project strcuture refactor

data/tickers.csv

@@ -0,0 +1,233 @@
+,name,tag
+0,ACS,acs
+1,Abengoa,abengoa
+2,Atresmedia,atresmedia
+3,Acerinox,acerinox
+4,BBVA,bbva
+5,Bankinter,bankinter
+6,BME,bme
+7,Acciona,acciona
+8,Caixabank,caixabank
+9,Enagás,enagas
+10,FCC,fcc
+11,Naturgy Energy,naturgy-energy
+12,Siemens Gamesa,siemens-gamesa
+13,Grifols,grifols
+14,Ferrovial,ferrovial
+15,Red Eléctrica,red-electrica
+16,Inditex,inditex
+17,Repsol,repsol
+18,Iberdrola,iberdrola
+19,Banco Popular,banco-popular
+20,Indra,indra
+21,Mapfre,mapfre
+22,Telefónica,telefonica
+23,Mediaset,mediaset
+24,Sacyr,sacyr
+25,Banco Sabadell,banco-sabadell
+26,Santander,santander
+27,Colonial,colonial
+28,Técnicas Reunidas,tecnicas-reunidas
+29,OHL,ohl
+30,IAG,iag
+31,Ebro Foods,ebro-foods
+32,Endesa,endesa
+33,Amadeus,amadeus
+34,Bankia,bankia
+35,DIA,dia
+36,Vértice 360,vertice-360
+37,Rovi,rovi
+38,GAM,gam
+39,Solaria,solaria
+40,Papeles Y Cartones,papeles-y-cartones
+41,Airtificial Intelligence,airtificial-intelligence
+42,Alantra Partners,alantra-partners
+43,Alba SA,alba-sa
+44,PRISA,prisa
+45,Meliá Hotels,melia-hotels
+46,Empresarial San Jose,empresarial-san-jose
+47,Nueva Expresion,nueva-expresion
+48,Audax Renovables,audax-renovables
+49,Adveo Group,adveo-group
+50,Miquel y Costas,miquel-y-costas
+51,Catalana Occidente,catalana-occidente
+52,Service P.S.,service-p.s.
+53,ENCE,ence
+54,Construcciones y Auxiliar,construcciones-y-auxiliar
+55,Urbas,urbas
+56,Insur,insur
+57,Quabit,quabit
+58,Lingotes Especiales,lingotes-especiales
+59,Iberpapel,iberpapel
+60,Bodegas Riojanas,bodegas-riojanas
+61,Adolfo Domínguez,adolfo-dominguez
+62,Realia,realia
+63,Nyesa Valores Corp,nyesa-valores-corp
+64,Clínica Baviera,clinica-baviera
+65,Reno De Medici,reno-de-medici
+66,Nicolás Correa,nicolas-correa
+67,Cie Automotive,cie-automotive
+68,Renta 4,renta-4
+69,Reig Jofre,reig-jofre
+70,Ezentis,ezentis
+71,Duro Felguera,duro-felguera
+72,Zardoya,zardoya
+73,Barón de Ley,baron-de-ley
+74,Montebalito,montebalito
+75,Metrovacesa,metrovacesa
+76,NH Hoteles,nh-hoteles
+77,Faes Farma,faes-farma
+78,Tubos Reunidos,tubos-reunidos
+79,Pescanova,pescanova
+80,Grifols Pref,grifols-pref
+81,Biosearch,biosearch
+82,Viscofan,viscofan
+83,Prosegur,prosegur
+84,Almirall,almirall
+85,Vocento,vocento
+86,Vidrala,vidrala
+87,Empresarial Materiales,empresarial-materiales
+88,Tubacex,tubacex
+89,Renta Corp.,renta-corp.
+90,Fluidra,fluidra
+91,Elecnor,elecnor
+92,Azkoyen,azkoyen
+93,Aperam,aperam
+94,Sniace,sniace
+95,Ercros,ercros
+96,Codere,codere
+97,Bayer,bayer
+98,Natra,natra
+99,Amper,amper
+100,Airbus Group,airbus-group
+101,Prim,prim
+102,Deoleo,deoleo
+103,ArcelorMittal,arcelormittal
+104,Abengoa B,abengoa-b
+105,Liberbank,liberbank
+106,Ebioss Energy,ebioss-energy
+107,Entrecampos Cuatro,entrecampos-cuatro
+108,PETROBRAS PN,petrobras-pn
+109,America Movil,america-movil
+110,BRADESPAR ON,bradespar-on
+111,BRADESPAR PN,bradespar-pn
+112,BRASKEM PNA,braskem-pna
+113,COPEL PNB,copel-pnb
+114,ELETROBRAS ON,eletrobras-on
+115,ELETROBRAS PNB,eletrobras-pnb
+116,PETROBRAS ON,petrobras-on
+117,USIMINAS ON,usiminas-on
+118,USIMINAS PNA,usiminas-pna
+119,VALE ON,vale-on
+120,Alfa,alfa
+121,Grupo Elektra,grupo-elektra
+122,Grupo Financiero Banorte,grupo-financiero-banorte
+123,TV Azteca Cpo,tv-azteca-cpo
+124,Frances,frances
+125,CEMIG PN,cemig-pn
+126,BRADESCO PN EJ N1 ,bradesco-pn-ej-n1-
+127,GERDAU PN N1,gerdau-pn-n1
+128,Volcan,volcan
+129,1nkemia IUCT SA,1nkemia-iuct-sa
+130,Ab-Biotics,ab-biotics
+131,Altia,altia
+132,ADL Bionatur,adl-bionatur
+133,Catenon,catenon
