docs-v2/content/influxdb/v2.1/api-guide/client-libraries/python.md

---
title: Python client library
seotitle: Use the InfluxDB Python client library
list_title: Python
description: >
  Use the InfluxDB Python client library to interact with InfluxDB.
menu:
  influxdb_2_1:
    name: Python
    parent: Client libraries
influxdb/v2.1/tags: [client libraries, python]
aliases:
  - /influxdb/v2.1/reference/api/client-libraries/python/
  - /influxdb/v2.1/reference/api/client-libraries/python-cl-guide/
  - /influxdb/v2.1/tools/client-libraries/python/
weight: 201
---

Use the [InfluxDB Python client library](https://github.com/influxdata/influxdb-client-python) to integrate InfluxDB into Python scripts and applications.

This guide presumes some familiarity with Python and InfluxDB.
If just getting started, see [Get started with InfluxDB](/influxdb/v2.1/get-started/).

## Before you begin

1. Install the InfluxDB Python library:

    ```sh
    pip install influxdb-client
    ```

2. Ensure that InfluxDB is running.
   If running InfluxDB locally, visit http://localhost:8086.
   (If using InfluxDB Cloud, visit the URL of your InfluxDB Cloud UI.
   For example: https://us-west-2-1.aws.cloud2.influxdata.com.)

## Write data to InfluxDB with Python

We are going to write some data in [line protocol](/influxdb/v2.1/reference/syntax/line-protocol/) using the Python library.

1. In your Python program, import the InfluxDB client library and use it to write data to InfluxDB.

   ```python
   import influxdb_client
   from influxdb_client.client.write_api import SYNCHRONOUS
   ```

2. Define a few variables with the name of your [bucket](/influxdb/v2.1/organizations/buckets/), [organization](/influxdb/v2.1/organizations/), and [token](/influxdb/v2.1/security/tokens/).

   ```python
   bucket = "<my-bucket>"
   org = "<my-org>"
   token = "<my-token>"
   # Store the URL of your InfluxDB instance
   url="http://localhost:8086"
   ```

3. Instantiate the client. The `InfluxDBClient` object takes three named parameters: `url`, `org`, and `token`. Pass in the named parameters.

   ```python
   client = influxdb_client.InfluxDBClient(
      url=url,
      token=token,
      org=org
   )
   ```
    The `InfluxDBClient` object has a `write_api` method used for configuration.

4. Instantiate a **write client** using the `client` object and the `write_api` method. Use the `write_api` method to configure the writer object.

   ```python
   write_api = client.write_api(write_options=SYNCHRONOUS)
   ```

5. Create a [point](/influxdb/v2.1/reference/glossary/#point) object and write it to InfluxDB using the `write` method of the API writer object. The write method requires three parameters: `bucket`, `org`, and `record`.

   ```python
   p = influxdb_client.Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
   write_api.write(bucket=bucket, org=org, record=p)
   ```

### Complete example write script

```python
import influxdb_client
from influxdb_client.client.write_api import SYNCHRONOUS

bucket = "<my-bucket>"
org = "<my-org>"
token = "<my-token>"
# Store the URL of your InfluxDB instance
url="http://localhost:8086"

client = influxdb_client.InfluxDBClient(
    url=url,
    token=token,
    org=org
)

write_api = client.write_api(write_options=SYNCHRONOUS)

p = influxdb_client.Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
write_api.write(bucket=bucket, org=org, record=p)
```
## Query data from InfluxDB with Python

1. Instantiate the **query client**.

   ```python
   query_api = client.query_api()
   ```

2. Create a Flux query, and then format it as a Python string.

   ```python
   query = ' from(bucket:"my-bucket")\
   |> range(start: -10m)\
   |> filter(fn:(r) => r._measurement == "my_measurement")\
   |> filter(fn: (r) => r.location == "Prague")\
   |> filter(fn:(r) => r._field == "temperature" ) '
   ```

    The query client sends the Flux query to InfluxDB and returns a Flux object with a table structure.

3. Pass the `query()` method two named parameters:`org` and `query`.  

   ```python
   result = query_api.query(org=org, query=query)
   ```

4. Iterate through the tables and records in the Flux object.
   - Use the `get_value()` method to return values.
   - Use the `get_field()` method to return fields.

   ```python
   results = []
   for table in result:
     for record in table.records:
       results.append((record.get_field(), record.get_value()))

   print(results)
   [(temperature, 25.3)]
   ```

**The Flux object provides the following methods for accessing your data:**

- `get_measurement()`: Returns the measurement name of the record.
- `get_field()`: Returns the field name.
- `get_value()`: Returns the actual field value.
- `values`: Returns a map of column values.
- `values.get("<your tag>")`: Returns a value from the record for given column.
- `get_time()`: Returns the time of the record.
- `get_start()`: Returns the inclusive lower time bound of all records in the current table.
- `get_stop()`: Returns the exclusive upper time bound of all records in the current table.


### Complete example query script

```python
query_api = client.query_api()
query = ‘ from(bucket:"my-bucket")\
|> range(start: -10m)\
|> filter(fn:(r) => r._measurement == "my_measurement")\
|> filter(fn: (r) => r.location == "Prague")\
|> filter(fn:(r) => r._field == "temperature" )‘
result = query_api.query(org=org, query=query)
results = []
for table in result:
    for record in table.records:
        results.append((record.get_field(), record.get_value()))

print(results)
[(temperature, 25.3)]
```

For more information, see the [Python client README on GitHub](https://github.com/influxdata/influxdb-client-python).