15 Mea Paahana Hoʻoheheʻe ʻikepili maikaʻi loa, lako polokalamu a me nā pae

ʻIke wau i ka hoʻonāukiuki a me ka hoʻopau manawa i ka unuhi ʻana i ka ʻikepili mai nā ʻano kumu like ʻole:

• paena
• i hōkeo 'ikepili
• palapala
• a me nā API.

A e ʻoiaʻiʻo, ke hana ʻoe i ka ʻikepili ʻikepili, nā papahana noiʻi, a i ʻole ke kūkulu ʻana i nā pipeline data, he mea koʻikoʻi ka loaʻa ʻana o ka ʻikepili pololei a hoʻonohonoho.

Me ka ʻole o nā mea hana pono, hiki iā ʻoe ke hoʻopau i ka ʻike piha ʻole, ʻino, a i ʻole ka wā kahiko, hiki ke alakaʻi i nā ʻike hewa a i ʻole nā ​​​​hoʻoholo.

ʻO ia ke kumu i hele mai ai au e kaʻana like me ʻoe i nā mea hana ʻikepili ʻikepili maikaʻi loa 15 ma waho.

E maʻalahi lākou i kou ola ma ka hoʻomaʻamaʻa ʻana i ke kaʻina hana, ka mālama ʻana i ka nui o ka ʻikepili, a me ka hoʻomaʻemaʻe a me ka hoʻololi ʻana i ka ʻikepili i unuhi ʻia no ʻoe.

E hāʻawi mai iaʻu i nā pepeiao a pau inā ʻoe he ʻikepili ʻikepili, mea noiʻi, mea hoʻomohala, a i ʻole kekahi mea pono e hoʻopaʻa lima i ka ʻikepili hilinaʻi.

Hoʻomaka mākou me kā mākou ʻōlelo aʻoaʻo kiʻekiʻe - Bright Data.

1. ʻIkepili Bright

(7 lā hoʻokolokolo no nā hui i hoʻopaʻa ʻia)

I ka hiki ʻana mai i ka ʻikepili ʻikepili pūnaewele, ʻo Bright Data ka hana maoli.

Loaʻa iā lākou kahi hui piha o nā hāʻina e kōkua iā ʻoe e hōʻiliʻili i ka ʻikepili pūnaewele lehulehu ma ka nui. A hana lākou me ka manaʻo nui i ka ʻike, hoʻokō, a me nā hana kūpono.

ʻO ka mea mua, e kamaʻilio e pili ana i kā lākou pūnaewele proxy.

Hāʻawi ʻo Bright Data i ke komo ʻana i kahi pūnaewele nui o nā proxies—noho, datacenter, ISP, a me nā proxies mobile mai 195 mau ʻāina. Me kēia mau proxies, hiki iā ʻoe ke kāpae i nā geo-restrictions, nā poloka IP, a me nā mea pale ʻē aʻe e like me ka luna.

Hāʻawi pū ka Bright Data i ka mana ʻūmiʻi pūnaewele nā mea hana e hoʻomaʻamaʻa i ka ʻili ʻikepili.

ʻO kā lākou Web Scraper IDE (Integrated Development Environment), no ka laʻana, a me ka Scraping Browser e ʻae iā ʻoe e unuhi i ka ʻikepili mai nā pūnaewele me ka ʻole o ke kākau ʻana i kahi laina code.

A no ka poʻe makemake e noho ma luna o nā hopena ʻenekini huli, ʻo ka SERP API o Bright Data he mea hoʻololi pāʻani.

Hāʻawi ia iā ʻoe e kiʻi i ka ʻikepili hualoaʻa ʻenekini, me nā papa inoa organik a me nā uku, ma kahi ʻano i kūkulu ʻia.

Akā e kali, ʻoi aku ka mea hou aʻe!

Hāʻawi pū ʻia ʻo Bright Data i kahi hōʻiliʻili nui o nā ʻikepili i kālai mua ʻia ma nā ʻoihana like ʻole, me ka e-commerce, kālā, mālama olakino, a me nā mea hou aku.

Hiki iā ʻoe ke mākaʻikaʻi a kūʻai i kēia mau ʻikepili a i ʻole e noi i ka hōʻiliʻili ʻikepili maʻamau no kāu mau pono kikoʻī.

ʻO nā hiʻohiʻona kiʻekiʻe o ka ʻikepili Bright

• ʻO nā hana hōʻiliʻili ʻikepili kūpono a kūpono hoʻi (e mālama nui lākou i kēia mea)
• ʻO ka wai IP nui me ka 72 miliona mau IP noho
• ʻO nā koho hulina kiʻekiʻe no ka hōʻiliʻili ʻike kikoʻī (zip code, kūlanakauhale, ASN, etc.)
• ʻO nā ʻōnaehana paʻa no ka manawa kiʻekiʻe a me ka wikiwiki wikiwiki
• Kākoʻo piha a me nā kumuwaiwai

2. ʻOheʻe

(Hoʻolālā manuahi, hoʻāʻo 14 lā ma nā hoʻolālā uku)

ʻO Octoparse kahi mea hoʻolaha unuhi ʻikepili pūnaewele mea hana e hiki ai i nā mea a pau ke ʻimi i ka ʻikepili mai nā pūnaewele.

