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dt_json.py
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# EXAMPLE: json_tutorial
# HIDE_START
"""
Code samples for JSON doc pages:
https://redis.io/docs/latest/develop/data-types/json/
"""
import redis
r = redis.Redis(decode_responses=True)
# HIDE_END
# REMOVE_START
r.delete("bike")
r.delete("crashes")
r.delete("newbike")
r.delete("rider")
# REMOVE_END
# STEP_START set_get
res1 = r.json().set("bike", "$", '"Hyperion"')
print(res1) # >>> True
res2 = r.json().get("bike", "$")
print(res2) # >>> ['"Hyperion"']
res3 = r.json().type("bike", "$")
print(res3) # >>> ['string']
# STEP_END
# REMOVE_START
assert res2 == ['"Hyperion"']
# REMOVE_END
# STEP_START str
res4 = r.json().strlen("bike", "$")
print(res4) # >>> [10]
res5 = r.json().strappend("bike", '" (Enduro bikes)"')
print(res5) # >>> 27
res6 = r.json().get("bike", "$")
print(res6) # >>> ['"Hyperion"" (Enduro bikes)"']
# STEP_END
# REMOVE_START
assert res6 == ['"Hyperion"" (Enduro bikes)"']
# REMOVE_END
# STEP_START num
res7 = r.json().set("crashes", "$", 0)
print(res7) # >>> True
res8 = r.json().numincrby("crashes", "$", 1)
print(res8) # >>> [1]
res9 = r.json().numincrby("crashes", "$", 1.5)
print(res9) # >>> [2.5]
res10 = r.json().numincrby("crashes", "$", -0.75)
print(res10) # >>> [1.75]
# STEP_END
# REMOVE_START
assert res10 == [1.75]
# REMOVE_END
# STEP_START arr
res11 = r.json().set("newbike", "$", ["Deimos", {"crashes": 0}, None])
print(res11) # >>> True
res12 = r.json().get("newbike", "$")
print(res12) # >>> ['["Deimos", { "crashes": 0 }, null]']
res13 = r.json().get("newbike", "$[1].crashes")
print(res13) # >>> ['0']
res14 = r.json().delete("newbike", "$.[-1]")
print(res14) # >>> [1]
res15 = r.json().get("newbike", "$")
print(res15) # >>> [['Deimos', {'crashes': 0}]]
# STEP_END
# REMOVE_START
assert res15 == [["Deimos", {"crashes": 0}]]
# REMOVE_END
# STEP_START arr2
res16 = r.json().set("riders", "$", [])
print(res16) # >>> True
res17 = r.json().arrappend("riders", "$", "Norem")
print(res17) # >>> [1]
res18 = r.json().get("riders", "$")
print(res18) # >>> [['Norem']]
res19 = r.json().arrinsert("riders", "$", 1, "Prickett", "Royce", "Castilla")
print(res19) # >>> [4]
res20 = r.json().get("riders", "$")
print(res20) # >>> [['Norem', 'Prickett', 'Royce', 'Castilla']]
res21 = r.json().arrtrim("riders", "$", 1, 1)
print(res21) # >>> [1]
res22 = r.json().get("riders", "$")
print(res22) # >>> [['Prickett']]
res23 = r.json().arrpop("riders", "$")
print(res23) # >>> ['"Prickett"']
res24 = r.json().arrpop("riders", "$")
print(res24) # >>> [None]
# STEP_END
# REMOVE_START
assert res24 == [None]
# REMOVE_END
# STEP_START obj
res25 = r.json().set(
"bike:1", "$", {"model": "Deimos", "brand": "Ergonom", "price": 4972}
)
print(res25) # >>> True
res26 = r.json().objlen("bike:1", "$")
print(res26) # >>> [3]
res27 = r.json().objkeys("bike:1", "$")
print(res27) # >>> [['model', 'brand', 'price']]
# STEP_END
# REMOVE_START
assert res27 == [["model", "brand", "price"]]
# REMOVE_END
# STEP_START set_bikes
# HIDE_START
inventory_json = {
"inventory": {
"mountain_bikes": [
{
"id": "bike:1",
"model": "Phoebe",
"description": "This is a mid-travel trail slayer that is a fantastic "
"daily driver or one bike quiver. The Shimano Claris 8-speed groupset "
"gives plenty of gear range to tackle hills and there\u2019s room for "
"mudguards and a rack too. This is the bike for the rider who wants "
"trail manners with low fuss ownership.",
"price": 1920,
"specs": {"material": "carbon", "weight": 13.1},
"colors": ["black", "silver"],
