From 100e5c30c2bba9d2e50a439ced8e7c79c454d230 Mon Sep 17 00:00:00 2001
From: Colas Le Guernic <clslgrnc@users.noreply.github.com>
Date: Thu, 7 May 2020 10:49:08 +0200
Subject: [PATCH] precision_factor should be an int, not a float

might fix #822
---
 influxdb/_dataframe_client.py | 57 +++++++++++++++++------------------
 1 file changed, 27 insertions(+), 30 deletions(-)

diff --git a/influxdb/_dataframe_client.py b/influxdb/_dataframe_client.py
index ec58cebb..2df2e4ab 100644
--- a/influxdb/_dataframe_client.py
+++ b/influxdb/_dataframe_client.py
@@ -13,7 +13,7 @@
 import numpy as np
 
 from .client import InfluxDBClient
-from .line_protocol import _escape_tag
+from .line_protocol import _escape_tag, _to_nanos
 
 
 def _pandas_time_unit(time_precision):
@@ -267,11 +267,11 @@ def _convert_dataframe_to_json(dataframe,
 
         precision_factor = {
             "n": 1,
-            "u": 1e3,
-            "ms": 1e6,
-            "s": 1e9,
-            "m": 1e9 * 60,
-            "h": 1e9 * 3600,
+            "u": 10 ** 3,
+            "ms": 10 ** 6,
+            "s": 10 ** 9,
+            "m": 10 ** 9 * 60,
+            "h": 10 ** 9 * 3600,
         }.get(time_precision, 1)
 
         if not tag_columns:
@@ -279,7 +279,7 @@ def _convert_dataframe_to_json(dataframe,
                 {'measurement': measurement,
                  'fields':
                     rec.replace([np.inf, -np.inf], np.nan).dropna().to_dict(),
-                 'time': np.int64(ts.value / precision_factor)}
+                 'time': np.int64(ts.value) // precision_factor}
                 for ts, (_, rec) in zip(
                     dataframe.index,
                     dataframe[field_columns].iterrows()
@@ -293,7 +293,7 @@ def _convert_dataframe_to_json(dataframe,
              'tags': dict(list(tag.items()) + list(tags.items())),
              'fields':
                 rec.replace([np.inf, -np.inf], np.nan).dropna().to_dict(),
-             'time': np.int64(ts.value / precision_factor)}
+             'time': np.int64(ts.value) // precision_factor}
             for ts, tag, (_, rec) in zip(
                 dataframe.index,
                 dataframe[tag_columns].to_dict('record'),
@@ -354,20 +354,20 @@ def _convert_dataframe_to_lines(self,
 
         precision_factor = {
             "n": 1,
-            "u": 1e3,
-            "ms": 1e6,
-            "s": 1e9,
-            "m": 1e9 * 60,
-            "h": 1e9 * 3600,
+            "u": 10 ** 3,
+            "ms": 10 ** 6,
+            "s": 10 ** 9,
+            "m": 10 ** 9 * 60,
+            "h": 10 ** 9 * 3600,
         }.get(time_precision, 1)
 
         # Make array of timestamp ints
         if isinstance(dataframe.index, pd.PeriodIndex):
-            time = ((dataframe.index.to_timestamp().values.astype(np.int64) /
-                     precision_factor).astype(np.int64).astype(str))
+            time = ((dataframe.index.to_timestamp().values.astype(np.int64) //
+                     precision_factor).astype(str))
         else:
-            time = ((pd.to_datetime(dataframe.index).values.astype(np.int64) /
-                     precision_factor).astype(np.int64).astype(str))
+            time = ((pd.to_datetime(dataframe.index).values.astype(np.int64) //
+                     precision_factor).astype(str))
 
         # If tag columns exist, make an array of formatted tag keys and values
         if tag_columns:
@@ -473,16 +473,13 @@ def _stringify_dataframe(dframe, numeric_precision, datatype='field'):
         return dframe
 
     def _datetime_to_epoch(self, datetime, time_precision='s'):
-        seconds = (datetime - self.EPOCH).total_seconds()
-        if time_precision == 'h':
-            return seconds / 3600
-        elif time_precision == 'm':
-            return seconds / 60
-        elif time_precision == 's':
-            return seconds
-        elif time_precision == 'ms':
-            return seconds * 1e3
-        elif time_precision == 'u':
-            return seconds * 1e6
-        elif time_precision == 'n':
-            return seconds * 1e9
+        nanos = _to_nanos(datetime)
+        precision_factor = {
+            "n": 1,
+            "u": 10 ** 3,
+            "ms": 10 ** 6,
+            "s": 10 ** 9,
+            "m": 10 ** 9 * 60,
+            "h": 10 ** 9 * 3600,
+        }.get(time_precision, 1)
+        return nanos // precision_factor

<!DOCTYPE html PUBLIC '-//W3C//DTD XHTML 1.0 Transitional//EN' 'http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd'>
<html xmlns='http://www.w3.org/1999/xhtml'>
<head>
<title>pFad - Phonifier reborn</title>
<meta http-equiv='Content-Type' content='text/html; charset=utf-8' />
</head>
<body>
<h1>Pfad - The Proxy pFad of &#169; 2024 Garber Painting. All rights reserved.</h1>


<!-- Disclaimer -->
<p>Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.</p>
<br>
<p>Alternative Proxies:</p><p><a href="http://rainy.clevelandohioweatherforecast.com/php-proxy/index.php?q=https://patch-diff.githubusercontent.com/raw/influxdata/influxdb-python/pull/823.patch" target="_blank">Alternative Proxy</a></p><p><a href="http://rainy.clevelandohioweatherforecast.com/pFad/index.php?u=https://patch-diff.githubusercontent.com/raw/influxdata/influxdb-python/pull/823.patch" target="_blank">pFad Proxy</a></p><p><a href="http://rainy.clevelandohioweatherforecast.com/pFad/v3index.php?u=https://patch-diff.githubusercontent.com/raw/influxdata/influxdb-python/pull/823.patch" target="_blank">pFad v3 Proxy</a></p><p><a href="http://rainy.clevelandohioweatherforecast.com/pFad/v4index.php?u=https://patch-diff.githubusercontent.com/raw/influxdata/influxdb-python/pull/823.patch" target="_blank">pFad v4 Proxy</a></p></body>
</html>