ʻO kāna hiʻohiʻona hiʻohiʻona he hiʻohiʻona hiʻohiʻona, kiko-a-kaomi e hoʻohālike i ke ʻano nānā pūnaewele kanaka, hiki iā ʻoe ke unuhi i nā mea ʻikepili i makemake ʻia ma ke kaomi wale ʻana iā lākou i loko o ka polokalamu.

ʻOiai ʻoi aku ka maikaʻi o ka mea hoʻohana, mamao loa ʻo Octoparse i ka palena o kona hiki.

Hiki iā ia ke mālama i nā pūnaewele static a me nā pūnaewele ikaika e hoʻohana ana i nā ʻenehana e like me AJAX, ka ʻōwili pau ʻole, nā kaʻina hōʻoia hōʻoia, a me nā mea hou aku.

ʻIke ʻokoʻa a unuhi ʻo Octoparse i ka ʻikepili mai kēia mau hale pūnaewele paʻakikī.

No ka hoʻokō ʻana i nā pono kīwī pūnaewele nui, hāʻawi ʻo Octoparse i kahi lawelawe ʻohi ʻana i ke ao e hoʻohana ana i ka mana computing i hāʻawi ʻia ma nā kikowaena he nui. ʻAe kēia iā ʻoe e ʻohi i ka ʻikepili mai nā miliona o nā ʻaoʻao pūnaewele i nā wikiwiki kiʻekiʻe.

Ke lawe ʻia ka ʻikepili, hāʻawi ʻo Octoparse i nā koho hoʻoiho maʻalahi me nā faila Excel, CSV, HTML, a me TXT, a me ka hoʻopili pololei ʻana me nā waihona e like me MySQL, SQL Server, a me Oracle ma o kahi API.

ʻO nā hiʻohiʻona kiʻekiʻe o Octoparse

• ʻIkeʻike, code-free point-and-click data extraction interface
• Kākoʻo i nā pūnaewele static a me ka ikaika me AJAX, logins, scrolling infinite
• ʻO ka lawelawe ʻohi ʻana i ke ao no ka ʻili ʻana i ka ʻili nui
• Nui nā ʻano hoʻopuka ʻikepili a me ka hoʻohui ʻana i ka waihona ma o API
• ʻO ka huli ʻana IP i kūkulu ʻia a me ke kākoʻo proxy e kāpae i nā palena
• Hoʻonohonoho i nā mana no ka unuhi ʻana i ka ʻikepili maʻemaʻe
• ʻO nā mea hana kiʻekiʻe e like me RegEx, XPath, a me ka hoʻokuʻu ʻana i ka waihona waihona auto

3. Apify

(Hoʻolālā manuahi)

ʻO Apify kahi kahua hoʻokumu i ke ao e hoʻohauʻoli ai i ka ʻili pūnaewele, ka ʻohi ʻikepili, a me ka hana ʻana i nā hana pūnaewele.

A ʻo ka hapa maikaʻi loa? ʻAʻole pono ʻoe e lilo i wizard coding e hoʻohana ai.

Loaʻa iā Apify kēia mea weliweli i kapa ʻia ʻo "Actors". Ua like lākou me nā palapala i kūkulu mua ʻia a i ʻole nā ​​​​mea hana e hiki ke hoʻopaʻa i nā ʻano hana ʻoki pūnaewele a me nā hana automation.

Hiki iā ʻoe ke hoʻohana i nā mea mai kā lākou waihona nui a i ʻole hana i kāu mau mea hana maʻamau inā makemake ʻoe.

Eia naʻe kahi maikaʻi loa - kūkulu ʻia ʻo Apify no ka scalability.

Hāʻawi kā lākou ʻoihana kapuaʻi iā ʻoe e hoʻokele i nā papahana scraping pūnaewele nui loa, me nā hiʻohiʻona e like me ka hoʻololi ʻana i ka proxy e kāpae i nā ana anti-scraping.

A inā he mea hoʻomohala ʻoe, hiki iā ʻoe ke hoʻolaha i kāu mau mea hana ʻōpala ma kā lākou wahi kūʻai a loaʻa i kahi loaʻa passive.

ʻO nā hiʻohiʻona kiʻekiʻe o Apify

• ʻO ka hiki ke hoʻopaʻa ʻia i kekahi pūnaewele
• ʻO ka polokalamu kele pūnaewele poʻo ʻole no nā ʻaoʻao i hāʻawi ʻia e JavaScript
• ʻO ka unuhi ʻikepili a me nā mea hana hoʻololi e hoʻomaʻemaʻe i kēlā ʻikepili ʻino
• Ka nānā ʻana o ka pūnaewele a me nā hoʻolaha e mālama iā ʻoe i ka loop
• Mea hoʻomohala me nā API, SDK, a me ke kākoʻo no nā ʻōlelo papahana kaulana

4. Elima

(Hoʻolālā manuahi, hoʻāʻo 14 lā ma nā hoʻolālā uku)

ʻO Fivetran kahi kahua hoʻoneʻe ʻikepili automated e mālama iā ʻoe i ka nui o ka manawa a me ke poʻo i ka wā e loaʻa ai ka ʻikepili mai nā kumu like ʻole.

Eia ke kumu o ka hana ʻana o Fivetran:

Hāʻawi ia ma luna o 400 mau mea hoʻohui i kūkulu mua ʻia e hiki ke unuhi i ka ʻikepili mai nā kumu like ʻole āu e noʻonoʻo ai - nā ʻikepili, nā polokalamu SaaS, nā kapuaʻi kapuaʻi, inoa ʻoe.