},
{
"id": "bike:2",
"model": "Quaoar",
"description": "Redesigned for the 2020 model year, this bike "
"impressed our testers and is the best all-around trail bike we've "
"ever tested. The Shimano gear system effectively does away with an "
"external cassette, so is super low maintenance in terms of wear "
"and tear. All in all it's an impressive package for the price, "
"making it very competitive.",
"price": 2072,
"specs": {"material": "aluminium", "weight": 7.9},
"colors": ["black", "white"],
},
{
"id": "bike:3",
"model": "Weywot",
"description": "This bike gives kids aged six years and older "
"a durable and uberlight mountain bike for their first experience "
"on tracks and easy cruising through forests and fields. A set of "
"powerful Shimano hydraulic disc brakes provide ample stopping "
"ability. If you're after a budget option, this is one of the best "
"bikes you could get.",
"price": 3264,
"specs": {"material": "alloy", "weight": 13.8},
},
],
"commuter_bikes": [
{
"id": "bike:4",
"model": "Salacia",
"description": "This bike is a great option for anyone who just "
"wants a bike to get about on With a slick-shifting Claris gears "
"from Shimano\u2019s, this is a bike which doesn\u2019t break the "
"bank and delivers craved performance. It\u2019s for the rider "
"who wants both efficiency and capability.",
"price": 1475,
"specs": {"material": "aluminium", "weight": 16.6},
"colors": ["black", "silver"],
},
{
"id": "bike:5",
"model": "Mimas",
"description": "A real joy to ride, this bike got very high "
"scores in last years Bike of the year report. The carefully "
"crafted 50-34 tooth chainset and 11-32 tooth cassette give an "
"easy-on-the-legs bottom gear for climbing, and the high-quality "
"Vittoria Zaffiro tires give balance and grip.It includes "
"a low-step frame , our memory foam seat, bump-resistant shocks and "
"conveniently placed thumb throttle. Put it all together and you "
"get a bike that helps redefine what can be done for this price.",
"price": 3941,
"specs": {"material": "alloy", "weight": 11.6},
},
],
}
}
# HIDE_END
res1 = r.json().set("bikes:inventory", "$", inventory_json)
print(res1) # >>> True
# STEP_END
# STEP_START get_bikes
res2 = r.json().get("bikes:inventory", "$.inventory.*")
print(res2)
# >>> [[{'id': 'bike:1', 'model': 'Phoebe',
# >>> 'description': 'This is a mid-travel trail slayer...
# STEP_END
# STEP_START get_mtnbikes
res3 = r.json().get("bikes:inventory", "$.inventory.mountain_bikes[*].model")
print(res3) # >>> [['Phoebe', 'Quaoar', 'Weywot']]
res4 = r.json().get("bikes:inventory", '$.inventory["mountain_bikes"][*].model')
print(res4) # >>> [['Phoebe', 'Quaoar', 'Weywot']]
res5 = r.json().get("bikes:inventory", "$..mountain_bikes[*].model")
print(res5) # >>> [['Phoebe', 'Quaoar', 'Weywot']]
# STEP_END
# REMOVE_START
assert res3 == ["Phoebe", "Quaoar", "Weywot"]
assert res4 == ["Phoebe", "Quaoar", "Weywot"]
assert res5 == ["Phoebe", "Quaoar", "Weywot"]
# REMOVE_END
# STEP_START get_models
res6 = r.json().get("bikes:inventory", "$..model")
print(res6) # >>> [['Phoebe', 'Quaoar', 'Weywot', 'Salacia', 'Mimas']]
# STEP_END
# REMOVE_START
assert res6 == ["Phoebe", "Quaoar", "Weywot", "Salacia", "Mimas"]
# REMOVE_END
# STEP_START get2mtnbikes
res7 = r.json().get("bikes:inventory", "$..mountain_bikes[0:2].model")
print(res7) # >>> [['Phoebe', 'Quaoar']]
# STEP_END
# REMOVE_START
assert res7 == ["Phoebe", "Quaoar"]
# REMOVE_END
# STEP_START filter1
res8 = r.json().get(
"bikes:inventory",
"$..mountain_bikes[?(@.price < 3000 && @.specs.weight < 10)]",
)
print(res8)
