# In[14]:
# マーケット一覧から先物を除外:product_code最後の9文字で判断する。
r = re.compile('[0-9]{2}[A-Z]{3}[0-9]{2}')
markets = list(
filter(lambda item: not r.match(item['product_code'][-9:]),
markets_all[1]))
# In[15]:
# Mongo DB
mongo_db_name = 'bf'
mongo_dataset_name = '_ticker_board01'
dbc = MongoClient()
# Open DB
db = dbc[mongo_db_name]
# Dataset
ds = db[mongo_dataset_name]
#
#ds.create_index('_timestamp')
# In[16]:
max_age_of_data = 21600 # 6 hours.
# In[ ]:
# とりあえず 500 とってみよう。500xproducts
#MongoDB Example
import pymongo import MongoClient
import datetime
#Open connection with localhost and port 27017
client = MongoClient("localhost", 27017)
#Access test Database
db = client.test_database
#Get the test collection
collection = db.test_collection
#Use Python Dictionary to create document
post = {"author": "Mike",
"text": "This is a test",
"tags": ["mongodb", "python", "pymongo"],
"date": datetime.datetime.utcnow()
}
#Insert a Document
posts = db.posts
post_id = posts.insert_one(post).inserted_id
post_id
import pandas as pd
import GooglePlace as gp
import MongoClient as mongo_client
train = pd.read_csv("<Train CSV file location>")
coordinates = train.ix[1:len(train), ['X', 'Y']]
for index, coordinate in coordinates.iterrows():
latitude = str(coordinate['Y'])
longitude = str(coordinate['X'])
radius = 3000
authKey = "<Google API Key>"
# Refer below link for set of valid place types supported by google places API
# https://developers.google.com/places/supported_types
types = "police|post_office|bus_station|train_station|taxi_stand|airport|fire_station|bank|gas_station|school|university|night_club|casino|shopping_mall|convenience_store|lodging"
#types="cafe"
mongo_collection = mongo_client.mongodb_connections(
"sfocrimelocs", "neighbourhood")
if mongo_client.isRecordsExists(mongo_collection, latitude,
longitude) == False:
json_data = gp.GooglePlace(latitude, longitude, radius, types, authKey)
# Get MongoDB connection and collection to insert
json_data['latitude'] = latitude
json_data['longitude'] = longitude
mongo_collection.insert(json_data)
print "inserted"
else:
print "records already exists"
from werkzeug.security import generate_password_hash, check_password_hash
from flask_bootstrap import Bootstrap
from flask_wtf import FlaskForm
from werkzeug.urls import url_parse
import re, os
import pymongo import MongoClient
app = Flask(__name__)
UPLOAD_FOLDER = "uploads"
ALLOWED_EXTENSIONS = {'txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif'}
basedir = os.path.abspath(os.path.dirname(__file__))
#client = pymongo.MongoClient("mongodb+srv://wad:[email protected]/test")
#db = client["wad"]
#users = db["users"]
client = MongoClient('mongodb', 27017)
db = client.wad
users = db.users
users.create_index("username")
app.secret_key = "super secret key"
login_manager = LoginManager(app)
login_manager.login_view = 'login'
app.config['UPLOAD_FOLDER']= UPLOAD_FOLDER
bootstrap = Bootstrap(app)
@app.route('/favicon.ico')
def favicon():
return send_from_directory(os.path.join(app.root_path, 'static'), 'favicon.ico', mimetype='favicon.ico')
ffrom pymongo import MongoClient
MONGO_URI = 'mongodb://localhost'
client = MongoClient(MONGO_URI)
db = client['musicalInstrumentsShop']
collectionCategory = db['category']
collectionCategory.insert_many([
{
"nombre": "Piano Digital",
};
{
"nombre": "Guitarra Electrica"
};
{
"nombre":"Bateria Completa"
};
{
"nombre":"Flauta"
};
{
"nombre":"Violin"
};
In [8]: y = x**2
In [9]: print(x)
[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
In [10]: print(y)
[ 0. 1. 4. 9. 16. 25. 36. 49. 64. 81. 100.]