A ʻo ka ʻāpana maikaʻi loa?

Hoʻopili ʻo Fivetran i ke kaʻina hoʻoiho holoʻokoʻa a me ka hoʻouka ʻana, ka lawelawe ʻana i nā loli schema, hoʻoponopono ʻikepili, hoʻonui hou, a me kēlā jazz āpau.

Akā ʻaʻole ʻo ia wale nō - mālama pū ʻo Fivetran i nā loli ʻikepili no ʻoe.

Hoʻohui pono ia me ka dbt Core, no laila hiki iā ʻoe ke hoʻokele i kāu mau hiʻohiʻona dbt maʻamau i loko o Fivetran.

A i ka wā e pili ana i ka palekana a me ka hoʻokō ʻana, ʻaʻole ʻino ʻo Fivetran. Hoʻopili ʻo ia i nā lula pilikino ʻikepili nui e like me GDPR, HIPAA, a me PCI, e hōʻoia ana i ka paʻa paʻa ʻana o kāu ʻikepili koʻikoʻi.

Ma luna o kēlā, kūkulu ʻia ʻo Fivetran e hoʻonui i ka maʻalahi i ka ulu ʻana o ka nui o kāu ʻikepili, a hoʻohui pū me kāu waihona ʻikepili i loaʻa, e ʻae iā ʻoe e hoʻonui i kona hiki.

ʻO nā hiʻohiʻona kiʻekiʻe o Fivetran

• ʻO ka ʻohi ʻikepili a me ka hoʻouka ʻana mai 400+ mau mea hoʻohui i kūkulu mua ʻia
• Mālama i nā hoʻololi hoʻolālā, hoʻoponopono ʻikepili, a me nā mea hou i hoʻonui ʻia
• Nā hoʻololi ʻikepili i kūkulu ʻia me ke kākoʻo no nā kumu hoʻohālike dbt Core
• Ka palekana a me ka hoʻokō pono (GDPR, HIPAA, PCI, etc.)
• Hoʻohui pū me kāu waihona ʻikepili i loaʻa a ʻae i nā hoʻonui maʻamau

5. Airbyte

(14 lā hoʻāʻo)

ʻO Airbyte kahi kahua ākea e maʻalahi loa ka huki ʻana i ka ʻikepili mai nā ʻano kumu like ʻole a hoʻouka i loko o kāu mau hale waihona ʻikepili, loko, a me nā wahi ʻē aʻe.

Loaʻa iā Airbyte kahi waihona puke nui ma mua o 300 mau mea hoʻohui i kūkulu mua ʻia no ka ʻikepili, nā polokalamu SaaS, nā lawelawe mālama kapua, a me nā mea hou aku.

No laila ma kahi e noho ai kāu ʻikepili, hiki iā Airbyte ke unuhi iā ia no ʻoe me nā kaomi liʻiliʻi.

Akā, ʻaʻole wale ia.

Loaʻa iā Airbyte kēia hiʻohiʻona maikaʻi i kapa ʻia ʻo Connector Development Kit (CDK). Me kēia, hiki iā ʻoe ke kūkulu i nā mea hoʻohui maʻamau no kekahi kumu ʻikepili a i ʻole kahi e hele ai i loko o 30 mau minuke.

A i ka wā e hoʻoneʻe maoli ai i kāu ʻikepili a puni, hāʻawi ʻo Airbyte iā ʻoe i kahi ton o ka maʻalahi.

Hiki iā ʻoe ke hana i nā hōʻoluʻolu piha, nā syncs incremental, a i ʻole hopu i nā loli i ka manawa maoli me CDC (Change Data Capture).

Eia hou, hiki iā ʻoe ke hoʻololi i kāu ʻikepili ma ka lele me SQL a i ʻole hoʻohui pū me nā mea hana e like me dbt.

ʻO ka hoʻonohonoho ʻana i nā pipeline data a me ka nānā ʻana iā lākou he mea maʻalahi hoʻi. Hiki iā ʻoe ke hoʻonohonoho i nā hana, loaʻa nā mākaʻikaʻi inā hewa kekahi mea, a koho e hoʻokipa iā ʻoe iho i ka mana open-source a i ʻole e hoʻohana i ka lawelawe ʻo Airbyte Cloud.

Nā hiʻohiʻona kiʻekiʻe o Airbyte

• Hale waihona mea hoʻohui nui no nā tona o nā kumu ʻikepili a me nā wahi e hele ai
• Hoʻomohala ʻia nā mea hoʻohui maʻamau i 30 mau minuke me ka CDK
• Hoʻopili hou i ka ʻikepili maʻalahi: hōʻoluʻolu piha, hoʻonui, CDC
• Nā mana hoʻololi ʻikepili i kūkulu ʻia
• Ka hoʻonohonoho ʻana, ka nānā ʻana, a me ka makaʻala
• Nā koho ʻāpua a mālama ʻia

6. ʻIkepili Hevo

(14 lā hoʻāʻo)

ʻO ka Hevo Data kahi kahua no-code e maʻalahi loa ka neʻe ʻana i ka ʻikepili mai nā kumu like ʻole i kāu waihona ʻikepili a i ʻole ka waihona.

Hoʻokaʻawale ia i ke kaʻina holoʻokoʻa o ka unuhi ʻana, hoʻololi, a me ka hoʻouka ʻana (ETL) i kāu ʻikepili i hiki iā ʻoe ke nānā aku i ka nānā ʻana.