# >>> [{'id': 'bike:2', 'model': 'Quaoar',
# 'description': "Redesigned for the 2020 model year...
# STEP_END
# REMOVE_START
assert res8 == [
{
"id": "bike:2",
"model": "Quaoar",
"description": "Redesigned for the 2020 model year, this bike impressed "
"our testers and is the best all-around trail bike we've ever tested. "
"The Shimano gear system effectively does away with an external cassette, "
"so is super low maintenance in terms of wear and tear. All in all it's "
"an impressive package for the price, making it very competitive.",
"price": 2072,
"specs": {"material": "aluminium", "weight": 7.9},
"colors": ["black", "white"],
}
]
# REMOVE_END
# STEP_START filter2
res9 = r.json().get("bikes:inventory", "$..[?(@.specs.material == 'alloy')].model")
print(res9) # >>> ['Weywot', 'Mimas']
# STEP_END
# REMOVE_START
assert res9 == ["Weywot", "Mimas"]
# REMOVE_END
# STEP_START filter3
res10 = r.json().get("bikes:inventory", "$..[?(@.specs.material =~ '(?i)al')].model")
print(res10) # >>> ['Quaoar', 'Weywot', 'Salacia', 'Mimas']
# STEP_END
# REMOVE_START
assert res10 == ["Quaoar", "Weywot", "Salacia", "Mimas"]
# REMOVE_END
# STEP_START filter4
res11 = r.json().set(
"bikes:inventory", "$.inventory.mountain_bikes[0].regex_pat", "(?i)al"
)
res12 = r.json().set(
"bikes:inventory", "$.inventory.mountain_bikes[1].regex_pat", "(?i)al"
)
res13 = r.json().set(
"bikes:inventory", "$.inventory.mountain_bikes[2].regex_pat", "(?i)al"
)
res14 = r.json().get(
"bikes:inventory",
"$.inventory.mountain_bikes[?(@.specs.material =~ @.regex_pat)].model",
)
print(res14) # >>> ['Quaoar', 'Weywot']
# STEP_END
# REMOVE_START
assert res14 == ["Quaoar", "Weywot"]
# REMOVE_END
# STEP_START update_bikes
res15 = r.json().get("bikes:inventory", "$..price")
print(res15) # >>> [1920, 2072, 3264, 1475, 3941]
res16 = r.json().numincrby("bikes:inventory", "$..price", -100)
print(res16) # >>> [1820, 1972, 3164, 1375, 3841]
res17 = r.json().numincrby("bikes:inventory", "$..price", 100)
print(res17) # >>> [1920, 2072, 3264, 1475, 3941]
# STEP_END
# REMOVE_START
assert res15 == [1920, 2072, 3264, 1475, 3941]
assert res16 == [1820, 1972, 3164, 1375, 3841]
assert res17 == [1920, 2072, 3264, 1475, 3941]
# REMOVE_END
# STEP_START update_filters1
res18 = r.json().set("bikes:inventory", "$.inventory.*[?(@.price<2000)].price", 1500)
res19 = r.json().get("bikes:inventory", "$..price")
print(res19) # >>> [1500, 2072, 3264, 1500, 3941]
# STEP_END
# REMOVE_START
assert res19 == [1500, 2072, 3264, 1500, 3941]
# REMOVE_END
# STEP_START update_filters2
res20 = r.json().arrappend(
"bikes:inventory", "$.inventory.*[?(@.price<2000)].colors", "pink"
)
print(res20) # >>> [3, 3]
res21 = r.json().get("bikes:inventory", "$..[*].colors")
print(
res21
) # >>> [['black', 'silver', 'pink'], ['black', 'white'], ['black', 'silver', 'pink']]
# STEP_END
# REMOVE_START
assert res21 == [
["black", "silver", "pink"],
["black", "white"],
["black", "silver", "pink"],
]
# REMOVE_END