+134,Euroespes,euroespes
+135,Eurona,eurona
+136,Griñó Ecologic,grino-ecologic
+137,Masmovil Ibercom,masmovil-ibercom
+138,Imaginarium,imaginarium
+139,Medcom Tech,medcom-tech
+140,Neuron,neuron
+141,Secuoya,secuoya
+142,Zinkia,zinkia
+143,eDreams,edreams
+144,Lar España,lar-espana
+145,Hispania,hispania
+146,Applus,applus
+147,Merlin Properties,merlin-properties
+148,Facephi,facephi
+149,Logista,logista
+150,Cerbium,cerbium
+151,Home Meal,home-meal
+152,Aena,aena
+153,Uro Property Holdings,uro-property-holdings
+154,NBI Bearings Europe,nbi-bearings-europe
+155,Naturhouse,naturhouse
+156,Cellnex Telecom,cellnex-telecom
+157,Talgo,talgo
+158,Euskaltel SA,euskaltel-sa
+159,Fidere Patrimonio SOCIMI SA,fidere-patrimonio-socimi-sa
+160,Grenergy Renovables SA,grenergy-renovables-sa
+161,Inclam CO2 SA,inclam-co2-sa
+162,Trajano Iberia Socimi SA,trajano-iberia-socimi-sa
+163,Lleidanetworks Serveis Telematics,lleidanetworks-serveis-telematics
+164,Autonomy Spain Real Estate Socimi S,autonomy-spain-real-estate-socimi-s
+165,Obsido Socimi SA,obsido-socimi-sa
+166,Pharma Mar,pharma-mar
+167,Gigas Hosting SA,gigas-hosting-sa
+168,Neol Biosolutions SA,neol-biosolutions-sa
+169,Agile Content SA,agile-content-sa
+170,Think Smart SA,think-smart-sa
+171,Zambal Spain Socimi SA,zambal-spain-socimi-sa
+172,Oryzon Genomics SA,oryzon-genomics-sa
+173,Tecnoquark Trust SA,tecnoquark-trust-sa
+174,Clerhp Estructuras,clerhp-estructuras
+175,Corpfin Capital Prime Retail III,corpfin-capital-prime-retail-iii
+176,Global Dominion,global-dominion
+177,Telepizza,telepizza
+178,Parques Reunidos,parques-reunidos
+179,Jaba I Inversiones,jaba-i-inversiones
+180,Corporacion Geo SAB,corporacion-geo-sab
+181,Silvercode Investments,silvercode-investments
+182,Coca-Cola European,coca-cola-european
+183,Asturias Retail,asturias-retail
+184,Vitruvio Real Estate,vitruvio-real-estate
+185,Isc Fresh Water,isc-fresh-water
+186,Quonia SOCIMI,quonia-socimi
+187,Atrys Health,atrys-health
+188,Voztelecom Oigaa360,voztelecom-oigaa360
+189,GMP Property,gmp-property
+190,Optimum Re Spain,optimum-re-spain
+191,CommCenter,commcenter
+192,ECG,ecg
+193,Clever Global,clever-global
+194,Mondo TV,mondo-tv
+195,Pangaea Oncology,pangaea-oncology
+196,VBARE Iberian Properties,vbare-iberian-properties
+197,Ores Socimi,ores-socimi
+198,Prosegur Cash,prosegur-cash
+199,Neinor Homes,neinor-homes
+200,Gestamp,gestamp
+201,Optimum III Value Added,optimum-iii-value-added
+202,Asturiana de Laminados,asturiana-de-laminados
+203,Unicaja Banco,unicaja-banco
+204,GGC,ggc
+205,Numulae Gestion de Servicios,numulae-gestion-de-servicios
+206,Borges Agricultural,borges-agricultural
+207,AM Locales Property,am-locales-property
+208,Grupo Ortiz,grupo-ortiz
+209,Domo Activos,domo-activos
+210,Aedas Homes,aedas-homes
+211,Netex Knowledge,netex-knowledge
+212,Greenalia,greenalia
+213,Student Properties,student-properties
+214,Heref Habaneras,heref-habaneras
+215,Robot,robot
+216,Tempore Properties,tempore-properties
+217,Serrano 61 Desarrollo,serrano-61-desarrollo
+218,Ap67 Socimi,ap67-socimi
+219,Tier1,tier1
+220,Torbel Investmentד,torbel-investmentd
+221,Quid Pro Quo Alquiler,quid-pro-quo-alquiler
+222,Excem Socimi,excem-socimi
+223,Castellana Properties,castellana-properties
+224,Testa Residencial,testa-residencial
+225,Berkeley Energy,berkeley-energy
+226,Alquiber Quality,alquiber-quality
+227,Go Madrid Benz,go-madrid-benz
+228,Arima Real Estate,arima-real-estate
+229,Amrest,amrest
+230,Atom Hoteles,atom-hoteles
+231,Solarpack Corporacion Tecnologica,solarpack-corporacion-tecnologica