Hoʻopili ia i nā kumu ʻikepili ma luna o 150 - mai nā waihona a me nā polokalamu SaaS i ka mālama ʻana i ke ao a me nā lawelawe streaming - a huki i kēlā ʻikepili i kahi kikowaena kikowaena.

ʻO kekahi o nā mea ʻoluʻolu loa e pili ana i ka Hevo Data ʻo ia kona hiki i ka manawa maoli.

Hiki iā ia ke hoʻomau i kāu waihona ʻikepili me ka ʻikepili hou mau, no laila ke hana mau nei ʻoe me ka ʻike hou loa.

Eia kekahi, ʻike ʻokoʻa ʻo ia i nā loli i kāu schema data a hoʻololi e like me ia, e hoʻopakele iā ʻoe mai ka palapala palapala lima luhi.

Inā pono kāu ʻikepili i kahi hoʻomaʻemaʻe ma mua o ka hoʻouka ʻana, ua loaʻa iā Hevo Data kou kua me nā hoʻololi preload.

Hiki iā ʻoe ke hoʻohana i kāna interface drag-and-drop a i ʻole kākau i ka code Python e hoʻomaʻemaʻe a hōʻano i kāu ʻikepili e like me kou makemake.

Nā hiʻohiʻona kiʻekiʻe o ka ʻikepili Hevo

• ʻAʻohe code, kauo-a-hoʻokuʻu no ka hana ʻana i nā pipeline data
• Ka hoʻoili ʻikepili manawa maoli a hoʻololi i ka hopu ʻikepili (CDC)
• Ka hoʻomalu ʻana i ka schema a me ka palapala ʻāina
• E hoʻouka mua i nā hoʻololi ʻikepili me Python a i ʻole kahi hiʻohiʻona ʻike
• Hoʻokumu ʻia nā ʻōnaehana kapua e pili ana i ka haʻahaʻa hana
• Ka nānā ʻana a me ka makaʻala no nā pilikia pipeline

7. Diffbot

(Hoʻolālā manuahi)

Hana wale ʻo Diffbot i nā mea liʻiliʻi a hana pololei lākou, ʻokoʻa - ka ʻohi ʻikepili pūnaewele a me ke kūkulu ʻana i nā kiʻi ʻike.

ʻO ka mea mua, ʻoi aku ka nui o kā lākou Knowledge Graph. Ke kamaʻilio nei mākou e pili ana i kahi hōʻiliʻili o nā mea ʻoi aku ma mua o 10 biliona a me 2 trillion ʻoiaʻiʻo, i unuhi ʻia mai ka pūnaewele.

A loaʻa i kēia, ke hoʻomau mau nei lākou i kēia ʻIke ʻIke i kēlā me kēia 3-5 mau lā. No laila, ʻike ʻoe ke kiʻi nei ʻoe i ka ʻikepili hou.

Hiki iā ʻoe ke paʻi i ka ʻikepili ma o kā lākou API a hoʻohana iā ia no nā ʻano mea ʻoluʻolu e like me ka ʻike mākeke, ka nānā ʻana i nā nūhou, a me ke aʻo ʻana i kāu mau hiʻohiʻona aʻo mīkini.

Akā ʻaʻole wale kēlā!

Loaʻa iā Diffbot kēia mau killer Automatic Extraction API e hiki ke huki i ka ʻikepili i kūkulu ʻia mai kekahi pūnaewele a i ʻole URL.

Hoʻohana kēia poʻe i kekahi ʻike kamepiula pae aʻe a me ka hoʻoponopono ʻōlelo kūlohelohe e ʻike a unuhi i ka ʻike pili, inā he kikokikona, nā kiʻi, ke kumu kūʻai, nā loiloi, inoa ʻoe.

I kēia manawa, e kamaʻilio e pili ana i kā lākou pāʻani NLP. Hiki iā Diffbot ke unuhi i nā mea i kūkulu ʻia, nā pilina, a me nā manaʻo mai nā kikokikona kahiko.

No laila, hiki iā ʻoe ke hana i kāu mau kiʻi ʻike ponoʻī mai nā ʻatikala, nā hōʻike, nā pou media kaiapili, a i ʻole nā ​​​​mea āpau āu e moe nei.

ʻO nā hiʻohiʻona kiʻekiʻe o Diffbot

• ʻIke ʻIke Nui me 10 biliona+ hui a me 2 trillion ʻoiaʻiʻo
• Nā API hoʻoemi ʻakomi ikaika no ka ʻohi ʻikepili i kūkulu ʻia
• Crawlbot no ka kolo pūnaewele nui a me ka ʻohi ʻikepili
• Hiki i ka NLP kiʻekiʻe no ka unuhi ʻana i nā hui, nā pilina, a me nā manaʻo mai ka kikokikona
• ʻO ka hoʻonuiʻana i kaʻikepili a me ka hoʻohuiʻana me nā mea hana a me nā paepae kaulana

8. ʻAi ʻAi

(Hoʻāʻo manuahi me 1000 mau kelepona API manuahi)

ʻO ScrapingBee kahi hoʻonā hoʻoheheʻe pūnaewele me kahi API hoʻohana i nā mea hoʻomohala e unuhi i ka ʻikepili mai nā pūnaewele.

