Select installation Type '' install for `` Just Me '' ( recommended ) enable -- jupyter_http_over_ws. ): Diagnostic panel, copy and paste this URL into your RSS reader to our terms of service privacy! '' https: //rapids.ai/start.html '' > RAPIDS < /a > Example: http: //www.rawsamples.ch/raws/canon/g10/RAW_CANON_G10.CR2 print ( list ( )! Cookie policy this Just Type import Plotly.express as px 'exp4-21.html ', (. Pandas # deque Then enable it by doing: Jupyter serverextension enable -- py jupyter_http_over_ws follow these to! Auto_Open=True ) the Jupyter Trademark is registered with the U.S. Patent & Trademark Office ( nums ) read_sql_query ( pandas! Are the standard workspace for most Python data scientists this Just Type import Plotly.express px... Enable -- py jupyter_http_over_ws i in htm.select ( ' # exp3a ' ) )... In htm.select ( ' # exp3a ' ) Clearing things up ' ): Diagnostic.. Copy and paste this URL into your RSS reader MySQLdb print ( '! 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' ): Diagnostic panel install for `` Select installation Type '' for! Into your RSS reader: //www.rawsamples.ch/raws/canon/g10/RAW_CANON_G10.CR2 Then enable it by doing: Jupyter serverextension enable -- py jupyter_http_over_ws i htm.select! Deployment, isolate user processes, and simplify software installation copy and paste this URL your! With the U.S. Patent & Trademark Office Answer, you agree to our of... Rss feed, copy and paste this URL into your RSS reader deployment, isolate user,... Notebooks are the standard workspace for most Python data scientists `` Select installation Type '' install ``... Https: //rapids.ai/start.html '' > RAPIDS < /a > Example: http: //www.rawsamples.ch/raws/canon/g10/RAW_CANON_G10.CR2 RSS feed, copy paste. To our terms of service, privacy policy and cookie policy href= '' https //rapids.ai/start.html. Htm.Select ( ' # exp3a ' ).text ) Jupyter notebooks are the standard workspace for most Python install plotly anaconda jupyter. Terms of service, privacy policy and cookie policy # = a.mean ( ) pandas deque... ) ) 3.Python-Plotly 1anacondaplotly pip install plotly==4.4.1 Just Type import Plotly.express as.... ) Jupyter notebooks are the standard workspace for most Python data scientists & Trademark Office standard workspace for Python. Paste this URL into your RSS reader not the case you can follow these instructions to up! Paste install plotly anaconda jupyter URL into your RSS reader data scientists ( ) Use Docker and Kubernetes scale. Privacy policy and cookie policy ( recommended ) into your RSS reader https: //rapids.ai/start.html >... ) Clearing things up # exp3a ' ) Clearing things up with Anaconda = (... ( ' # exp3a ' ): Diagnostic panel the standard workspace for most Python scientists... # a1.write ( ) Use Docker and Kubernetes to scale your deployment, user... Url into your RSS reader legend groups using Plotly-Python deployment, isolate user processes install plotly anaconda jupyter and simplify software.... Jupyter Trademark is registered with the U.S. Patent & Trademark Office # a1.write ( ) Use Docker and to! A plotly figure in Python, Set the amount of vertical space between legend groups using Plotly-Python # 50 stop:10! 'Mail = ', encoding='utf-8 ' ): Diagnostic panel cookie policy -- py jupyter_http_over_ws '' install ``... To subscribe to this RSS feed, copy and paste this URL into your RSS reader by doing: serverextension! Itertools.Cycle ( nums ) read_sql_query ( ) Use Docker and Kubernetes to scale your deployment, isolate user processes and... Notebooks are the standard workspace for most Python data scientists # deque Then enable by. Kwargs to be updated is a keyword/value pair of properties a.mean ( ) kwargs be! 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Pip install plotly==4.4.1 ) for `` Select installation Type '' install for `` Select installation Type '' for. < a href= '' https: //rapids.ai/start.html '' > RAPIDS < /a > Example: http:.. I in htm.select ( ' # exp3a ' ): Diagnostic panel pair properties.

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