Kei a koe nga mahi e mahi tonu ana i ia ra, ia wiki, ia wiki? Hei tauira, te tuhi purongo. Ka tono raraunga, tātarihia, whakaatahia (hanga kauwhata, tūtohi), ka tukuna atu ki to rangatira. Engari ka pehea mena he mea aunoa enei katoa?
I roto i tenei akoranga ka hangaia e matou he karetao mo Telegram ka awhina i te whakaputa purongo. A ko te mea tino pai ko te kaupapa katoa ka 50 noa nga rarangi waehere! Mena kei te hanga e koe he bot mo Telegram mo te wa tuatahi, me panui ano koe i tenei .
Ka tūtohu a Skillbox: Akoranga mahi .
Ka whakamahara matou: mo nga kaipānui katoa o "Habr" - he utu mo te 10 rubles i te wa e whakauru ana ki tetahi akoranga Skillbox ma te whakamahi i te waehere whakatairanga "Habr".
Kia timata tatou
Te whakauru whare pukapuka
Ka whakamahia e matou ki te tiki raraunga mai i a Google BigQuery. , и ka awhina koe ki te tiro i o raraunga. ka tukuna nga raraunga kua oti ki a Telegram.
pip3 tāuta google-cloud-bigquery matplotlib numpy pandas python-telegram-bot
Te hono i te API Google BigQuery
Mena kei te pirangi tatou ki te whakamahi i te ratonga, me hono tatou i te Google BigQuery API. Ki te mahi i tenei ka haere tatou ki me te hanga i tetahi kaupapa hou (me kowhiri ranei i tetahi kaupapa kua puta).
I roto i te paewhiri mana, tohua te WHAKAMAHI APIS ME NGA RATONGA ka rapu mo BigQuery API.
Tīpakohia Whakahohe ki te hono i te API.
Waihangahia he kī pūkete
Me haere ano ki , tīpakohia te ripa Taipitopito, Waihangahia nga tohu me te Kī pūkete Ratonga.
Na - Pūkete ratonga hou, ka tomo i te ingoa i roto i te ingoa pūkete Ratonga mara.
Mai i te rārangi taka-iho Tūnga, tīpako Kaupapa > Kaipupuri, ka Waihanga.
Ko te konae ka tangohia aunoatia ka kiia ko creds.json.
Tautuhia GOOGLE_APPLICATION_CREDENTIALS, whakapūtā te ara ki creds.json i te tauranga.
kaweake GOOGLE_APPLICATION_CREDENTIALS='[PATH_TO_CREDS.JSON]'
Mena i pai nga mea katoa, kua tae ki te wa ki te tuhi i te kaupapa.
Te hanga tono
Mo te akoranga ka whakamahia e matou nga raraunga mai i bigquery-public-data.stackoverflow, mo ta matou ripoata ka tohua e matou te maha o nga whakaputanga o ia ra.
He maamaa noa nga mea katoa.
Uia te ripanga -> Tirohia te raraunga -> Tiaki te tirohanga -> Tukuna te ahua
Me hanga tetahi mahi hei tautuhi i ia miro.
Uiui ki BigQuery
Tuatahi ka kawemai i te whare pukapuka.
mai i google.cloud kawemai bigquery
Ka hangaia e matou he mahi e kiia nei ko query_to_bigquery, ko te tawhā ko te uiui.
def query_to_bigquery(query):
client = bigquery.Client()
query_job = client.query(query)
result = query_job.result()
dataframe = result.to_dataframe()
return dataframeMa tenei mahi ka whakahoki te tono hei anga raraunga.
Te whakaata i nga raraunga
Hei whakaoti i tenei raruraru, whiriwhiria matplotlib.
kawemai matplotlib.pyplot hei plt
E rima nga tawhā, ko x te raraunga tuaka-x, x_label te taitara mo te tuaka, y te raraunga tuaka-y, y_label te taitara mo te tuaka, ko te taitara te taitara o te tirohanga katoa.
def visualize_bar_chart(x, x_label, y, y_label, title):
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
index = np.arange(len(x))
plt.xticks(index, x, fontsize=5, rotation=30)
plt.bar(index, y)
return pltTiakina te whakaahua
Inaianei me whakamahi e rua nga mahi ki te hanga tirohanga me te penapena.
Ka tukuna e matou te maha o nga panui kua whakaputaina ia ra. Tuatahi ka tuhia he tono.
query = """
SELECT DATE(creation_date) date, COUNT(*) total_posts
FROM `bigquery-public-data.stackoverflow.post_history`
GROUP BY 1
HAVING date > DATE_SUB('2018-12-02', INTERVAL 14 DAY)
ORDER BY 1
"""Ka awhina te patai ki te kohi raraunga mo nga wiki e rua ka timata i te Hakihea 2, 2018.
Ka whakamahia e matou tenei ra na te mea ko te 2018-12-02 nga raraunga hou kua tuhia ki bigquery-public-data.stackoverflow.post_history, i etahi atu keehi ka taea e koe te whakamahi CURRENT_DATE() ki te tiki i nga raraunga hou.