Hāʻawi ia i kahi ʻano o nā hiʻohiʻona e lanakila ai i nā pilikia maʻamau i ka wā o ka ʻimi ʻana i ka pūnaewele, e like me ka pale ʻana i ka IP, ka unuhi JavaScript, a me ka hoʻonā CAPTCHA.

Me ScrapingBee, ʻaʻole pono ʻoe e hopohopo e pili ana i ka hoʻopaʻa ʻia ʻana a i ʻole ka hoʻopili ʻana i nā palapala noi ʻaoʻao hoʻokahi paʻakikī.

Mālama ka API i ke kaʻina hana ʻōpala pūnaewele holoʻokoʻa, me ka hoʻokele proxy, ka unuhi JavaScript, a me ka hoʻonā CAPTCHA.

ʻO nā mea a pau āu e hana ai, ʻo ka hāʻawi ʻana i ka URL, a na kā lākou API e unuhi i ka ʻikepili āu e pono ai ma kahi ʻano maʻalahi e hana pū me, e like me JSON a i ʻole HTML.

E maʻalahi e like me ka mea.

Loaʻa iā lākou kahi pūnāwai o nā proxies rotating, e komo pū ana me nā proxies noho a me ka premium, no laila hiki iā ʻoe ke ʻimi me ka inoa ʻole me ka hopohopo ʻole e pili ana i nā poloka IP.

Pono ʻoe e kaomi i nā pihi, ʻōwili i nā ʻaoʻao, a i ʻole e hana i kahi ʻōpala holomua?

ʻaʻole pilikia! Hāʻawi ʻo ScrapingBee iā ʻoe e hoʻokō i nā snippets JavaScript maʻamau. Hiki iā ʻoe ke ʻimi i nā ʻaoʻao hopena ʻimi me ka hoʻohana ʻana i kā lākou Google Search API.

ʻO nā hiʻohiʻona kiʻekiʻe o ScrapingBee

• He API ikaika no ka unuhi ʻana i ka ʻikepili mai nā pūnaewele me ka hāʻawi ʻana i ka URL
• Hoʻohana i nā mākaʻikaʻi poʻo ʻole e hoʻolilo i nā pūnaewele JavaScript-kaumaha
• Loaʻa i nā proxies huli ʻana, me nā proxies noho a me ka uku
• Hoʻoholo i nā CAPTCHA e kāʻalo i kēia ana anti-scraping maʻamau
• ʻAe ʻia ka hoʻokō ʻana i nā snippets JavaScript maʻamau no ka ʻoki ʻana i ka holomua
• Wehe i ka ʻikepili i kūkulu ʻia ma nā ʻano like ʻole (HTML, JSON, XML)
• Hāʻawi i kahi API no ka ʻohi ʻana i nā hopena Huli Google

9. Docparser

(14 lā hoʻāʻo)

ʻO Docparser kahi polokalamu kapuaʻi e hoʻohana ana i ka OCR (Optical Character Recognition) e unuhi i ka ʻikepili mai nā palapala e like me PDF, nā faila Word, a me nā kiʻi scanned.

Loaʻa iā ia kahi mea hoʻohana-friendly interface e hiki ai iā ʻoe ke wehewehe i nā lula parsing a unuhi i ka ʻikepili me ka ʻole o ke kākau ʻana i kahi laina code.

ʻAʻole pono ʻoe e lilo i wizard coding e hoʻohana iā Docparser. E hoʻouka wale i kāu mau palapala a hoʻokuʻu i kāna hana kilokilo.

Loaʻa iā Docparser nā kānāwai i kūkulu mua ʻia no ka unuhi ʻana i ka ʻikepili i hōʻano ʻia e like me nā lā, nā leka uila, nā helu invoice, a me nā mea hou aʻe, i hana ʻia i nā ʻano palapala kikoʻī.

Inā ʻaʻole ʻoki nā lula i kūkulu mua ʻia, hiki iā ʻoe ke hana i kāu mau lula parsing maʻamau i 100% kūpono i kāu mau pono.

Ke hana nei me nā hoʻolālā ʻikepili paʻakikī e like me nā papa a me ka hana hou ʻana i nā ʻano kikokikona? Ua uhi ʻo Docparser iā ʻoe.

ʻIke ʻino nā palapala i nānā ʻia? Hiki iā Docparser ke hoʻomaʻemaʻe iā lākou, hoʻololi i nā ʻaoʻao, wehe i ka walaʻau, a hoʻopaʻa i nā kiʻi no ka hana ʻoi aku ka maikaʻi o ka OCR.

Hiki iā ʻoe ke hoʻohui iā Docparser i kāu mau ʻōnaehana ʻē aʻe me ka hoʻohana ʻana i kāna API a i ʻole webhooks, a lawe aku i ka ʻikepili i nā ʻano like ʻole e like me CSV, Excel, JSON, a me XML.

ʻO nā hiʻohiʻona kiʻekiʻe o Docparser

• ʻO ka unuhi ʻana i ka ʻikepili no-code mai nā palapala ma o ka ʻike maka
• Nā rula i kūkulu mua ʻia no ka unuhi ʻana i ka ʻikepili i hoʻopaʻa ʻia e like me nā lā, nā leka uila, nā helu invoice, etc
• Hiki ke hana i nā lula parsing maʻamau i kūpono i nā hihia hoʻohana kikoʻī
• Ka unuhi ʻana i nā mea laina, nā papa, a me ka hana hou ʻana i nā ʻano kikokikona mai nā palapala
• ʻO ka hoʻoponopono mua ʻana o nā kiʻi no nā palapala i nānā ʻia (deskewing, hoʻopau walaʻau, etc.)
• Hoʻohui me Zapier no ka hoʻopili ʻana i nā noi ao ʻē aʻe

10. ʻīlio ʻili

(30 lā hoʻāʻo)

ʻO Scrapingdog kahi API hoʻoheheʻe pūnaewele holoʻokoʻa e hana i ka unuhi ʻana i ka ʻikepili mai nā pūnaewele i kahi hele wāwae i ka paka.