__init__.py → investing_scrapper/__init__.py

@@ -5,17 +5,16 @@
 import requests
 from bs4 import BeautifulSoup
 
-import tickers as ts
-import user_agent as ua
-from data import Data
+from investing_scrapper import user_agent as ua, tickers as ts
+from investing_scrapper.data import Data
 
 
 def get_recent_data(ticker):
     if os.path.exists('tickers.csv') is False:
         tickers = ts.get_ticker_names()
         ts.convert_tickers_into_csv(tickers)
 
-    tickers = pd.read_csv('tickers.csv')
+    tickers = pd.read_csv('../data/tickers.csv')
 
     for item in tickers:
         if item['name'] == ticker:
@@ -90,7 +89,4 @@ def get_historical_data(ticker, start, end):
             df = pd.DataFrame.from_records([value.to_dict() for value in result])
             df.set_index('Date', inplace=True)
 
-            return df
-
-
-print(get_historical_data('bbva', '10/10/2010', '10/10/2012'))
+            return df

tickers.py → investing_scrapper/tickers.py

@@ -3,7 +3,7 @@
 import unidecode
 from bs4 import BeautifulSoup
 
-import user_agent as ua
+from investing_scrapper import user_agent as ua
 
 
 def get_ticker_names():
@@ -47,4 +47,4 @@ def get_ticker_names():
 
 def convert_tickers_into_csv(data):
     df = pd.DataFrame(data)
-    df.to_csv('tickers.csv', index=True)
+    df.to_csv('../data/tickers.csv', index=True)

user_agent.py → investing_scrapper/user_agent.py

@@ -2,7 +2,7 @@
 
 
 def get_random():
-    file = 'user-agent-list.txt'
+    file = '../data/user-agent-list.txt'
 
     with open(file, 'r') as f:
         lines = f.readlines()

setup.py

@@ -0,0 +1,13 @@
+from setuptools import setup
+
+setup(
+    name='investing_scrapper',
+    version='0.1',
+    packages=['', 'investing_scrapper'],
+    url='',
+    license='MIT License',
+    author='Álvaro Bartolomé',
+    author_email='[email protected]',
+    description='This is a scrapping tool that retrieves continuous Spanish stock market information from https://es.investing.com, into a Pandas DataFrame.',
+    install_requires=['requests', 'pandas', 'beautifulsoup4', 'unidecode']
+)