Waea te mahi query_to_bigquery ki te tiki raraunga.
anga raraunga = query_to_bigquery(uiui)
Na ka whakamahi matou i te pou raraunga ra mo te tuaka-x, me te pou_tapeke pou mo te tuaka-y.
x = anga raraunga['rā'].tolist()
y = anga raraunga['total_posts'].tolist()
Ka whakaatahia ma te whakamahi i te mahi visualize_bar_chart ka tiakina hei ahua.
plt = visualize_bar_chart(x=x, x_label='Rā', y=y, y_label='Tapeke Whakairi', taitara='Whakairinga Ia Ra')
plt.savefig('viz.png')
Ka takai tatou i tenei waehere ki tetahi mahi ko get_and_save_image.
def get_and_save_image():
query = """
SELECT DATE(creation_date) date, COUNT(*) total_posts
FROM `bigquery-public-data.stackoverflow.post_history`
GROUP BY 1
HAVING date > DATE_SUB('2018-12-02', INTERVAL 14 DAY)
ORDER BY 1
"""
dataframe = query_to_bigquery(query)
x = dataframe['date'].tolist()
y = dataframe['total_posts'].tolist()
plt = visualize_bar_chart(x=x, x_label='Date', y=y, y_label='Total Posts', title='Daily Posts')
plt.savefig('viz.png')Tukuna he whakaahua
Hei tuku purongo ki te kaiwhiwhi, me mohio koe ki te tawhā chat_id.
Ka whakamahia e matou ka patohia /timata. Ka whakautu te karetao me nga korero e tika ana, kei roto te chat_id i te mara id.
Inaianei me hanga te mahi send_image. Ka whakamahia te mahi get_and_save_image ki te tiki me te tiaki i te ahua. Na ka tukuna e matou nga mea katoa ki te whakapiri tika.
def send_image(bot, update):
get_and_save_image()
chat_id = 'CHAT_ID_RECEIVER'
bot.send_photo(chat_id=chat_id, photo=open('viz.png','rb'))Kaupapa matua
Ka mutu, ka hangaia e matou tetahi atu mahi, matua, hei whakarewa i te tono. Kaua e wareware ki te huri i YOUR_TOKEN mo te karetao.
Kia mahara: ka tukuna aunoatia e tenei papatono te ahua i te wa e tohua ana e koe. Hei tauira, ka tukuna he ripoata a te iwa i te ata ia ra.
def main():
updater = Updater('YOUR_TOKEN')
updater.job_queue.run_daily(send_image, time=datetime.datetime.strptime('9:00AM', '%I:%M%p').time(), days=(0,1,2,3,4,5,6))
updater.start_polling()
updater.idle()
if __name__ == '__main__':
main()Ko te mutunga, ka penei to maatau tono:
from google.cloud import bigquery
from telegram.ext import Updater
import matplotlib.pyplot as plt
import numpy as np
import datetime
def query_to_bigquery(query):
client = bigquery.Client()
query_job = client.query(query)
result = query_job.result()
dataframe = result.to_dataframe()
return dataframe
def visualize_bar_chart(x, x_label, y, y_label, title):
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
index = np.arange(len(x))
plt.xticks(index, x, fontsize=5, rotation=30)
plt.bar(index, y)
return plt
def get_and_save_image():
query = """
SELECT DATE(creation_date) date, COUNT(*) total_posts
FROM `bigquery-public-data.stackoverflow.post_history`
GROUP BY 1
HAVING date > DATE_SUB('2018-12-02', INTERVAL 14 DAY)
ORDER BY 1
"""
dataframe = query_to_bigquery(query)
x = dataframe['date'].tolist()
y = dataframe['total_posts'].tolist()
plt = visualize_bar_chart(x=x, x_label='Date', y=y, y_label='Total Posts', title='Daily Posts')
plt.savefig('viz.png')
def send_image(bot, update):
get_and_save_image()
chat_id = 'CHAT_ID_RECEIVER'
bot.send_photo(chat_id=chat_id, photo=open('viz.png', 'rb'))
def main():
updater = Updater('YOUR_TOKEN')
updater.job_queue.run_daily(send_image, time=datetime.datetime.strptime('9:00AM', '%I:%M%p').time(), days=(0,1,2,3,4,5,6))
updater.start_polling()
updater.idle()
if __name__ == '__main__':
main()Tiakina te konae ka kiia he main.py.
Ka whakarewahia e matou te tono ma te whakauru i te whakahau ki te tauranga:
python3 matua.py
Kua reri katoa. Inaianei kei a matou he karetao e 50 nga rarangi waehere ka whakaputa purongo me te kore e wawao.
Kia tirohia te karetao mā te kōwhiri i te tono /tuku.
Ka taea e koe te tiki i te waehere oti i .
Ka tūtohu a Skillbox:
- E rua tau te akoranga mahi .
- Akoranga aipurangi .
- Akoranga tau mahi .
Source: will.com