ʻO kaʻoiaʻiʻo, ua uhi lākou i nā kumu āpau, mai ka lawelawe ʻana i nā proxies a me nā polokalamu kele a hiki i ka hoʻoponopono ʻana i nā CAPTCHA.

ʻO ka mea e hoʻokaʻawale ai iā Scrapingdog ʻo ia ka laulā o nā mea hana a me nā hiʻohiʻona.

E ʻae mai iaʻu e wehewehe iā ʻoe:

ʻO ka mea mua, loaʻa iā lākou kahi API scraping pūnaewele maʻamau e ʻae iā ʻoe e ʻohi i ka ʻikepili HTML mai kekahi pūnaewele.

Akā hāʻawi pū ʻo Scrapingdog i nā API scraper i hoʻolaʻa ʻia no nā mea pāʻani nui e like me Google, Amazon, a me LinkedIn.

Hāʻawi kēia mau API i ka ʻikepili JSON i hoʻonohonoho ʻia ma kahi pā kālā, e hoʻomaʻamaʻa ana i ka ʻili a me ka nānā ʻana i ka ʻike kikoʻī mai kēia mau kahua.

Makemake ʻoe i kā lākou Google Scraper API. Hiki iā ia ke ʻohi ma luna o 100 miliona mau hopena hulina organik i ka lā hoʻokahi.

ʻOi aku ka nui o ia mea.

Loaʻa i ka Scrapingdog kahi ʻauʻau ma luna o 40 miliona mau leka uila IP mai nā ʻāina nui. Ke hele nei kēlā me kēia noi hou i kahi IP ʻokoʻa, e hoʻonui ana i ka helu kūleʻa a pale i nā poloka.

Hāʻawi ʻo Scrapingdog i kahi Screenshot API e hiki ai iā ʻoe ke hopu i nā kiʻi piha a ʻāpana paha o nā ʻaoʻao pūnaewele.

ʻO nā hiʻohiʻona kiʻekiʻe o Scrapingdog

• General Web Scraping API e unuhi i ka ʻikepili HTML mai kekahi pūnaewele
• Nā API Scraper no Google, Amazon, a me LinkedIn
• Rotating Proxy Pool me 40 miliona mau helu IP mai nā ʻāina nui
• Ka hoʻohana ʻana i nā mākaʻikaʻi Chrome poʻo ʻole no ka hoʻolilo JavaScript
• API paʻi kiʻi no ka hopu ʻana i nā kiʻi piha a ʻāpana paha o nā ʻaoʻao pūnaewele

11. Rivery

(14 lā hoʻāʻo)

ʻO Rivery kahi mea hana ELT (extract, load, and transform) e maʻalahi ka hoʻokomo ʻana i ka ʻikepili.

Ua loaʻa iā lākou ma mua o 200 mau mea hoʻohui i kūkulu mua ʻia e ʻae iā ʻoe e hoʻopili koke i nā kumu ʻikepili i noʻonoʻo ʻia - mai nā ʻikepili a me nā API i nā noi ao a me ka waiho waihona.

A inā makemake ʻoe i kahi mea maʻamau, ʻaʻohe pilikia, ua uhi lākou iā ʻoe me kā lākou mea hoʻohui API.

Akā ʻaʻole wale ʻo Rivery e pili ana i ka loaʻa ʻana o ka ʻikepili i loko, he pro kekahi i ka hoʻololi ʻana i kēlā ʻikepili i mea hiki iā ʻoe ke hoʻohana.

Me ke kākoʻo Python maoli a me ka hoʻololi ʻana i SQL, hiki iā ʻoe ke hoʻokaʻawale i kāu kaʻina hana hoʻomākaukau ʻikepili holoʻokoʻa.

Hiki iā ʻoe ke hoʻonohonoho i nā kahe hana automated e mālama i nā mea āpau mai ka loina kūlana i ka lālā a me nā puka lou.

A i ka wā e pili ana i ka hoʻokele ʻana i kāu hana ʻikepili, aia ʻo Rivery i kou kua me ka hōʻike kikowaena, ka nānā ʻana, a me ka makaʻala.

Nā hiʻohiʻona kiʻekiʻe o Rivery

• Ma luna o 200 mau mea hoʻohui ʻikepili i kūkulu mua ʻia no ka hoʻohui maʻalahi
• Kākoʻo Python maoli a me nā hoʻololi hoʻololi SQL
• ʻO ka hoʻoponopono ʻikepili ʻakomi me ka loiloi kūlana, ka lālā, a me nā puka lou
• Ka hōʻike kikowaena, ka nānā ʻana, a me ka makaʻala no nā hana ʻikepili
• Nā kūlana palekana a me nā kūlana pilikino

12. Improvado

(ʻAʻole loaʻa ka hoʻāʻo manuahi)

ʻO Improvado ka hoʻohui ʻana i ka ʻikepili kūʻai a me ka mana analytics e maʻalahi ai kou ola.

