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Merged
merged 8 commits into from
Apr 5, 2024
Merged

fix: code style of source files #80

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cd807b2
fix: code style of source files
bednar Apr 2, 2024
4c8f2e7
fix: code style
bednar Apr 2, 2024
a6b7873
chore(ci): add flake8 to tests
bednar Apr 2, 2024
eb79ff0
chore(ci): add flake8 to tests
bednar Apr 2, 2024
c9a1a40
chore(ci): add flake8 to examples
bednar Apr 2, 2024
f7687db
chore(ci): fix code style
bednar Apr 2, 2024
4c0203d
docs: update CHANGELOG.md
bednar Apr 2, 2024
f02e9ed
fix: code style
bednar Apr 3, 2024
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12 changes: 11 additions & 1 deletion .circleci/config.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -68,6 +68,16 @@ jobs:
command: |
pip install flake8 --user
flake8 influxdb_client_3/
- run:
name: Checks style consistency across tests.
command: |
pip install flake8 --user
flake8 tests/
- run:
name: Checks style consistency across examples.
command: |
pip install flake8 --user
flake8 Examples/
check-twine:
docker:
- image: *default-python
Expand Down Expand Up @@ -102,7 +112,7 @@ workflows:
not:
equal: [ scheduled_pipeline, << pipeline.trigger_source >> ]
jobs:
# - check-code-style
- check-code-style
# - check-docstyle
- check-twine
- tests-python:
Expand Down
6 changes: 6 additions & 0 deletions .flake8
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Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
[flake8]
count = True
max-line-length = 120

# W504: Line break occurred after a binary operator
ignore = W504
6 changes: 5 additions & 1 deletion CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -2,4 +2,8 @@

### Bugfix

1. [#77](https://github.com/InfluxCommunity/influxdb3-python/pull/77): Support using pandas nullable types
1. [#77](https://github.com/InfluxCommunity/influxdb3-python/pull/77): Support using pandas nullable types

### Others

- [#80](https://github.com/InfluxCommunity/influxdb3-python/pull/80): Integrate code style check into CI
69 changes: 32 additions & 37 deletions Examples/batching_example.py
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@karel-rehor karel-rehor Apr 5, 2024 •
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Ran this example against an initial user account - it eventually resulted in the following error

The retriable error occurred during request. Reason: 'org fbb67cd4c8905be6 has exceeded limited_write plan limit'. Retry in 206s.

While a good example of batching, I'm not sure from perhaps a marketing perspective, if it is a good example for newer users.

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This issue should be addressed by #82

Original file line number Diff line number Diff line change
@@ -1,13 +1,10 @@
import datetime
import random
import pymongo
import pandas as pd

from bson import ObjectId

import influxdb_client_3 as InfluxDBClient3
import pandas as pd
import numpy as np
from influxdb_client_3 import write_client_options, WritePrecision, WriteOptions, InfluxDBError
import datetime
import time


class BatchingCallback(object):
Expand Down Expand Up @@ -42,26 +39,24 @@ def retry(self, conf, data: str, exception: InfluxDBError):
callback = BatchingCallback()

write_options = WriteOptions(batch_size=5_000,
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)

wco = write_client_options(success_callback=callback.success,
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)
# Opening InfluxDB client with a batch size of 5k points or flush interval
# of 10k ms and gzip compression
with InfluxDBClient3.InfluxDBClient3(token=token,
host=url,
org=org,
database=database, enable_gzip=True, write_client_options=wco) as _client:


# Creating iterator for one hour worth of data (6 sensor readings per
# minute)
for i in range(0, 525600):
Expand Down Expand Up @@ -93,25 +88,25 @@ def retry(self, conf, data: str, exception: InfluxDBError):
bcWh).field(
"bdW",
bdW).field(
"bdWh",
bdWh).field(
"cPvWh",
cPvWh).field(
"cW",
cW).field(
"cWh",
cWh).field(
"eWh",
eWh).field(
"iWh",
iWh).field(
"pW",
pW).field(
"pWh",
pWh).field(
"scWh",
scWh).time(
now.strftime('%Y-%m-%dT%H:%M:%SZ'),
"bdWh",
bdWh).field(
"cPvWh",
cPvWh).field(
"cW",
cW).field(
"cWh",
cWh).field(
"eWh",
eWh).field(
"iWh",
iWh).field(
"pW",
pW).field(
"pWh",
pWh).field(
"scWh",
scWh).time(
now.strftime('%Y-%m-%dT%H:%M:%SZ'),
WritePrecision.S)

# Writing point (InfluxDB automatically batches writes into sets of
Expand Down
3 changes: 0 additions & 3 deletions Examples/cloud_dedicated_query.py
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Tried this example as well against a new user account. Apparently the "flight2" bucket needs to be created in another example.

Failed with error

pyarrow.lib.ArrowInvalid: Flight returned invalid argument error, with message: bucket "flight2" not found. gRPC client debug context: UNKNOWN:Error received from peer ipv4:34.196.233.7:443 {created_time:"2024-04-05T10:59:19.006603056+02:00", grpc_status:3, grpc_message:"bucket \"flight2\" not found"}. Client context: IOError: Server never sent a data message. Detail: Internal

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This issue should be addressed by #82

Original file line number Diff line number Diff line change
@@ -1,14 +1,11 @@
import influxdb_client_3 as InfluxDBClient3
import pandas as pd
import numpy as np

client = InfluxDBClient3.InfluxDBClient3(
token="",
host="b0c7cce5-8dbc-428e-98c6-7f996fb96467.a.influxdb.io",
org="6a841c0c08328fb1",
database="flight2")


table = client.query(
query="SELECT * FROM flight WHERE time > now() - 4h",
language="influxql")
Expand Down
47 changes: 25 additions & 22 deletions Examples/community/custom_url.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,9 @@
from influxdb_client_3 import InfluxDBClient3,InfluxDBError,WriteOptions,write_client_options
import pandas as pd
import random

import pandas as pd

from influxdb_client_3 import InfluxDBClient3, InfluxDBError, WriteOptions, write_client_options


class BatchingCallback(object):

