Небольшой трик с регулярными выражениями который редко вижу в чужом коде.
Допустим, вам нужно распарсить простой текст и вытащить оттуда пары имя+телефон. Вернуть всё это надо в виде списка словарей. Возьмем очень простой пример текста.
>>> text = '''
>>> Alex:8999123456
>>> Mike:+799987654
>>> Oleg:+344456789
>>> '''
Соответственно, для выделения нужных элементов будем использовать группы. Получится такой паттерн:
(\w+):([\d+]+)
Как мы будем формировать словарь из найденных групп?
>>> import re
>>> results = []
>>> for match in re.finditer(r"(\w+):([\d+]+)", text):
>>> results.append({
>>> "name": match.group(1),
>>> "phone": match.group(2)
>>> })
>>> print(results)
[{'name': 'Alex', 'phone': '8999123456'}, ...]
Можно немного сократить запись используя zip
>>> results = []
>>> for match in re.finditer(r"(\w+):([\d+]+)", text):
>>> results.append(dict(zip(['name', 'phone'], match.groups())))
Но есть способ лучше! Это именованные группы в regex. Можно в паттерне указать имя группы и результат сразу забрать в виде словаря.
>>> for match in re.finditer(r"(?P<name>\w+):(?P<phone>[\d+]+)", text):
>>> results.append(match.groupdict())
То есть всё что я сделал, это добавил в начале группы (внутри сбокочек) такую запись:
(?P<group-name>...)
Теперь найденная группа имеет имя и можно обратиться к ней как к элементу списка
>>> name = match['name']
Либо забрать сразу весь словарь методом groupdict()
>>> match.groupdict()
#tricks#regex
Bitcoin and Ethereum ETF Outflows Report
On February 21, Bitcoin spot ETFs saw a net outflow of $62.77M, while BlackRock's ETF IBIT experienced a net inflow of $21.64M. Additionally, Ethereum spot ETFs recorded a net outflow of $8.92M. Read more here.
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Bitcoin ETFs experience record outflows nearing $1 billion. In 2023, all crypto sectors underperform compared to Bitcoin, with AI frameworks down 84%, agent projects 70%, and more. SEC acknowledges NYSE Arca's filing for Grayscale Ethereum ETF staking. Meanwhile, Bybit hackers have laundered 45,900 ETH ($113M) in 24 hours, totaling 135,000 ETH ($335M) to date, with more expected to be laundered soon.
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Crypto Outflows Reach $508M Amid Caution
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3️⃣ BTC holders recorded losses of $1.73 billion, marking the highest since August 2024.
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5️⃣ Meme coins like Dogecoin and Shiba Inu drop significantly, as market saturation affects their traction.
6️⃣ New AI-meme project MIND of Pepe raises $6.8 million, distinguishing itself with functional AI integration.
7️⃣ Ethereum Foundation pledges $1.25 million for legal defense of Tornado Cash developer.
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