Loaʻa iā lākou nā hoʻohui i kūkulu mua ʻia no nā kumu ʻikepili 500, no laila hiki iā ʻoe ke hoʻopili a pāʻani.

Ke loaʻa iā Improvado kāu ʻikepili, hoʻomaʻemaʻe ia, hoʻololi, a hoʻomaʻamaʻa i nā mea āpau a mākaukau no ka nānā ʻana.

Boom, loaʻa iā ʻoe kahi hiʻohiʻona akaka o kāu hana kūʻai aku ma nā ala āpau.

A inā makemake ʻoe, hiki iā ʻoe ke hana i nā hiʻohiʻona ʻikepili maʻamau i kūpono i kāu pono ʻoihana a i ʻole e hoʻonohonoho i ka hōʻike a me nā dashboards.

Eia naʻe ka kicker maoli: Hoʻohana ʻo Improvado iā AI a me ke aʻo ʻana i ka mīkini e hōʻike maʻalahi i nā ʻike a me nā anomalies mai kāu ʻikepili.

ʻO nā hiʻohiʻona kiʻekiʻe o Improvado

• Wehe i ka ʻikepili mai 500+ kumu, me nā kahua kūʻai nui āpau
• ʻO ka hoʻomaʻamaʻa ʻana i ka ʻikepili a me ka hoʻololi ʻana no ka nānā mau
• E kūkulu i nā hiʻohiʻona ʻikepili maʻamau a me nā hōʻike / dashboard
• Nā ʻike i hoʻoikaika ʻia e AI a me nā kānana wānana
• Hoʻohui pū me nā mea hana BI kaulana e like me Looker, Tableau, a me Power BI
• Loaʻa i ka ʻikepili mōʻaukala a hiki i 5 mau makahiki o ke kālepa gula

13. ScraperAPI

(7 lā hoʻāʻo)

ʻO ScraperAPI kekahi API kiki-ass web scraping API e lawe i ka ʻeha a pau mai ka unuhi ʻana i ka ʻikepili mai nā pūnaewele.

Hoʻohana ʻia ia e nā hui ʻoi aku o 10,000, mai nā hoʻomaka hou a hiki i Fortune 500 pilikua, a ke kaʻina nei i kahi 36 biliona noi ʻili pūnaewele i kēlā me kēia mahina.

Kōkua ʻo ScraperAPI i nā ʻoihana e hōʻiliʻili i ka ʻikepili maʻemaʻe a me ka ʻike mai kekahi ʻaoʻao pūnaewele HTML me ka hoʻopaʻa ʻole ʻia e nā hana anti-scraping.

Mālama ʻo ia i nā pilikia ʻenehana hoʻonāukiuki a pau e like me ka rotation proxy, ka hoʻololi ʻana i ka polokalamu kele pūnaewele, a me ka hoʻonā CAPTCHA, no laila hiki iā ʻoe ke nānā wale i ka unuhi ʻana i ka ʻikepili āu e pono ai.

Ke hana nei ia ma kahi ākea nui, e ʻimi ana ma luna o 14,000 mau pūnaewele i kēlā me kēia kekona, a e hōʻoia i ka hūnā ʻia ʻana o kāu IP IP maoli a wehe ʻole ʻia.

Nā hiʻohiʻona kiʻekiʻe o ScraperAPI

• Hoʻololi i ka IP me kēlā me kēia noi mai nā miliona o nā proxies
• Hoʻopaʻa i nā ʻaoʻao i hāʻawi ʻia e JavaScript me kahi ʻāpana
• Hoʻoponopono 'akomi i nā CAPTCHA me ka hoʻohana ʻana i nā IP like ʻole a me ML
• Huli i nā wahi kikoʻī ma ka hoʻonohonoho ʻana i ke code ʻāina
• Hōʻoia i ka bandwidth palena ʻole no ka holo wikiwiki ʻana
• Mālama i ka nui o ka papahana mai 100 a 100M+ ʻaoʻao

14. Skyvia

(Hoʻolālā manuahi)

ʻO Skyvia kāu superhero ʻikepili kapua maʻalahi. He kahua hoʻohui ʻikepili e pili ana i ke ao e hana maʻalahi ai ka unuhi ʻana, hoʻololi a me ka hoʻouka ʻana (ETL).

Hiki iā ʻoe ke hoʻohui i nā kumu ʻikepili i manaʻo ʻia - nā polokalamu kapuaʻi e like me Salesforce a i ʻole HubSpot, nā waihona e like me SQL Server a i ʻole Oracle, a me nā faila palahalaha e like me CSV.

I kēia manawa, ʻo ka ʻāpana ʻoluʻolu?

Hiki iā ʻoe ke hoʻoneʻe i ka ʻikepili i kēlā me kēia ʻaoʻao āu e makemake ai - hoʻokomo, hoʻokuʻu aku, hoʻopili, a hoʻonohonoho paha.

Eia hou, inā pono ʻoe e hoʻihoʻi i kāu ʻikepili kapuaʻi makamae, ua uhi ʻo Skyvia iā ʻoe.

E hoʻopaʻa paʻa ia i kāu Salesforce, HubSpot, a i ʻole nā ​​​​ʻikepili ao ʻē aʻe, no laila hiki iā ʻoe ke hoʻihoʻi iā ia me nā kaomi liʻiliʻi.