Expand All @@ -14,36 +16,38 @@ def error(self, conf, data: str, exception: InfluxDBError):
def retry(self, conf, data: str, exception: InfluxDBError):
print(f"Retryable error occurs for batch: {conf}, data: {data} retry: {exception}")

callback = BatchingCallback()

callback = BatchingCallback()

write_options = WriteOptions(batch_size=100,
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)

wco = write_client_options(success_callback=callback.success,
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)

client = InfluxDBClient3(
token="",
host="https://eu-central-1-1.aws.cloud2.influxdata.com:442",
org="6a841c0c08328fb1",
database="pokemon-codex", enable_gzip=True, write_client_options=wco, write_port_overwrite=443, query_port_overwrite=443)
database="pokemon-codex", enable_gzip=True, write_client_options=wco, write_port_overwrite=443,
query_port_overwrite=443)

now = pd.Timestamp.now(tz='UTC').floor('ms')
now = pd.Timestamp.now(tz='UTC').floor('ms')

# Lists of possible trainers
trainers = ["ash", "brock", "misty", "gary", "jessie", "james"]

# Read the CSV into a DataFrame
pokemon_df = pd.read_csv("https://gist.githubusercontent.com/ritchie46/cac6b337ea52281aa23c049250a4ff03/raw/89a957ff3919d90e6ef2d34235e6bf22304f3366/pokemon.csv")
pokemon_df = pd.read_csv(
"https://gist.githubusercontent.com/ritchie46/cac6b337ea52281aa23c049250a4ff03/raw/89a957ff3919d90e6ef2d34235e6bf22304f3366/pokemon.csv") # noqa: E501

# Creating an empty list to store the data
data = []
Expand All @@ -57,17 +61,17 @@ def retry(self, conf, data: str, exception: InfluxDBError):
# Generating random data
for i in range(num_entries):
trainer = random.choice(trainers)

# Randomly select a row from pokemon_df
random_pokemon = pokemon_df.sample().iloc[0]
caught = random_pokemon['Name']

# Count the number of times this trainer has caught this Pokémon
if (trainer, caught) in trainer_pokemon_counts:
trainer_pokemon_counts[(trainer, caught)] += 1
else:
trainer_pokemon_counts[(trainer, caught)] = 1

# Get the number for this combination of trainer and Pokémon
num = trainer_pokemon_counts[(trainer, caught)]

Expand All @@ -93,9 +97,8 @@ def retry(self, conf, data: str, exception: InfluxDBError):
# Print the DataFrame
print(caught_pokemon_df)


try:
client.write(caught_pokemon_df, data_frame_measurement_name='caught',
data_frame_tag_columns=['trainer', 'id', 'num'])
data_frame_tag_columns=['trainer', 'id', 'num'])
except Exception as e:
print(f"Error writing point: {e}")
print(f"Error writing point: {e}")
45 changes: 17 additions & 28 deletions Examples/community/database_transfer.py
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Original file line number Diff line number Diff line change
@@ -1,14 +1,8 @@
import random
import pymongo
import pandas as pd
from bson import ObjectId
import influxdb_client_3 as InfluxDBClient3
import pandas as pd
import numpy as np
from influxdb_client_3 import write_client_options, WritePrecision, WriteOptions, InfluxDBError
import datetime
import time

import influxdb_client_3 as InfluxDBClient3
from influxdb_client_3 import write_client_options, WriteOptions, InfluxDBError


class BatchingCallback(object):

Expand All @@ -22,44 +16,41 @@ def retry(self, conf, data: str, exception: InfluxDBError):
print(f"Retryable error occurs for batch: {conf}, data: {data} retry: {exception}")




# InfluxDB connection details
token = ""
org = "6a841c0c08328fb1"
dbfrom = "a"
dbto = "b"
url = "eu-central-1-1.aws.cloud2.influxdata.com"
measurement = "airSensors"
taglist= []
taglist = []

callback = BatchingCallback()

write_options = WriteOptions(batch_size=5_000,
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)
flush_interval=10_000,
jitter_interval=2_000,
retry_interval=5_000,
max_retries=5,
max_retry_delay=30_000,
exponential_base=2)

wco = write_client_options(success_callback=callback.success,
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)
error_callback=callback.error,
retry_callback=callback.retry,
WriteOptions=write_options
)
# Opening InfluxDB client with a batch size of 5k points or flush interval
# of 10k ms and gzip compression
with InfluxDBClient3.InfluxDBClient3(token=token,
host=url,
org=org,
enable_gzip=True, write_client_options=wco) as _client:
enable_gzip=True, write_client_options=wco) as _client:
query = f"SHOW TAG KEYS FROM {measurement}"
tags = _client.query(query=query, language="influxql", database=dbfrom)
tags = tags.to_pydict()
taglist = tags['tagKey']


query = f"SELECT * FROM {measurement}"
reader = _client.query(query=query, language="influxql", database=dbfrom, mode="chunk")
try:
Expand All @@ -69,10 +60,8 @@ def retry(self, conf, data: str, exception: InfluxDBError):
pd = batch.to_pandas()
pd = pd.set_index('time')
print(pd)
_client.write(database=dbto, record=pd, data_frame_measurement_name=measurement, data_frame_tag_columns=taglist)
_client.write(database=dbto, record=pd, data_frame_measurement_name=measurement,
data_frame_tag_columns=taglist)
time.sleep(2)
except StopIteration:
print("No more chunks to read")



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