In [11]: figure, axis = plt.subplots(1, 1)
In [12]: axis.plot(x, y)
Out[12]: [<matplotlib.lines.Line2D at 0x7f53c6a1c6d8>]
In [13]: figure.savefig("x_squared.svg")
In [14]: db = MongoClient("mongodb://mongo0.scitecha.com,mongo1.scitecha.com,mongo2.mrocha.org/mrocha?replicaSet=rs0").mrocha
In [15]: user_data = list(db.users.find({}, {"profile.TracyProgress": 1}))
In [16]: tprogress = [user["profile"]["TracyProgress"] for user in user_data]
In [17]: figure, axis = plt.subplots(1, 1)
In [18]: axis.hist(tprogress, bins=10)
Out[18]:
(array([3., 1., 5., 7., 2., 3., 5., 3., 0., 1.]),
array([ 3. , 11.8, 20.6, 29.4, 38.2, 47. , 55.8, 64.6, 73.4, 82.2, 91. ]),
<a list of 10 Patch objects>)
In [19]: figure.savefig('TracyProgress_histogram.svg')
In [21]: figure.savefig('TracyProgress_histogram.svg'
# Setting up environment to use existing models
import os, django
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "uber_challenge.settings
django.setup()
# Import models
from film.models import
# Setup MongoDB
from pymongo import MongoClient
import json
import requests
# Connect to database
client = MongoClient()
db = client.uber_challenge
coll = db.film
# Remove old data before getting new data
coll.remove()
# Dump the data from provided API endpoint
r = requests.get('https://data.sfgov.org/resource/yitu-d5am.json')
data = json.loads(r.text)
for i in range(len(data)):
curr = data[i]
# @TODO: Create Models According to Data and Save to the DataBase
train = pd.read_csv("<Train CSV file location>")
coordinates = train.ix[1:len(train), ['X', 'Y']]
for index, coordinate in coordinates.iterrows():
latitude = str(coordinate['Y'])
longitude = str(coordinate['X'])
radius = 3000;
authKey = "<Google API Key>"
# Refer below link for set of valid place types supported by google places API
# https://developers.google.com/places/supported_types
types = "police|post_office|bus_station|train_station|taxi_stand|airport|fire_station|bank|gas_station|school|university|night_club|casino|shopping_mall|convenience_store|lodging"
#types="cafe"
mongo_collection = mongo_client.mongodb_connections("sfocrimelocs","neighbourhood")
if mongo_client.isRecordsExists(mongo_collection, latitude, longitude) == False:
json_data = gp.GooglePlace(latitude, longitude, radius, types, authKey)
# Get MongoDB connection and collection to insert
json_data['latitude']=latitude
json_data['longitude']=longitude
mongo_collection.insert(json_data);
print "inserted"
else:
print "records already exists"
> db.user.find()
{ "_id" : ObjectId("59a8034564e0acb13483d514"), "user" : "jin", "age" : 31, "email" : "*****@*****.**", "addr" : [ "GZ", "SZ" ] }
{ "_id" : ObjectId("59a8034564e0acb13483d515"), "user" : "nan", "age" : 26, "email" : "*****@*****.**", "addr" : [ "NJ", "AH" ] }
上面的命令成功的删除所有地址包含 "CD" 的用户，共删除了两条记录。
MongoDB 基本操作视频：
Play Video
Python 操作 MongoDB
在 Python 中访问 MongoDB 数据库，主要通过 PyMongo 软件包。该软件包含一个 MongoClient 对象，可以用于建立 MongoDB 客户端。在 IPython 中输入下面的示例代码，创建客户端：
In [2]: from pymongo import MongoClient
In [3]: client = MongoClient('127.0.0.1', 27017)
In [4]: db = client.shiyanlou
前文中，已经知道 MongoDB 默认监听在 127.0.0.1:27017 地址上，所以在创建 client 时，使用了该地址。客户端创建成功后，我们通过 client.shiyanlou 方式选择了 shiyanlou 数据库。接着就可以查询所有的文档了：
In [13]: for user in db.user.find():
...: print(user)
...:
{'_id': ObjectId('59a8034564e0acb13483d514'), 'user': '******', 'age': 31.0, 'email': '*****@*****.**', 'addr': ['GZ', 'SZ']}
{'_id': ObjectId('59a8034564e0acb13483d515'), 'user': '******', 'age': 26.0, 'email': '*****@*****.**', 'addr': ['NJ', 'AH']}
通过 PyMongo 插入数据也非常简单，直接通过 insert_one 方法：
In [14]: user = {'name': 'Aiden', 'age': 30, 'addr': ['CD', 'SH', 'BJ']}
In [15]: db.user.insert_one(user)
Out[15]: <pymongo.results.InsertOneResult at 0x10730aa08>