A inā makemake nui ʻoe, hiki iā ʻoe ke nīnau a mālama i kēlā ʻikepili āpau me ka hoʻohana ʻana iā SQL a i ʻole kahi mea hana ʻike.

Eia kekahi, hāʻawi ʻo Skyvia iā ʻoe e hoʻopili i kāu kumu ʻikepili i nā polokalamu a me nā mea hana ʻē aʻe ma o nā kikoʻī OData a me SQL. No laila, hiki iā ʻoe ke kaʻana like i ke aloha ʻikepili me kāu BI punahele a i ʻole nā ​​​​mea hana analytics.

ʻO nā hiʻohiʻona kiʻekiʻe o Skyvia

• ʻAʻohe-code hoʻohui ʻikepili no ka poʻe ʻenehana ʻole (a i ʻole nā ​​coders palaualelo e like me aʻu)
• Hoʻohui i nā kumu ʻikepili 180+, me nā polokalamu kapuaʻi, nā waihona, a me nā faila
• ʻO nā hoʻololi ʻikepili ikaika no ka hoʻomaʻemaʻe ʻana a me ka hana ʻana i kāu ʻikepili
• Kākoʻo Cloud-to-cloud e mālama pono i kāu ʻikepili
• Mea hana nīnau SQL e kiʻi a mālama i ka ʻikepili ma nā kumu
• ʻO ka hui pū ʻana a me ka ʻae ʻana i nā mana no nā hana hui

15. mea paʻi maʻalahi

(Hoʻolālā manuahi)

ʻO ka mea hope loa, ʻo Simplescraper kahi mea hana inā ʻoe e ʻimi nei e unuhi i ka ʻikepili mai nā pūnaewele me ka ʻole e komo i ka coding.

Loaʻa iā Simplescraper kēia hoʻonui Chrome e hiki ai iā ʻoe ke koho ʻike i ka ʻikepili āu e makemake ai e ʻoka mai kekahi pūnaewele ma ke kaomi wale ʻana iā ia.

ʻAʻole pono e hakakā me nā mea koho CSS a i ʻole nā ​​palapala.

Kuhi wale a kaomi, a boom! Ua loaʻa iā ʻoe kahi meaʻai ʻōpala.

Hāʻawi pū ʻo Simplescraper i nā hiki ke ʻoki ʻana i ke ao, ʻo ia ka mea hiki iā ʻoe ke ʻimi i nā pūnaewele e hoʻohana ana i ka hoʻololi JavaScript a i ʻole nā ​​​​hana anti-scraping i kahi.

A ʻaʻole ʻo ia ka ʻāpana maikaʻi loa.

Hiki ke mālama ʻia a hoʻohana hou ʻia kēia mau mea ʻai ʻōpala i nā manawa a pau e pono ai ʻoe e unuhi hou i ka ʻikepili mai nā pūnaewele like.

Ke loaʻa iā ʻoe kāu ʻikepili, ʻae ʻo Simplescraper iā ʻoe e hoʻokuʻu aku iā ia ma nā ʻano like ʻole e like me CSV, JSON, a i ʻole pololei i nā mea hana e like me Google Sheets, Airtable, a me Zapier.

ʻO nā hiʻohiʻona kiʻekiʻe o Simplescraper

• Kuhi-a-kaomi no ke koho ikepili ike
• ʻO ke ao ʻana i nā wahi i hāʻawi ʻia e JavaScript a me ka pale ʻana i ka anti-scraping
• Hiki ke hoʻohana hou ʻia nā ʻōkuhi ʻōpala no ka ʻohi ʻana i ka ʻikepili
• Nā koho hoʻoili ʻikepili: CSV, JSON, Google Sheets, Airtable, Zapier, etc.
• ʻO nā meaʻai mākaukau no nā pūnaewele kaulana
• Kākoʻo proxy e mālama i nā kapu IP
• Loaʻa API no nā mea hoʻomohala e hoʻohui i ka ʻōpala i nā noi

Ka Manaʻo - ʻO wai ka mea hana ʻikepili e ola ai i kāna ʻōlelo hoʻohiki?

Maʻalahi - lākou a pau!

Eia nō naʻe, ʻaʻohe hoʻonā hoʻokahi-nui-kūpono i nā mea a pau ma aneʻi.

ʻO kahi mea maikaʻi e hana ai, ma muli o kā lākou mau hiʻohiʻona, kānana i kekahi mau mea hana i kū maoli no ʻoe.

E hele i mua a e ʻimi i nā mea e hoʻopiʻi i kou hoihoi.

Nui ka poʻe e hāʻawi i nā hoʻokolohua manuahi a i ʻole nā ​​​​hoʻolālā, no laila hiki iā ʻoe ke kiki i nā kaila ma mua o ka hana ʻana.

ʻO ka hope, e ʻoiaʻiʻo iā ʻoe iho - Makemake ʻoe e hoʻolilo i nā hola me ka hoʻokomo lima ʻana i nā ʻikepili āpau ma kāu mau pepa me he ʻāpana hana ma ka hopena?

A i ʻole makemake ʻoe e hoʻokaʻawale i ka hapa nui a hoʻolilo i kēlā manawa i kahi mea e neʻe ai i ka nila no ʻoe?

ʻO ka nūhou maikaʻi - hiki iā ʻoe ke hoʻoholo i kēlā no ʻoe iho.